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http://data.semanticuniverse.com/resource/semtech-2011-3775 http://purl.org/dc/elements/1.1/title Data Fusion for Command and Control
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http://data.semanticuniverse.com/resource/semtech-2011-3775 http://www.w3.org/2000/01/rdf-schema#label Data Fusion for Command and Control
http://data.semanticuniverse.com/resource/semtech-2011-3775 http://purl.org/dc/elements/1.1/description Semantic technology is helping the Department of Defense move from stove pipe systems with unique data models to a SOA approach to Command and Control (C2) and eventually to a private cloud architecture. Moving information from application specific schemas to XML significantly simplifies the creation of a comprehensive picture of situational awareness. Eliminating the need for costly and time consuming normalization of data allows for rapid assimilation of new data sources such as from a coalition partner and allows for data sources that do not fit well into the rows and columns of a relational database to be included in the common operating picture. <P> Virtually no DoD mission today uses data from a single system: <ul><li>UAVs <li>Ground forces <li>Multiple command stations <li>Onboard systems on the aircraft including targeting systems. <li>Some number of the above components are typically owned by countries other than the US</ul> A "halo" of icons is being used for each asset to bring together information from disparate sources including: <ul><li>Logistics <li>Ammo loadout <li>Geolocation <li>Rules of engagement with situational policies <li>Current capabilities <li>Existing missions</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3775 http://purl.org/dc/elements/1.1/abstract Fusion of multiple data sources into a common operating picture for effective C2 must frequently cope with new data sources and unknown schemas. An XML repository is an effective answer.
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http://data.semanticuniverse.com/resource/semtech-2011-4028 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4028 http://purl.org/dc/elements/1.1/title The Use of Semantic Technology for Execution and Reconciliation of Security Policies
http://data.semanticuniverse.com/resource/semtech-2011-4028 http://purl.org/dc/elements/1.1/abstract An approach to dynamic management and execution of security policies will be discussed. Policies are expressed using a security ontology and rules, and interpreted by an OWL2RL inference engine (BaseVISor).
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http://data.semanticuniverse.com/resource/semtech-2011-4028 http://www.w3.org/2000/01/rdf-schema#label The Use of Semantic Technology for Execution and Reconciliation of Security Policies
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http://data.semanticuniverse.com/resource/semtech-2011-4028 http://purl.org/dc/elements/1.1/description It is desirable to be able to modify existing, or add new security policies without restarting the system. Policies represented in a declarative language seem to be easier to handle to achieve such an objective. In this talk, an approach based on policies grounded in a security ontology expressed in OWL and policy rules expressed in a rule language will be discussed. Such policies are then interpreted by an OWL 2 RL reasoner (BaseVISor, a product of VIStology, Inc.). One of the additional features of this approach is the capability of reconciling multiple, possibly conflicting, policies and allowing access to resources when a nonempty intersection of the requirements can be found. This approach has been partially implemented. Demos are available for a number of scenarios: reconciliation of provisioning policies for OpenVPN, reconciliation of access control policies for Fedora and extending the expressiveness of access control policies for MS Groups Policy. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3998 http://purl.org/dc/elements/1.1/description Many application areas have needs for analyses of technologies of various types and their relationships with other technologies, articles, technical data, know-how, capabilities, organizations, services, and processes. Manufacturers and governments need to analyze their technology needs, plans, and investments in the context of the global marketplace. Governments have more specific needs to assess the needs for controls on technologies that have military or other critical applications, and which need to be supported through reliable supply chains or denied to adversaries. Semantic models of such technologies and their relationships are needed to capture their distinctive characteristics to support reasoning about the needs and potential consequences of investments in technologies relative to enterprise goals and capability needs. This briefing describes a rich ontology of technologies and their relationships, as used in analyses of military criticality for purposes of export control and damage assessment in cases of information compromises. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3998 http://purl.org/dc/elements/1.1/abstract An ontology is presented for technologies and their relationships, as used in analyses of military criticality in export control and in potential impacts of the compromise of controlled technological information and products.
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http://data.semanticuniverse.com/resource/politecnico-di-milano http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
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http://data.semanticuniverse.com/resource/semtech-2011-3787 http://purl.org/dc/elements/1.1/description For more than a decade, magazine and STM (Scientific, Technical, and Medical) publishers have been investigating semantic technologies to add value to their content. The technologies are used to create metadata that makes the content more searchable, more easily personalized, and provides a better foundation for more sophisticated applications. As examples, basic categorization and entity extraction have been used for years by some publishers to make their content more easily searchable, and to provide links to additional materials such as reports on companies mentioned in an article or to biographies of people mentioned. More sophisticated examples include mining bodies of 'facts' from published materials and building applications on top of those knowledge bases. <P> The semantic techniques have certain error rates, so their output needs to be reviewed (on at least a statistical sampling basis) and approved by people. Each individual enhancement can accumulate a surprising amount of provenance and approval information. When Elsevier recently undertook the design of a new workflow for semantic technologies, they looked to upcoming semantic annotation specifications like the Annotation Ontology (AO) and the Open Annotation Collaboration (OAC) for inspiration. <P> This talk provides a review of the requirements that shaped Elsevier's new RDF-XML format for conveying content enhancements, provides a brief introduction to the AO and OAC specifications, and provides information on the enhancement format we have defined. Early experiences with the format will be reported and likely directions for changes based on those experiences will be described. This talk provides a rare look into the development process at one large publisher as they use semantic technologies to reinvent themselves. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3787 http://purl.org/dc/elements/1.1/abstract Review Elsevier's requirements for metadata that is added to our content, then look at annotation format standards that guided the development of our new internal enhancement format. Describe early experience with the format and planned changes.
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http://data.semanticuniverse.com/resource/semtech-2011-3787 http://purl.org/dc/elements/1.1/title Annotation Formats and Content Enhancements
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http://data.semanticuniverse.com/resource/globocom http://xmlns.com/foaf/0.1/name Globo.com
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http://data.semanticuniverse.com/resource/semtech-2011-3968 http://swrc.ontoware.org/ontology#keywords knowledge-representation
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http://data.semanticuniverse.com/resource/semtech-2011-3968 http://purl.org/dc/elements/1.1/description When humans deal with knowledge, they intuitively and subconsciously interpret the expressions of knowledge, such as natural language statements or diagrams. This is difficult for computers: They operate mostly on the syntactic level, such as the sequence of letters that stands for a word, which in turn may describe an object or concept. This limitation has some important consequences, but it also allows computers to perform certain operations extremely quickly. The goal of this tutorial is to identify the difficulties computers have in dealing with knowledge, and to explore some opportunities that the use of computers offers. It will address issues like: <ul> <li>the storage and representation of knowledge, <li>how to organize knowledge in such a way that computers can perform more meaningful tasks on it, <li>approaches used to perform reasoning with computers, <li>the exchange of knowledge, and <li>the presentation of knowledge to humans</ul> It is intended for people who are familiar with the use of computers, but would like to obtain a better understanding on how to utilize them for knowledge-intensive tasks. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3968 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
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http://data.semanticuniverse.com/resource/semtech-2011-3968 http://purl.org/dc/elements/1.1/abstract An introductory exploration of the opportunities that computers offer and the difficulties they are faced with when dealing with knowledge.
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http://data.semanticuniverse.com/resource/michael-lang http://www.w3.org/2001/vcard-rdf/3.0#title CEO
http://data.semanticuniverse.com/resource/michael-lang http://www.w3.org/2001/vcard-rdf/3.0#org Revelytix
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://swrc.ontoware.org/ontology#keywords data-integration
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-3842 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-information-architecture
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http://data.semanticuniverse.com/resource/semtech-2011-3842 http://www.w3.org/2000/01/rdf-schema#label Relational to RDF Mapping In Practice
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://purl.org/dc/elements/1.1/abstract An in-depth presentation of the internal operation and the use of a relational to RDF mapping tool based on the W3C RDB-to-RDF Mapping Language
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://purl.org/dc/elements/1.1/description Detailed discussion of using the W3C RDB-to-RDF Mapping Language (R2RML) (work-in-process) to query relational databases via SPARQL. Based on real-world experience at Revelytix developing an open-source targeted R2RML product delivering mapping ontologies, this talk describes the mechanics of transforming SPARQL into SQL and practices for dealing with common mapping issues. The goal is to describe a technical approach and highlight issues in implementing and using the W3C R2RML language. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/david-mcneil
http://data.semanticuniverse.com/resource/semtech-2011-3842 http://purl.org/dc/elements/1.1/audience Case Study
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http://data.semanticuniverse.com/resource/semtech-2011-3842 http://purl.org/dc/elements/1.1/title Relational to RDF Mapping In Practice
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http://data.semanticuniverse.com/resource/daniel-hansch http://www.w3.org/2001/vcard-rdf/3.0#org Ontoprise GmbH
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http://data.semanticuniverse.com/resource/digital-enterprise-research-institute-(deri)-national-university-of-ireland-galway http://xmlns.com/foaf/0.1/name Digital Enterprise Research Institute (DERI), National University of Ireland, Galway
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http://data.semanticuniverse.com/resource/to-kim http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3386.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/to-kim http://www.w3.org/2001/vcard-rdf/3.0#org First Retail, Inc.
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http://data.semanticuniverse.com/resource/semtech-2011-3812 http://swrc.ontoware.org/ontology#keywords sparql
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http://data.semanticuniverse.com/resource/semtech-2011-3812 http://purl.org/dc/elements/1.1/description SPARQL is a query and update language for RDF data. <P> This tutorial will take a practical approach to SPARQL and be driven by examples. It will give the participant a solid understanding of how to write and design SPARQL queries, from basic access through to use of the newest features for data manipulation and exploration. It will then cover the update features of fine-grain update and graph management. The tutorial will feature practical sessions. <P> * Basic SPARQL <P> *RDF and data ? the SPARQL data model; Graph patterns, the foundation of SPARQL; Filtering values; Coping with semi-structure data <P> * Practical session I <P> * Advanced SPARQL features <P> *Grouping, aggregation and sub-query; Testing for missing data <P> * SPARQL Update <P> *SPARQL Update Language; SPARQL HTTP Update <P> * Practical session II <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3812 http://purl.org/dc/elements/1.1/title SPARQL: From Zero to 1.1
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http://data.semanticuniverse.com/resource/semtech-2011-3812 http://purl.org/dc/elements/1.1/abstract This tutorial will cover the writing of SPARQL, from basic query through to the new features of SPARQL 1.1, including update features and protocol.
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http://data.semanticuniverse.com/resource/semtech-2011-3884 http://swrc.ontoware.org/ontology#keywords performance
http://data.semanticuniverse.com/resource/semtech-2011-3884 http://purl.org/dc/elements/1.1/abstract This presentation focuses on a survey (not comprehensive) of proven techniques in performing real-time reasoning over semantic data and shows how some of these techniques may be applied in building commercial applications.
http://data.semanticuniverse.com/resource/semtech-2011-3884 http://www.w3.org/2000/01/rdf-schema#label Survey of Basic Techniques in Real-Time Reasoning of Semantic Data and Their Applications
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http://data.semanticuniverse.com/resource/semtech-2011-3884 http://purl.org/dc/elements/1.1/description The presentation begins with a high-level survey of some algorithmic techniques to reason over semantic data in near-real-time. The second part of the presentation focuses on some of the applications in financial and medical verticals. The third part of the presentation provides concrete examples of the application of the algorithms and a survey of real commercial applications with success deploying the aforementioned methodologies. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4071 http://swrc.ontoware.org/ontology#keywords stream-reasoning
http://data.semanticuniverse.com/resource/semtech-2011-4071 http://purl.org/dc/elements/1.1/abstract To introduce scalable reasoning and querying techniques as powerful tool to make use of highly dynamic data streams and large-scale ontologies.
http://data.semanticuniverse.com/resource/semtech-2011-4071 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4071 http://www.w3.org/2000/01/rdf-schema#label Tutorial on Stream Reasoning for Linked Data
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http://data.semanticuniverse.com/resource/semtech-2011-4071 http://purl.org/dc/elements/1.1/description The goal of the Stream Reasoning for Linked Data tutorial is twofold: to (1) introduce scalable reasoning and querying techniques as powerful tool to make use of linked data and large-scale ontologies, and to (2) present interesting research problems as well as current solutions in reasoning with highly dynamic data streams. The tutorial consists of five parts. It will begin with an introduction of linked data, as well as the Semantic Web standard ontology language OWL 2 and its related reasoning services. The introduction will include examples of how to make use of OWL 2 ontologies in linked data and how to use reasoning services to exploit linked data. It will then start with semantic processing of data streams explained using C-SPARQL, a continuous extension of SPARQL for querying RDF streams and RDF graphs. The third part of the tutorial will present stream reasoning techniques for RDFS and OWL2-RL. The fourth part will introduce approximate stream reasoning techniques for OWL2-DL. The last part of the tutorial is a hands-on session on some tools and systems related to the first four parts. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4071 http://purl.org/dc/elements/1.1/title Tutorial on Stream Reasoning for Linked Data
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http://data.semanticuniverse.com/resource/semtech-2011-3769 http://purl.org/dc/elements/1.1/description The use of semantic Web technologies to make the myriad of data in cyberspace accessible to intelligent agents is well established. However, a crucial type of information on the Web--and especially in life sciences--is imaging, and images are largely being overlooked by current semantic Web endeavors. Technological approaches and standards are being developed so that Web agents can access and process images in cyberspace. We are developing methods and tools to enable the transparent discovery and use of large distributed collections of medical images on the Web as well as within hospital information systems. <P> Our approach is to make the human and machine descriptions of image pixel content machine-accessible through "semantic annotation" tools that use ontologies in a manner that is transparent to consumers of images. New standards for describing image contents in ways that can be published on the semantic Web are maturing, and while this work is focused on images in the life sciences, it has broader applicability to all images on the Web. We will describe tools we have developed to collect semantic annotations directly from people as they view the images on imaging workstations. Image annotations, represented as instances in an OWL ontology can be serialized to a variety of formats, enabling interoperability among a variety of systems that contain images: medical records systems, image archives in hospitals, and the Semantic Web. In addition, the semantic annotations, being linked to the source images from which they derived, can enable dynamically retrieving the images associated with the semantic annotations or their particular values. Our ultimate goal is to enable semantic integration of images and all the related scientific data pertaining to their content so that researchers and physicians can have the best understanding of the biological and physiological significance of image content. In the consumer sector, these methods could enable better image search and user-centric imaging applications. Ultimately, new Semantic Web applications will emerge that will emerge that will help us to better exploit the wealth of images now at our fingertips. <ul><li>Images are prevalent on the Web, and especially important to the life sciences <li>Several important recent advances promise to make images and the information within them machine-accessible for semantic Web applications <li>New standards are emerging to enable images to be described (annotated) using ontologies and used in semantic Web applications <li>Several new image-based semantic web applications are already in development <li>While most of the current work with images is in the life sciences, the technologies and tools described are applicable to all types of images</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3769 http://purl.org/dc/elements/1.1/abstract We will provide an overview of new standards emerging for semantic Web technologies in imaging and will show cutting-edge work in applying semantic Web technologies for extracting semantic meaning from images for image mining, content-based image retrieval, and image-based computer reasoning.
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http://data.semanticuniverse.com/resource/semtech-2011-3769 http://purl.org/dc/elements/1.1/title Imaging on the Semantic Web: Computer Access and Reasoning with Images
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http://data.semanticuniverse.com/resource/john-o-biderman http://www.w3.org/2001/vcard-rdf/3.0#title Information Architect
http://data.semanticuniverse.com/resource/john-o-biderman http://www.w3.org/2001/vcard-rdf/3.0#org Harvard Pigrim Health Care
http://data.semanticuniverse.com/resource/semtech-2011-4137 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-05T17:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-4137 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-4137 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dave-mccomb
http://data.semanticuniverse.com/resource/semtech-2011-4137 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4137 http://www.w3.org/2000/01/rdf-schema#label SemTech 101: What is Semantic Technology?
http://data.semanticuniverse.com/resource/semtech-2011-4137 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4137 http://purl.org/dc/elements/1.1/description This session is for semantic beginners. Dave McComb will help you get the most out of the conference by bringing you up to speed on the technology, terminology and concepts that will be discussed over the next few days. <P> What is Semantics? What does it have to do with information systems? What is inference? How does it work? Description and Examples of semantic technology applied in a variety of settings <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4137 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2011-4137 http://purl.org/dc/elements/1.1/title SemTech 101: What is Semantic Technology?
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http://data.semanticuniverse.com/resource/mark-wallace http://www.w3.org/2001/vcard-rdf/3.0#title Principal Engineer, Semantic Applications
http://data.semanticuniverse.com/resource/mark-wallace http://www.w3.org/2001/vcard-rdf/3.0#org Modus Operandi
http://data.semanticuniverse.com/resource/gary-carlson-consulting http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
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http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/eric-prudhommeaux
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords warehousing
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://www.w3.org/2000/01/rdf-schema#label Federation, Warehousing, and the Semantic Web: Where Does the Data Live?
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords etl
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/rob-gonzalez
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords distributed-query
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#PanelEvent
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/description Semantic Web technologies bring information together to solve problems. But _how_ and _when_ does that information come together? <P> For many people, the Semantic Web vision includes a fully federated environment in which data sources are layered with SPARQL endpoints that provide partial answers to large questions in a distributed manner. A federation engine combines the answers and provides the most up-to-date answer possible to the questioner. <P> For others, the most effective way to pursue Semantic Web solutions is to bring the data together into a warehouse, a single location that can serve out answers to questions against the integrated information. <P> Come and hear advocates of both approaches present their experiences and their advice as to the best ways to achieve rapid and flexible data integration with semantic technologies. Panelists will discuss their experiences using semantic technologies for data integration, and will also discuss topics including: <P> * Are Semantic Web technologies appropriate for data federation? For data warehousing? * How do semantic technologies change the traditional arguments for and against federation and warehousing? * Are there situations that demand one architectural approach or another? * Are there feasible middle grounds that combine elements of both approaches? * What tools and standards are key to realizing federated semantic query or semantic warehousing? <P>
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords eii
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords data-integration
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kendall-grant-clark
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T10:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords data-warehouse
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/abstract This is a panel session to discuss and debate viewpoints concerning whether semantic technologies are better suited for a federated or warehoused approach to integrating data.
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords federation
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-lang
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://swrc.ontoware.org/ontology#keywords data-mart
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/lee-feigenbaum
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http://data.semanticuniverse.com/resource/semtech-2011-3770 http://purl.org/dc/elements/1.1/title Federation, Warehousing, and the Semantic Web: Where Does the Data Live?
http://data.semanticuniverse.com/resource/semtech-2011-3770 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-information-architecture
http://data.semanticuniverse.com/resource/ecs-university-of-southampton http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/ecs-university-of-southampton http://xmlns.com/foaf/0.1/name ECS, University of Southampton
http://data.semanticuniverse.com/resource/ecs-university-of-southampton http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/rob-vesse
http://data.semanticuniverse.com/resource/ecs-university-of-southampton http://www.w3.org/2000/01/rdf-schema#label ECS, University of Southampton
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://www.w3.org/2000/01/rdf-schema#label Can MDM Survive Without Semantic Technology
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://swrc.ontoware.org/ontology#keywords enterprise-semantics
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/neil-raden
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/dc/elements/1.1/title Can MDM Survive Without Semantic Technology
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T15:55:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/dc/elements/1.1/description Master Data Management is an attempt to harmonize reference data within an organization (and beyond in some cases), but its goals are often too ambitious and either the project fails,or is scaled back, more or less defeating the purpose. While to dream of harmonized data that people and applications can use to eliminate ambiguity and error is possible in principle, the representational framework for it, usually relational databases, is not up to the task. The solution is right in front of us - ontology and semantic technology. <P> At the very least, the investigatory and modeling efforts at the from of MDM are perfect targets for a dose of semantics, if not the entire process. <P> Attendees will be presented: <ul><li>A very brief history and current state of MDM and Data Governance <li>Some common problems MDM projects encounter <li>A description, with examples,of applications of ontology in the early phases of MDM <li>Decryption of a completely ontology-based MDM and the power of context and reasoning</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://swrc.ontoware.org/ontology#keywords master-data
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-enterprise-data-management
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3866 http://purl.org/dc/elements/1.1/abstract MDM relies on flat files and relational tables, but is desperately in need of the advantages of semantic technology
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords owl
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/dc/elements/1.1/title Interactive Visualization Tools for Ontologies
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jon-modell
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords ui
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T17:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/dc/elements/1.1/abstract Ontology visualization remains an unresolved challenge to the industry. We have developed a visualization lanaguage over the last year that we we intend to package and summit to the W3C for committee consideration.
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords tool(s)
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords language
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/dc/elements/1.1/description They say "a picture is worth a thousand words" and it is Revelytix's belief that the lack of meaningful visual representations of ontologies makes the whole idea of using them harder for the masses to adopt. In our efforts to create a robust interactive ontology visualization tool we have met many challenges. In this session we will address: <ul><li>Creating a meaningful visual language for OWL/RDF resources <li>Using color and decorations for different resource types and sub-types <li>Optimizing the layout of a diagram to illustrate hierarchy and other types of relationships while avoiding 'spaghetti' <li>Expanding and contracting classes <li>Representing property restrictions, associations and compound resources.</ul> <P> We will demonstrate our current visualization tool and how we have dealt with these issues. We will also discuss the challenges we face developing such a tool, integration with other semantic technologies and the possibility for creating a standard way to visualize OWL/RDF resources. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://www.w3.org/2000/01/rdf-schema#label Interactive Visualization Tools for Ontologies
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-standards
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords graph
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords visualization
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://swrc.ontoware.org/ontology#keywords modeling
http://data.semanticuniverse.com/resource/semtech-2011-3951 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://swrc.ontoware.org/ontology#keywords metadata
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://purl.org/dc/elements/1.1/audience Case Study
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-a-jennings
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://www.w3.org/2000/01/rdf-schema#label Using Ontology Based Metadata Mining for Faceted Navigation
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://swrc.ontoware.org/ontology#keywords faceted-navigation
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://purl.org/dc/elements/1.1/description Faceted navigation is a powerful method of navigating large content repositories, and provides a number of advantages over raw search. Our team developed a tool that uses semantic technologies (RDF and ontology) to automatically mine ArcGIS and ISO metadata to organize our client?s large GIS holdings into five facets: Location, Date, Theme, Data Format, Organization and Schema. We use geospatial reasoning (comparing bounding box metadata to a gazetteer) and a feature ontology (based on national feature data standards, industrial classification codes, and independent research into geospatial and imagery analyst practices) to generate the facets. We will present our methodology and lessons learned in developing this deployed government application. <ul> <li>Multiple Paths for Multiple Minds: GIS analysts browse the geodatabase starting with whichever facet is most meaningful or memorable to them. <li>Better than Search: A keyword search for ?lake? may come up empty, but browse ?Water Feature? and find ponds, fresh water, and reservoirs. <li>Data Profiling: Choosing the ?Hydrography? theme facet limits results to products about Hydrography. If the location facet now only displays the US and Mexico, the database holds only North American hydrographic information. <li>Gaps in data can quickly be detected, and the user can assess the breadth and scope of the existing dataset.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-content-management
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://purl.org/dc/elements/1.1/abstract Describe how one can use semantic technologies to mine existing product metadata to provide a powerful new way to navigate large content repositories.
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://swrc.ontoware.org/ontology#keywords gis
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://purl.org/dc/elements/1.1/title Using Ontology Based Metadata Mining for Faceted Navigation
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T17:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4083 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#ConferenceEvent
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http://data.semanticuniverse.com/resource/buddy-altus http://www.w3.org/2000/01/rdf-schema#label Buddy Altus
http://data.semanticuniverse.com/resource/buddy-altus http://xmlns.com/foaf/0.1/name Buddy Altus
http://data.semanticuniverse.com/resource/buddy-altus http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3381.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/buddy-altus http://www.w3.org/2001/vcard-rdf/3.0#title Director of Electronic Distribution
http://data.semanticuniverse.com/resource/buddy-altus http://www.w3.org/2001/vcard-rdf/3.0#org Avis Budget Group
http://data.semanticuniverse.com/resource/google-inc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/google-inc http://xmlns.com/foaf/0.1/name Google Inc.
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http://data.semanticuniverse.com/resource/google-inc http://www.w3.org/2000/01/rdf-schema#label Google Inc.
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http://data.semanticuniverse.com/resource/semtech-2011-4053 http://purl.org/dc/elements/1.1/title Modeling of Decisions: Why and How
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http://data.semanticuniverse.com/resource/semtech-2011-4053 http://purl.org/dc/elements/1.1/abstract Most modeling exercises are either data or processes-driven and triggered by IT implementations. Before deciding to instrument or automate business decisions, it is key to inventory and model them in a structured and systematic manner.
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http://data.semanticuniverse.com/resource/semtech-2011-4053 http://purl.org/dc/elements/1.1/description Most modeling exercises are focusing either on data or processes. We create data and object models to represent more or less static representations of the business. On the other end, we model processes to capture the sequence of tasks and this provides a dynamic representation of the enterprise. But most of the approaches miss the business meaning. Data models and structures are then mined to extract semantic elements and relations. On the process side, we add to process diagrams the capability to capture capability maps to establish a linkage with the business intent. Between these two orthogonal and complementary modeling dimensions which are mostly undertaken to support IT initiatives, we miss a fundamental element: the decisions taken at all levels in organizations. After establishing the importance of decisions in modeling exercises and complementarity with current approaches, we will describe a framework and method to inventory decisions to help deciding which ones should then for instance be instrumented, automated or governed. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3993 http://purl.org/dc/elements/1.1/description OWL is deceptive. It is the de facto ontology language of the Semantic Web, and many companies are interested in using it as an internal standard for business ontologies. Yet applying preconceived notions derived from more familiar modeling languages such as ERD or OOM can lead you wildly astray. This tutorial is aimed at the ontologist who has a working knowledge of OWL but would like to better understand some of its subtleties. Dave McComb and Simon Robe have taught their highly rated four-day seminar, Designing and Building Business Ontologies, around the world and have developed many business ontologies for clients. Based on these experiences, this tutorial will cover seven of the most common misconceptions they see students in their classes struggle with. These include how the Open World Assumption affects the semantics of different constructs, and the specific ways OWL differs from traditional business modeling languages and data base technologies. Using animated slide presentations and interactive class polls, Dave and Simon will walk you through some of the most interesting aspects of the language. If you've ever puzzled over the results of an OWL inference engine, this is the tutorial for you. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3993 http://purl.org/dc/elements/1.1/title Seven Things You Didn't Know About OWL
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http://data.semanticuniverse.com/resource/semtech-2011-3993 http://purl.org/dc/elements/1.1/abstract This tutorial will explain many of the non obvious aspects of OWL and why the results of inference often surprise even relatively experienced modelers.
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http://data.semanticuniverse.com/resource/semtech-2011-3963 http://purl.org/dc/elements/1.1/description The Federal Government's Universal Core Semantic Layer (UCore SL) ontology provides a good basis for building intelligence ontologies. Using it, along with selections from SUMO and new OWL 2 constructs, we have developed an integrated set for integrating a large collection of data sources and data models. <P> The intelligence community also has XML standards for metadata, including security markings. We have converted these into OWL, leveraging the richer data type and annotation property constructs provided by OWL 2. We would like to see these used as the basis for devising standards for the community. <P> In this talk, we briefly describe the reasons for creating the sets of ontologies, how the various resources (UCore SL, SUMO, XML standards, OWL 2) were leveraged to address various modeling challenges, and how we envision the new security ontology working. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3963 http://purl.org/dc/elements/1.1/title Unifying Universal Core, SUMO, OWL 2, and XML Standards to Build Intelligence Ontologies
http://data.semanticuniverse.com/resource/semtech-2011-3963 http://www.w3.org/2000/01/rdf-schema#label Unifying Universal Core, SUMO, OWL 2, and XML Standards to Build Intelligence Ontologies
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http://data.semanticuniverse.com/resource/semtech-2011-3963 http://swrc.ontoware.org/ontology#keywords data-model-integration
http://data.semanticuniverse.com/resource/semtech-2011-3963 http://purl.org/dc/elements/1.1/abstract Building integrated sets of ontologies which start with the Universal Core Semantic Layer (UCore SL), adapt relevant XML standards, and leverage new OWL 2 constructs.
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http://data.semanticuniverse.com/resource/semtech-2011-3878 http://purl.org/dc/elements/1.1/description Effective communication requires participants in a conversation to have a common understanding of the concepts and vocabulary exchanged. An ontology makes the terminology, concepts and relationships between them explicit. Ontologies can be extremely useful when people or systems, who need to exchange information for some business purpose, do not have a consistent understanding of a domain. <P> Over the last several years there has been increasing commercial interest in semantic technologies, particularly for enriched search and navigation, search engine optimization, business intelligence, and social networking applications. Rule-based manufacturing, product configuration, and financial services systems have been deployed in production systems for many years, although the underlying ontologies for rule systems are just beginning to be formalized and exploited independently. Fewer organizations have successfully deployed semantically rich systems that incorporate ontology-based metadata, sophisticated reasoning and explanation support. In other words, the technology has been around for decades, though it remains challenging for people to understand, let alone use effectively. <P> This tutorial, which has been given annually for several years now, provides a great introduction for those who are just beginning to ?get their feet wet? in the field, and is helpful in setting the stage for the rest of the conference. It provides an overview of the knowledge representation landscape and attempts to de-mystify some of the ?black art? of ontology development. We will outline basic methodology steps developed from a combination of <ul> <li> Domain analysis methodology from software engineering<br> <li> IDEF methods developed for the US Department of Defense<br> <li> Terminology analysis using ISO terminology and metadata standards<br> <li> Formal concept analysis<br> <li> Best practices from the Semantic Web (Best Practices and) Deployment working group<br> <li> Experience and lessons learned<br></ul> <P> Examples from several business domains will be provided, with a focus on the Web Ontology Language (OWL). We will describe appropriate uses of some of the profiles developed for OWL 2, and of more expressive languages such as Common Logic, to help potential users understand both the power and limitations they impose on applications in making such choices. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3878 http://purl.org/dc/elements/1.1/title Ontology 101: An Introduction to Knowledge Representation and Ontology Development
http://data.semanticuniverse.com/resource/semtech-2011-3878 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-3878 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3878 http://purl.org/dc/elements/1.1/abstract This tutorial provides a high-level overview of knowledge representation and ontologies, aimed at newcomers to semantic technologies. It covers background knowledge, OWL basics and modeling methodology, development tool chains, and how to make use of ontologies into real world applications.
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http://data.semanticuniverse.com/resource/semtech-2011-3878 http://www.w3.org/2000/01/rdf-schema#label Ontology 101: An Introduction to Knowledge Representation and Ontology Development
http://data.semanticuniverse.com/resource/semtech-2011-3878 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/elisa-kendall
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http://data.semanticuniverse.com/resource/semtech-2011-3878 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2011-4035 http://purl.org/dc/elements/1.1/title Not Only SPARQL, Not Just RDF/OWL: Special Enterprise-focused Semantic Capabilities for Effective Utilization of Semantic Technologies in Oracle Database
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http://data.semanticuniverse.com/resource/semtech-2011-4035 http://purl.org/dc/elements/1.1/abstract Enterprise computing requires more than just RDF/OWL and SPARQL. This presentation illustrates combination of these fundamental capabilities with SQL, Security, complex data types and ACID properties in Oracle Database.
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http://data.semanticuniverse.com/resource/semtech-2011-4035 http://purl.org/dc/elements/1.1/description Enterprises across the globe trust relational databases to securely store and manage the information needed to operate their businesses. Enterprise relational data is ubiquitous, enormous, and vary from simple scalars to complex data types that include unstructured Text and Spatial data. However, current use of relational data lacks in its ability to fully exploit the rich semantics of the data. The fundamental building blocks of Semantic Technologies ? RDF/OWL, and SPARQL ? need to be effectively combined with time-tested Relational Technologies ? SQL, Security, complex data types, and ACID properties ? to allow the enterprise user to take full advantage of the best from both the worlds: <P> This session will: <P> 1) Give a short overview of support for the following fundamental semantic technology capabilities in Oracle Database: <ul><li>RDF/OWL, SPARQL, entailment, and SPARQL endpoints</ul> <P> 2) Motivate and illustrate in detail the use and benefits of the following enterprise-focused semantic technology capabilities in Oracle Database: <ul><li>SPARQL embedded in SQL to query RDF/OWL and relational data together <li>Fine-grained enterprise class security for RDF/OWL data <li>Extensible Indexing and semantics-enriched querying of text columns in relational tables using 3rd-party pluggable NLP extractors for extracting RDF/OWL triples from text data <li>Semantic query of relational columns that reference ontology terms <li>SPARQL Filters that utilize native database object types and index types such as Spatial data</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3818 http://purl.org/dc/elements/1.1/abstract The Open Source Callimachus platform (http://callimachusproject.org) gives Web developers a simple and intuitive way to use Linked Data in their applications. Developers with knowledge of XHTML and RDFa markup can use Callimachus to rapidly build complex Linked Data applications.
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http://data.semanticuniverse.com/resource/semtech-2011-3818 http://purl.org/dc/elements/1.1/description Today's Web application developer is nothing short of a jack-of-all-trades, requiring deep knowledge of user interface design, browser vagaries, obscure testing strategies, database query languages and more. Modern Web applications incorporate a myriad array of data model paradigms, that challenge the author's comprehension. Adding Linked Data to the mix may seem overwhelming, but Web application development with Linked Data can be easy, and even fun. <P> The Open Source Callimachus platform (http://callimachusproject.org) gives Web developers a simple and intuitive way to use Linked Data in their applications. Developers with knowledge of XHTML and RDFa markup can use Callimachus' natural query-by-example system to rapidly build complex Linked Data applications. Full control over Javascript and CSS leaves a Web developer in familiar territory. Learn how quickly new Web applications can be created without coding. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3794 http://purl.org/dc/elements/1.1/abstract Discuss, with noted experts, the recent findings regarding the enterprise adoption of the Semantic Web though an extensive research study sponsored by the University of Maryland.
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http://data.semanticuniverse.com/resource/semtech-2011-3794 http://purl.org/dc/elements/1.1/title Semantic Web Adoption in the Enterprise ? Survey Results and Discussion
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http://data.semanticuniverse.com/resource/semtech-2011-3794 http://www.w3.org/2000/01/rdf-schema#label Semantic Web Adoption in the Enterprise ? Survey Results and Discussion
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http://data.semanticuniverse.com/resource/semtech-2011-3794 http://purl.org/dc/elements/1.1/description The Semantic Web enters the mainstream of information technology offering adopters significant advantages and possibly risks. A recent University of Maryland study sheds light on this critical phenomenon. This presentation/panel examines the research findings and contributes perspectives as to the current enterprise approach to employing the Semantic Web and associated technologies. <P> The discussion examines three key dimensions of enterprise adoption; industry posture, organization profile, and technology considerations and their relationship to Semantic Web adoption. Probing these three dimensions reveals which industries and organizations are adopting Semantic technologies and why they see Semantic technologies as beneficial to their needs. The discussion also highlights the reasons why industries and corporations are holding back on adoption and what advances are needed to gain adoption revealing business opportunities. * Discover current adoption of the Semantic Web in the Enterprise across both government and commercial companies * Discover the key uses of the Semantic Web in the Enterprise * Discover current roadblocks to adoption from both a technical and business perspective * Participate in discussions as to how to advance and improve the adoption * Relate to research model predicting future adoption trends <P>
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http://data.semanticuniverse.com/resource/tom-reamy http://xmlns.com/foaf/0.1/name Tom Reamy
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http://data.semanticuniverse.com/resource/tom-reamy http://www.w3.org/2001/vcard-rdf/3.0#org KAPS Group
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http://data.semanticuniverse.com/resource/semtech-2011-4005 http://purl.org/dc/elements/1.1/description You've just been sent a hand edited csv file with bunch of entity data that needs to be reconciled with your beautifully organized semantic store. Who do you gonna call? <P> Google Refine is a gem of data cleansing and reconciliation. A locally installable web service includes everything from simple search and replace to regular expressions to automatic clusterings of similar column values. Tools to catch outliers, easy recording of actions and more. <P> The presentation will show a few examples of using Google Refine on real data. We'll take noisy data and put it into a machine-usable format in the matter of minutes. <P> At Zemanta we have been using GR for couple of months and it quickly became one of our most beloved tools. We believe Google Refine belongs into a bag of tricks of every data wrangler! <P>
http://data.semanticuniverse.com/resource/semtech-2011-4005 http://purl.org/dc/elements/1.1/title Google Refine - Data Cleansing You Were Looking For
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http://data.semanticuniverse.com/resource/semtech-2011-4005 http://purl.org/dc/elements/1.1/abstract Introduction of the Google Refine as a tool for many different data cleansing needs - useful both for web and for enterprise. The tool that needs to be in everyone's bag of tricks.
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http://data.semanticuniverse.com/resource/semtech-2011-4005 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/andraz-tori
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http://data.semanticuniverse.com/resource/semtech-2011-3975 http://swrc.ontoware.org/ontology#keywords rdf.rb
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://swrc.ontoware.org/ontology#keywords ruby
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/dc/elements/1.1/title Ruby: Making the Semantic Web and Linked Data Easy
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://www.w3.org/2000/01/rdf-schema#label Ruby: Making the Semantic Web and Linked Data Easy
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http://data.semanticuniverse.com/resource/semtech-2011-3975 http://swrc.ontoware.org/ontology#keywords sparql
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http://data.semanticuniverse.com/resource/semtech-2011-3975 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/dc/elements/1.1/description Semantic technologies have been growing rapidly for the last several years, and have the potential to break out into a much larger market. But the combined learning curves of RDF, SPARQL, OWL and Linked Data can be daunting for new developers. Can we soften the learning curve, and successfully reach the mainstream market? <P> If we can reduce the initial complexity of these technologies, we can help developers build small, successful projects. And as these small projects grow, they'll encourage developers to learn more. <P> The learning curve for web development was reduced sharply by Ruby on Rails. Ruby can help us do the same thing for the Semantic Web. We survey some popular Ruby libraries, and discuss where to go from here. <ul><li>RDF.rb: The new standard for RDF in Ruby. <li>Object mappers and SPARQL query generation. <li>Social network analysis. <li>Serving and consuming linked data. <li>The future: Rails 3 and ActiveModel?</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/eric-kidd
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://swrc.ontoware.org/ontology#keywords object-relational-mapping
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/dc/elements/1.1/abstract To cross the chasm, we need to make RDF accessible to mainstream developers. With Ruby, we can make simple things easy, and reveal the full power of RDF gradually.
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http://data.semanticuniverse.com/resource/semtech-2011-3975 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3975 http://swrc.ontoware.org/ontology#keywords linked-data
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http://data.semanticuniverse.com/resource/dan-g-mccreary http://www.w3.org/2000/01/rdf-schema#label Dan G McCreary
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http://data.semanticuniverse.com/resource/dan-g-mccreary http://www.w3.org/2001/vcard-rdf/3.0#title Semantic Web Consultant
http://data.semanticuniverse.com/resource/dan-g-mccreary http://www.w3.org/2001/vcard-rdf/3.0#org Dan McCreary & Associates
http://data.semanticuniverse.com/resource/semtech-2011-3764 http://www.w3.org/2000/01/rdf-schema#label Building a Semantic Integration Framework to Support a Federated Query Environment in 5 Easy Steps
http://data.semanticuniverse.com/resource/semtech-2011-3764 http://swrc.ontoware.org/ontology#keywords solutions
http://data.semanticuniverse.com/resource/semtech-2011-3764 http://swrc.ontoware.org/ontology#keywords integration-framework
http://data.semanticuniverse.com/resource/semtech-2011-3764 http://swrc.ontoware.org/ontology#keywords linked-data
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http://data.semanticuniverse.com/resource/semtech-2011-3764 http://purl.org/dc/elements/1.1/description Semantic web standards are designed with data integration in mind. Key integration capabilities foundational to RDF include globally unique identifiers and the ability to merge information. Data integration is of high importance in life sciences where a wealth of different data sets contain separate, but related information. Integration can produce important new insights but existing technologies struggle to achieve this goal. As a result, interest in semantic technologies is high. While standards are important in supporting integration goals, tool capabilities are equally critical to produce true business value. This case study is based on a project that integrated more than twenty data sources ranging from a data warehouse to LDAP servers. We will present a journey into the development of a semantic infrastructure applied to integration of data using a federated query approach. <P> In this talk we will cover:- 1. Exposing databases as linked data sources. 2. Use of common ontologies to capture dataset information 3. Use of common ontologies to capture concept relationships 4. Use of common ontologies to capture resource connections 5. Development of framework services to utilise and act upon items 1-4 to retrieve integrated data using a federated approach. <P> We will also highlight the tools used, lessons learned, and advantages of the semantic approach and how pragmatic application of standards and technologies can produce real business value. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3764 http://purl.org/dc/elements/1.1/abstract Case study on using semantic web technology at a European Pharmaceutical company to build a semantic framework for federated data query and integration.
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http://data.semanticuniverse.com/resource/semtech-2011-3764 http://swrc.ontoware.org/ontology#keywords federated-query
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http://data.semanticuniverse.com/resource/semtech-2011-3764 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/philip-ashworth
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http://data.semanticuniverse.com/resource/semtech-2011-3764 http://purl.org/dc/elements/1.1/title Building a Semantic Integration Framework to Support a Federated Query Environment in 5 Easy Steps
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http://data.semanticuniverse.com/resource/semtech-2011-3945 http://swrc.ontoware.org/ontology#keywords transformational-government
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://swrc.ontoware.org/ontology#keywords semantic-community.info
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http://data.semanticuniverse.com/resource/semtech-2011-3945 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/brand-l-niemann
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http://data.semanticuniverse.com/resource/semtech-2011-3945 http://purl.org/dc/elements/1.1/description We are restarting the Semantic Interoperability Community of Practice (by popular demand) and are working on a series of meetings/workshops in 2011 in collaboration with a numbers of groups and individuals based on three things: (1) Mapping Vivek Kundra's 25 point plan to CoPs and individuals; (2) The new OASIS Technical Committee on Transformational Government; and (3) Our very successful SICoP meeting in 2009. See From E-Government to Transformational Government Wiki page and slides at <a href="http://semanticcommunity.info/From_E-Government_to_Transformational_Government">http://semanticommunity.info/From_E-Government_to_Transformational_Government</a>. <P> To seed this activity we have prepared a series of Data Science Products for Social Business Intelligence with Open Government Data Using Semantics that will be demonstrated along with highlights from the meetings we have conducted so far. <P> The ideas we would like to explore with you include how best we might: (1) Harvest and package content from the sorts of meetings & demonstrations we have done and are planning for dissemination through media channels -- publications, digital, events, etc.; and (2) Collaborate together to develop and conduct a series of educational events that would reach the right audiences as well as benefit all parties involved. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://swrc.ontoware.org/ontology#keywords community-infrastructure-sandbox-for-2011
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://purl.org/dc/elements/1.1/audience Case Study
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http://data.semanticuniverse.com/resource/semtech-2011-3945 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mills-davis
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://swrc.ontoware.org/ontology#keywords open-government-data
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://swrc.ontoware.org/ontology#keywords social-business-intelligence
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://purl.org/dc/elements/1.1/title SICoP 2011: Transforming Government through Innovation with Semantic Technologies
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://www.w3.org/2000/01/rdf-schema#label SICoP 2011: Transforming Government through Innovation with Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2011-3945 http://swrc.ontoware.org/ontology#keywords knowledge-centric-approaches
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#ConferenceEvent
http://data.semanticuniverse.com/resource/semtech-2011-3945 http://purl.org/dc/elements/1.1/abstract How knowledge-centric approaches (semantic / ontology-based) drive value.
http://data.semanticuniverse.com/resource/semtech-2011-4077 http://purl.org/dc/elements/1.1/abstract The development and exploitation of linked data and semantic services for modern drug discovery.
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http://data.semanticuniverse.com/resource/semtech-2011-4077 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-4077 http://purl.org/dc/elements/1.1/description Modern drug discovery requires access to machine-understandable data that can be searched, retrieved, and subsequently analyzed using a wide array of analytical software and services. In this presentation, I will demonstrate the prediction of chemical toxicity through a set of SADI-compliant semantic web services that i) retrieve data from Bio2RDF, the largest linked open data project for the life sciences, ii) compute chemical attributes using the open source Chemical Development Kit (CDK), and iii) ultimately make predictions using formalized (machine understandable) decision trees. I will show how one can make use of the SADI-enabled SHARE client to automatically identify and invoke the necessary chemical semantic web services by reasoning about formalized service inputs and outputs described using basic types and relations from OWL the Semanticscience Integrated Ontology (SIO) and descriptors from the Chemical Information Ontology (CHEMINF). If you want to see the potential of the Semantic Web being realized, this talk is for you.<ul> <li>Bio2RDF provides over 30 billion triples to the Linked Open Data cloud <li>SADI services are easy to implement as they comply to a few simple conventions <li>Semantic web services may be parameterized and can also provide explicit data provenance <li>Effective toxicology regulatory regimes demand a transparent understanding of drug toxicity</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4077 http://swrc.ontoware.org/ontology#keywords service-composition
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http://data.semanticuniverse.com/resource/semtech-2011-4077 http://www.w3.org/2000/01/rdf-schema#label Predicting Drug Toxicity from Integrated Data and Services on the Life Science Semantic Web
http://data.semanticuniverse.com/resource/semtech-2011-4077 http://swrc.ontoware.org/ontology#keywords toxicity
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http://data.semanticuniverse.com/resource/semtech-2011-4077 http://purl.org/dc/elements/1.1/title Predicting Drug Toxicity from Integrated Data and Services on the Life Science Semantic Web
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http://data.semanticuniverse.com/resource/emanuele-della-valle http://www.w3.org/2001/vcard-rdf/3.0#org Politecnico di Milano
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http://data.semanticuniverse.com/resource/semtech-2011-4132 http://purl.org/dc/elements/1.1/description The U.S. Department of Defense is the largest and most complex organization in the world. It?s reach is truly galactic, and with 4 million active employees and tens of millions of retirees and dependents in all parts of the world, no organization is more of a management challenge. Decades of piecemeal implementation of IT systems and services has resulted in an unsustainable cost structure and notable failures to deliver needed business capabilities. It is clear that business as usual is not a sensible way ahead. Could semantic technologies, notably data constructed with RDF OWL, and capabilities delivered as services within a SOA be a new paradigm for business intelligence and business applications? This talk will explore these issues, and the Department?s Proof of Delivery (PoD) projects. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3776 http://purl.org/dc/elements/1.1/description In a Semantic MediaWiki implementation we had a requirement to protect certain content from editing by end users, since the pages were generated into the wiki programatically out of a database. Yet we still wanted user annotations to be visible in these protected articles and enable users to place hyperlinks to their own articles on the protected pages. This session will show how, using SMW semantic properties, the power of transclusion, semantic forms and wiki templates, we achieved seamless integration between generated content and user-contributed content in the wiki. This has general application in collaboration and knowledge management solutions where some content is protected yet cross-linking to and from content of any type is desired. We'll do a very brief overview of MediaWiki and its semantic extensions before getting to the crux of our solution, but some prior familiarity will be helpful. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/description We seldom see "real web" developers diving deep into semantic web technologies. So what's wrong with those guys? Let's ask them! <P> We'll be asking how semantic web tasted to classical web developers when they first tried it. Why haven't they left relation databases and imperative programming behind? What does semantic future mean for them? <P> Some of the topics - RDFa, do they care beyond Open Graph and rich snippets? - what are Rails of the semantic web? - RDF as a data model inside web apps? - mixing triple stores and relational databases, water and oil? - are JSON & REST really enough for everything? - can open governmental data lure people into semweb? <P> Hopefully we'll see where semweb can be used in web development today and what the future holds. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords rdfa
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords linking-open-data
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://www.w3.org/2000/01/rdf-schema#label Semantic Web Through the Eyes of "Real Web" Developers
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-web-applications
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/abstract A lively debate on what semantic web has to offer to classical web developers. Panel consisting of web developers who had at least a brief touch with semweb, but aren't pros.
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/joe-devon
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords web-apps
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/andraz-tori
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http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords web-development
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http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords rails
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://purl.org/dc/elements/1.1/title Semantic Web Through the Eyes of "Real Web" Developers
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords lod
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T08:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3999 http://swrc.ontoware.org/ontology#keywords open-graph
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://www.w3.org/2000/01/rdf-schema#label Stock Price Prediction Based on Semantic Analysis of Financial Web Communities
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T13:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/dc/elements/1.1/title Stock Price Prediction Based on Semantic Analysis of Financial Web Communities
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/dc/elements/1.1/abstract A range of German ?Financial Web Sources? (Forums, Blogs, Twitter and online News) are monitored and analyzed since 2009. Together with the Universities of St.Gallen and Zürich we have developed several prediction models.
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/dc/elements/1.1/description A good range of German ?Financial Web Communities? (Forums, Blogs, Twitter, online News) are monitored since 2009 and analyzed by semantic technologies. This web based monitoring system is focused on the discussion of ?Structured Products/ETF?. The semantic analysis of more than 8 mio posts/documents is showing a very interesting and consistent result. This monitoring and analysis system was developed in cooperation with a large Swiss Investment Bank in order to support their product development and marketing planning and controlling for ETF-products. First visual analysis of (qualitative and quantitative) discussion patterns indicated interesting results. In a joint-venture with the Universities of St.Gallen (HSG) and Zürich we have realized a research program to develop and test different forecast models. This presentation is giving insights into the existing (and growing) highly qualified ?Financial Web Community?; the methods to monitor and analyze millions of posts/documents in order to use the results as a verified indicator for stock trading strategies, product development and marketing instruments. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/leo-keller
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T14:10:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4090 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/brand-new-media-partners http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
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http://data.semanticuniverse.com/resource/brand-new-media-partners http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/robert-kost
http://data.semanticuniverse.com/resource/brand-new-media-partners http://www.w3.org/2000/01/rdf-schema#label Brand New Media Partners
http://data.semanticuniverse.com/resource/souripriya-das http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/souripriya-das http://www.w3.org/2000/01/rdf-schema#label Souripriya Das
http://data.semanticuniverse.com/resource/souripriya-das http://xmlns.com/foaf/0.1/name Souripriya Das
http://data.semanticuniverse.com/resource/souripriya-das http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/1916.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/souripriya-das http://www.w3.org/2001/vcard-rdf/3.0#title Architect
http://data.semanticuniverse.com/resource/souripriya-das http://www.w3.org/2001/vcard-rdf/3.0#org Oracle
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T07:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords design
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/dc/elements/1.1/description Are you thinking about how to achieve designs that will get a positive response from your users? Are you wondering how to refine an interface to work well with semantic data? While the ?magic? in design can?t be boiled down to a few simple rules, there are things you can do that will help get your project started on the right path. This talk will offer ideas that help you focus on usable design. <P> You will hear about 10 best practices you can do that are aligned to the needs of semantic technologies and data. What you learn will be brought to life through 5 examples that tell the story of achieving good designs that support user needs. Finally, together we will discuss two practical actions that you can take to focus your work on design and increase the value of your products. <P> Participants will: Gain an overview of the key analysis and design activities that produce the insights necessary for good user experience design Explore a framework for how to review site designs and consider design options, looking at user goal accomplishment and the overall experience as a way of assessing what works Identify where and how to effectively involve actual users in the analysis > design > evaluation process <P>
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T08:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-web-services
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/dc/elements/1.1/abstract This talk focuses on the key things that support user needs when designing semantic-enabled applications. Some design principles are universal, adopted from existing practices. Others are unique to semantic technologies.
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords visualization
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http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords user-experience
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords user-interface
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords usability
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords interaction
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://www.w3.org/2000/01/rdf-schema#label Design 10:5:2 ? 10 Best Practices, 5 Examples, 2 Actions
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/duane-degler
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords ui-development
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://purl.org/dc/elements/1.1/title Design 10:5:2 ? 10 Best Practices, 5 Examples, 2 Actions
http://data.semanticuniverse.com/resource/semtech-2011-4060 http://swrc.ontoware.org/ontology#keywords data-entry
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http://data.semanticuniverse.com/resource/yves-jaques http://www.w3.org/2000/01/rdf-schema#label Yves Jaques
http://data.semanticuniverse.com/resource/yves-jaques http://xmlns.com/foaf/0.1/name Yves Jaques
http://data.semanticuniverse.com/resource/yves-jaques http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3302.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/yves-jaques http://xmlns.com/foaf/0.1/onlineAccount http://twitter.com/FAO_AIMS
http://data.semanticuniverse.com/resource/yves-jaques http://www.w3.org/2001/vcard-rdf/3.0#title Information and Knowledge Management Officer
http://data.semanticuniverse.com/resource/yves-jaques http://www.w3.org/2001/vcard-rdf/3.0#org Food and Agriculture Organization of the United Nations
http://data.semanticuniverse.com/resource/brian-sletten http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/brian-sletten http://www.w3.org/2000/01/rdf-schema#label Brian Sletten
http://data.semanticuniverse.com/resource/brian-sletten http://xmlns.com/foaf/0.1/name Brian Sletten
http://data.semanticuniverse.com/resource/brian-sletten http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/191.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/brian-sletten http://www.w3.org/2001/vcard-rdf/3.0#title President
http://data.semanticuniverse.com/resource/brian-sletten http://www.w3.org/2001/vcard-rdf/3.0#org Bosatsu Consulting, Inc.
http://data.semanticuniverse.com/resource/robert-a-stanley http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/robert-a-stanley http://www.w3.org/2000/01/rdf-schema#label Robert A Stanley
http://data.semanticuniverse.com/resource/robert-a-stanley http://xmlns.com/foaf/0.1/name Robert A Stanley
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http://data.semanticuniverse.com/resource/robert-a-stanley http://xmlns.com/foaf/0.1/onlineAccount http://tinyurl.com/iofbook
http://data.semanticuniverse.com/resource/robert-a-stanley http://www.w3.org/2001/vcard-rdf/3.0#title CEO
http://data.semanticuniverse.com/resource/robert-a-stanley http://www.w3.org/2001/vcard-rdf/3.0#org IO Informatics, Inc.
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http://data.semanticuniverse.com/resource/nasa-johnson-space-center-itams-contract http://xmlns.com/foaf/0.1/name NASA Johnson Space Center, ITAMS Contract
http://data.semanticuniverse.com/resource/nasa-johnson-space-center-itams-contract http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/sarah-ann-berndt
http://data.semanticuniverse.com/resource/nasa-johnson-space-center-itams-contract http://www.w3.org/2000/01/rdf-schema#label NASA Johnson Space Center, ITAMS Contract
http://data.semanticuniverse.com/resource/gary-carlson http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/gary-carlson http://www.w3.org/2000/01/rdf-schema#label Gary Carlson
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http://data.semanticuniverse.com/resource/gary-carlson http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/2597.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/gary-carlson http://www.w3.org/2001/vcard-rdf/3.0#title Principal
http://data.semanticuniverse.com/resource/gary-carlson http://www.w3.org/2001/vcard-rdf/3.0#org Gary Carlson Consulting
http://data.semanticuniverse.com/resource/david-s-newman http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/david-s-newman http://www.w3.org/2000/01/rdf-schema#label David S Newman
http://data.semanticuniverse.com/resource/david-s-newman http://xmlns.com/foaf/0.1/name David S Newman
http://data.semanticuniverse.com/resource/david-s-newman http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/2566.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/david-s-newman http://www.w3.org/2001/vcard-rdf/3.0#title Strategic Planning Manager Enterprise Architecture
http://data.semanticuniverse.com/resource/david-s-newman http://www.w3.org/2001/vcard-rdf/3.0#org Wells Fargo
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/dc/elements/1.1/title A Tool for Visualizing and Managing Complex Rule Bases
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://swrc.ontoware.org/ontology#keywords rule-elicitation
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://swrc.ontoware.org/ontology#keywords rule-base-visualization
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-rules
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://swrc.ontoware.org/ontology#keywords owl/swrl
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/dc/elements/1.1/description Rule bases are common in many business rule applications and other types of intelligent systems. As the size of such rule bases grows and the interrelationships between rules become more complex, understanding and managing the content of the rule base can be quite difficult. In this talk, we present novel rule management techniques that can address this challenge. Our basic approach identifies common syntactic patterns in rule bases, which we use to support categorization, visualization, and paraphrasing of individual rules. We have developed rule-elicitation technique that provide users rule templates based on existing syntactic patterns in a rule base. We also have created a technique to visualize logical dependencies among rules to discover patterns based on these dependencies. We have implemented and validated these techniques within Axiomé, a plug-in tool we developed for managing Semantic Web Rule Language (SWRL) rules within the freely available, open-source Protégé-OWL knowledge-modeling environment. <ul><li>Rule base management is challenging when a rule base is large or complex. <li>Techniques for visualization, categorization, and elicitation of rule bases can facilitate their management. <li>Our approach uses analyses of syntactic signatures and logical dependencies to support these techniques. <li>We have applied these methods to the SWRL rule language, the default standard for OWL ontologies. <li>We have implemented and validated these techniques as a software plug-in for Protégé, the most widely used knowledge acquisition environment for ontologies.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/amar-k-das
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://swrc.ontoware.org/ontology#keywords protégé
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T15:55:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://www.w3.org/2000/01/rdf-schema#label A Tool for Visualizing and Managing Complex Rule Bases
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/dc/elements/1.1/abstract We present methods for managing, visualizing and acquiring rules for complex and large rule bases that are specified using the Semantic Web Rule Language.
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://swrc.ontoware.org/ontology#keywords rule-base-management
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4030 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/institute-for-defense-analyses http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/institute-for-defense-analyses http://xmlns.com/foaf/0.1/name Institute for Defense Analyses
http://data.semanticuniverse.com/resource/institute-for-defense-analyses http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/brian-a-haugh
http://data.semanticuniverse.com/resource/institute-for-defense-analyses http://www.w3.org/2000/01/rdf-schema#label Institute for Defense Analyses
http://data.semanticuniverse.com/resource/rensselaer-polytechnic-institute http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/rensselaer-polytechnic-institute http://xmlns.com/foaf/0.1/name Rensselaer Polytechnic Institute
http://data.semanticuniverse.com/resource/rensselaer-polytechnic-institute http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/li-ding
http://data.semanticuniverse.com/resource/rensselaer-polytechnic-institute http://www.w3.org/2000/01/rdf-schema#label Rensselaer Polytechnic Institute
http://data.semanticuniverse.com/resource/ontologica http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/ontologica http://xmlns.com/foaf/0.1/name Ontologica
http://data.semanticuniverse.com/resource/ontologica http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/barbara-h-starr
http://data.semanticuniverse.com/resource/ontologica http://www.w3.org/2000/01/rdf-schema#label Ontologica
http://data.semanticuniverse.com/resource/mayo-clinic http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
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http://data.semanticuniverse.com/resource/semtech-2011-3940 http://purl.org/dc/elements/1.1/abstract We leverage modified NCI disease and proprietary gene taxonomies in text analysis and search. Comparing solutions, we learn strengths and weaknesses of the taxonomies, our approaches, and the business requirements.
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http://data.semanticuniverse.com/resource/semtech-2011-3940 http://purl.org/dc/elements/1.1/title Repurposing Disease and Gene Taxonomies for Text Analysis and Search
http://data.semanticuniverse.com/resource/semtech-2011-3940 http://purl.org/dc/elements/1.1/description We set out to address two problems that involve common vocabularies. We supported a research effort to validate relationships between a set of genes and oncology diseases through text analysis. Concurrently, we developed a pilot search solution for our scientists to apply the gene and disease taxonomies to enhance findability and navigability of results. We chose the NCI oncology disease branch for the text analysis work based on evaluation that included coverage of diseases of interest, format (inverted form vs spoken language), and synonyms. We modified the NCI taxonomy to be a five level taxonomy, with the top two levels by Site (Organ System, Organ) and the next two levels by Morphology, with the bottom level including all leaf nodes. For the search pilot using Microsoft FAST, we treated the two level Site and two level Morphology taxonomies as independent taxonomies for categorization and navigation. <P> Our key takeaways from these projects: · NCI (and other) standard taxonomies are not well suited to text mining or search navigation naturally · Derivation of a modified taxonomy must balance navigability (usually biased toward fewer, higher level groupings) and granularity · It is critical to clearly convey this balance to end users, who have some uses that require navigability and some that require granularity <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4072 http://purl.org/dc/elements/1.1/description Within eBook reader devices and applications, users were limited to simple text searches and dictionary look-ups in order to find additional semantic information with an eBook. The latest revision of the EPUB spec now provides that ability to add semantic markup within the text of the eBook. The addition of semantic markup within the text will allow for more intelligent searches (alternate spellings, taxonomy based searching, etc.) as well as open new possibilities for presenting the information within the text. <P> The presentation will show how the markup works within the text, how this markup can be generated from other sources, such as the Linked Data Cloud, and discuss ways that the additional information can be presented in the reading environment. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4072 http://purl.org/dc/elements/1.1/abstract The latest revision of the EPUB spec adds the ability to marks semantics within the text of an eBook. This presentation will show how this is done and possible applications.
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http://data.semanticuniverse.com/resource/semtech-2011-4072 http://purl.org/dc/elements/1.1/title Smart Books: Semantic Markup in eBooks
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http://data.semanticuniverse.com/resource/semtech-2011-3910 http://purl.org/dc/elements/1.1/abstract VocBench is a web-based, workflow-enabled, multi-lingual vocabulary management tool developed by the UN. It transforms thesauri, authority lists and glossaries into SKOS/RDF concept schemes for use in linked data environments.
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http://data.semanticuniverse.com/resource/semtech-2011-3910 http://purl.org/dc/elements/1.1/title VocBench, A Web-based OWL/SKOS Multi-lingual Vocabulary Management Tool
http://data.semanticuniverse.com/resource/semtech-2011-3910 http://purl.org/dc/elements/1.1/description VocBench is a web-based multi-lingual vocabulary management tool developed by the Food and Agriculture Organization of the United Nations. It transforms thesauri, authority lists and glossaries into SKOS/RDF concept schemes for use in a linked data environment. <P> It supports a growing set of user communities, including the global, distributed group of terminologists who manage AGROVOC, a multi-lingual agricultural thesaurus of 40,000 terms in over 20 languages. <P> VocBench also manages the workflow and editorial processes implied by vocabulary evolution such as user rights/roles, validation and versioning. In addition VocBench features a flexible set of auxiliary web services that permit other applications to interact with VocBench vocabularies using REST queries. <P> Developed in Java, it leverages the Google Web Toolkit to support a rich-client interface and is released under a GPL license. FAO seeks interested partners to broaden the community base and ensure long-term sustainability. <P> -- What is VocBench? -- How does VocBench work (demo)? -- Who is the VocBench community? -- What are the current/future development plans for VocBench? -- What is the long-term sustainability of VocBench? <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3825 http://purl.org/dc/elements/1.1/description Today, many sensor networks and their applications employ a brute force approach to collecting and analyzing the huge volumes of sensor data currently generated. Such an approach often wastes valuable energy and computational resources by unnecessarily tasking sensors and generating observations of minimal use. People, on the other hand, have evolved sophisticated mechanisms to efficiently perceive their environment. This is accomplished through an ability to isolate the signal from the noise ? by focusing attention and seeking out those observations containing useful information. With the rise of social networking technology, people are now empowered to share their observations and perceptions with the world. A satisfying integration of such knowledge with observations generated by machine sensors, however, remains elusive. In this talk, we describe and demonstrate a semantics driven active perception prototype ? derived from cognitive theory ? that may be used to more effectively integrate observations from both machine sensors and people in order to efficiently generate comprehensive and robust situation awareness. <ul><li>Efficient generation of robust situation awareness. <li>Focusing attention to collect and analyze only those observations containing useful information. <li>Integration of observations from machine sensors and citizen sensing.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3825 http://swrc.ontoware.org/ontology#keywords social-network
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http://data.semanticuniverse.com/resource/semtech-2011-3825 http://swrc.ontoware.org/ontology#keywords situation-awareness
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http://data.semanticuniverse.com/resource/semtech-2011-3825 http://www.w3.org/2000/01/rdf-schema#label Active Perception Over Machine and Citizen Sensing
http://data.semanticuniverse.com/resource/semtech-2011-3825 http://purl.org/dc/elements/1.1/title Active Perception Over Machine and Citizen Sensing
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http://data.semanticuniverse.com/resource/semtech-2011-3825 http://purl.org/dc/elements/1.1/abstract Through active perception and the integration of machine observations and social data, an engagement of cognitive theory with Semantic Web technology will enable the generation of robust situation awareness.
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http://data.semanticuniverse.com/resource/semtech-2011-4138 http://purl.org/dc/elements/1.1/description Conference Chair Dave McComb offers an advance survey of the conference agenda and suggests some discussions and topics to watch for over the next few days. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4138 http://purl.org/dc/elements/1.1/title Hot Topics in Semantics this Year
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http://data.semanticuniverse.com/resource/semtech-2011-3897 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/axel-polleres
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://purl.org/dc/elements/1.1/abstract In current application environments, integrating RDF and XML data is not an easy task. XSPARQL is a new transformation language, published as a W3C member submission, that greatly simplifies such transformations.
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://swrc.ontoware.org/ontology#keywords xml
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-3897 http://purl.org/dc/elements/1.1/title Integrating RDF and XML with XSPARQL
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://purl.org/dc/elements/1.1/description On the Web and in corporate environments there exists a lot of XML data in various formats. XQuery and XSLT serve as a query and transformation language for XML, but as also RDF becomes mainstream, a gap becomes apparent between these two formats. Convenient languages and tools to transform between XML and RDF or merge sources of either format are missing, since both XQuery and SPARQL alone only insufficiently address this task. XSPARQL is a hybrid language that provides an integration framework for XML, RDF and in its next release even JSON and relational data by partially combining several languages such as XQuery, SPARQL and SQL. XSPARQL provides concise solutions for mapping between XML and RDF in either direction. As a use case, we can semantically enhance data both these input formats by, for example, mashing up data from DBPedia. We will: <ul><li>Discuss the major differences between RDF and XML and challenges of merging them <li>Introduce the XSPARQL language and its features by example <li>Provide hands-on experience by an online demo (http://xsparql.deri.org/demo/) <li>Discuss extensions and additional features of the coming XSPARQL1.1 release along with more use cases: ** The inclusion of SQL will allow to access data stored in relational databases and to easily combine it with data that is currently present in the Web. ** Consuming JSON enables us to draw information from Web2.0 sites.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3897 http://www.w3.org/2000/01/rdf-schema#label Integrating RDF and XML with XSPARQL
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http://data.semanticuniverse.com/resource/oreilly-media http://xmlns.com/foaf/0.1/name O'Reilly Media
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http://data.semanticuniverse.com/resource/joel-natividad http://www.w3.org/2000/01/rdf-schema#label Joel Natividad
http://data.semanticuniverse.com/resource/joel-natividad http://xmlns.com/foaf/0.1/name Joel Natividad
http://data.semanticuniverse.com/resource/joel-natividad http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3362.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/joel-natividad http://www.w3.org/2001/vcard-rdf/3.0#org TCG Software, Wholly owned subsidiary of The Chatterjee Group
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://purl.org/dc/elements/1.1/title Implementing Digital Provenance on the World Wide Web Using Semantic Web Technology
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://purl.org/dc/elements/1.1/description In response to the President?s call to secure the nation?s cyber infrastructure, the National Cyber Leap Year Summit was convened to identify the ?game-changing? technologies needed to secure cyberspace. One of the technologies identified is Digital Provenance (DP). DP is metadata that establishes the chain-of-custody information needed for users to make trust decisions about digital data. The SemWeb community is already working with DP technologies through the development of several markup languages and the W3C has an incubator group that is unifying the existing languages toward a draft recommendation. However, significant work remains to be done in the development of actual tools that allow users to author and view DP metadata. This talk will feature: <P> A introduction to DP including a review of the current state-of-the-art; A use case on how an DP information can enhance everyday web browsing; An approach for developing tools that utilize DP. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/greg-joiner
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-09T11:10:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://swrc.ontoware.org/ontology#keywords digital
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://swrc.ontoware.org/ontology#keywords trust
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://swrc.ontoware.org/ontology#keywords cyber
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://www.w3.org/2000/01/rdf-schema#label Implementing Digital Provenance on the World Wide Web Using Semantic Web Technology
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://swrc.ontoware.org/ontology#keywords security
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://purl.org/dc/elements/1.1/abstract This talk presents an introduction to digital provenance including a review of the current state-of-the-art and outlines an approach for developing new Semantic Web Tools that utilize digital provenance.
http://data.semanticuniverse.com/resource/semtech-2011-3982 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2011-3982 http://swrc.ontoware.org/ontology#keywords provenance
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http://data.semanticuniverse.com/resource/neil-raden http://www.w3.org/2000/01/rdf-schema#label Neil Raden
http://data.semanticuniverse.com/resource/neil-raden http://xmlns.com/foaf/0.1/name Neil Raden
http://data.semanticuniverse.com/resource/neil-raden http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3262.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/neil-raden http://www.w3.org/2001/vcard-rdf/3.0#org Hired Brains
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http://data.semanticuniverse.com/resource/gavin-james-carothers http://www.w3.org/2000/01/rdf-schema#label Gavin James Carothers
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http://data.semanticuniverse.com/resource/gavin-james-carothers http://www.w3.org/2001/vcard-rdf/3.0#title Semantic Solutions Developer
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http://data.semanticuniverse.com/resource/mike-perkowitz http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
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http://data.semanticuniverse.com/resource/mike-perkowitz http://xmlns.com/foaf/0.1/name Mike Perkowitz
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http://data.semanticuniverse.com/resource/mike-perkowitz http://www.w3.org/2001/vcard-rdf/3.0#title Senior Program Manager
http://data.semanticuniverse.com/resource/mike-perkowitz http://www.w3.org/2001/vcard-rdf/3.0#org Kiha Software, Inc.
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ian-eslick
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://www.w3.org/2000/01/rdf-schema#label Social Advertising: Reach and Convert Efficiently
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http://data.semanticuniverse.com/resource/semtech-2011-3771 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T13:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://purl.org/dc/elements/1.1/abstract Learn innovative ways companies are using social media channels to reach new customers at critical moments when these prospects are online and searching for answers and solutions.
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T14:10:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://swrc.ontoware.org/ontology#keywords integrated-marketing
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://purl.org/dc/elements/1.1/description In this session, Compass Labs Co-Founder and VP of Engineering Ian Eslick will discuss the value of leveraging data from social networks to target consumers based on real time values, desires and preferences, while preserving consumer privacy. Ian will also present promising new technological advances in the analysis of real-time conversational content. Innovations in these areas allow advertisers to target consumers at the exact moment they desire a product, while preserving and safeguarding user experience <P> Using real life examples, Ian will discuss the value and opportunities for brands of advertising on social networks, as well as the challenges associated with harnessing this information. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://purl.org/dc/elements/1.1/title Social Advertising: Reach and Convert Efficiently
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http://data.semanticuniverse.com/resource/semtech-2011-3771 http://swrc.ontoware.org/ontology#keywords social-media
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://purl.org/dc/elements/1.1/audience Case Study
http://data.semanticuniverse.com/resource/semtech-2011-3771 http://swrc.ontoware.org/ontology#keywords mobile
http://data.semanticuniverse.com/resource/library-of-congress http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
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http://data.semanticuniverse.com/resource/semtech-2011-3952 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/keith-griffin
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http://data.semanticuniverse.com/resource/semtech-2011-3952 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://swrc.ontoware.org/ontology#keywords social-network
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http://data.semanticuniverse.com/resource/semtech-2011-3952 http://swrc.ontoware.org/ontology#keywords cisco
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http://data.semanticuniverse.com/resource/semtech-2011-3952 http://purl.org/dc/elements/1.1/description Starting from an enterprise social semantic network consisting of people, communities and information, SPARQL queries were executed against a RDF store contained in an Oracle Spatial 11g database. These queries ranged from simple user queries to complex social networking queries consisting of facets and pivots on a social graph. Various query types and associated system performance bottlenecks will be described during the session. This will be followed by performance tuning solutions with input from Zhe Wu from Oracle. This session will benefit software engineers and researchers that are planning enterprise social software deployments using social semantic graphs by presenting real world challenges and associated solutions. The following topics will be covered by the presenters. <ul><li>Description of the People - Community - Information social semantic graph <li>Description of SPARQL queries executed and results obtained <li>Performance tuning techniques in software and hardware <li>Discussion of results obtained <li>Future work and optimizations</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://purl.org/dc/elements/1.1/title Tuning a RDF Store for an Enterprise Social Network
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://swrc.ontoware.org/ontology#keywords oracle
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://purl.org/dc/elements/1.1/abstract During 2010 Cisco carried out tests with support from Oracle on enterprise social network queries as part of a proof of concept using Oracle Spatial 11g. This session presents results from those tests.
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://swrc.ontoware.org/ontology#keywords social-graph
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T14:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-3952 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/zhe-wu
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-enterprise-applications
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://swrc.ontoware.org/ontology#keywords performance
http://data.semanticuniverse.com/resource/semtech-2011-3952 http://www.w3.org/2000/01/rdf-schema#label Tuning a RDF Store for an Enterprise Social Network
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T17:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/chancellor-thomas-pascale
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://swrc.ontoware.org/ontology#keywords integration-cyber-experimentation-design-capture-reuse
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http://data.semanticuniverse.com/resource/semtech-2011-4084 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-case-studies-use-cases
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://www.w3.org/2000/01/rdf-schema#label Using Semantic Technologies for Design Reuse in Network Experimentation
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/dc/elements/1.1/abstract This presentation describes the use of a variety of semantic technologies including Jena, semantic wikis, and semantic graph visualization in creating an environment for design reuse in network security experiments.
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/dc/elements/1.1/description As part of a large effort in developing an environment for network security experimentation, a small group of developers at JHU APL have been tasked with creation of a knowledge management system. The purpose of the system is to allow for design reuse of a variety of network components of varying levels of specificity. A central repository will process design, component, measurement, and topological documentation in the form of XML into RDF/XML using XSLT. Along with use of XSLT, a wiki using semantic wiki technologies will be used as a platform for gathering experiment and facility lessons learned. Experimenter will explore the semantic graph that is housed in the knowledge base as they start and refine their design, taking useful components from prior designs and including them in the topology and measurement of experiment. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/dc/elements/1.1/title Using Semantic Technologies for Design Reuse in Network Experimentation
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4084 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://purl.org/dc/elements/1.1/abstract See examples of how to leverage frameworks like Lucene and SIREn to index and query RDF data with extremely fast search results
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://purl.org/dc/elements/1.1/title Improving Performance of Semantic Web Applications with Lucene, SIREn and RDF
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2011-3867 http://www.w3.org/2000/01/rdf-schema#label Improving Performance of Semantic Web Applications with Lucene, SIREn and RDF
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-09T00:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3867 http://purl.org/dc/elements/1.1/description Building web applications that allow users to search massive RDF datasets present new challenges to developers. In particular, as the number of triples grows, some SPARQL queries will not return quickly enough to satisfy the speed and scalability requirements of end users. By indexing RDF data in advance, powerful search frameworks like Lucene and SIREn can overcome this problem and provide near real-time responses to user queries. <P> The team at Entagen has been leveraging these indexing and search frameworks along with a traditional triplestore, SPARQL queries, multi-core processing and caching to deliver an interactive and responsive user experience for TripleMap. TripleMap (triplemap.com) is a web-based application that can be used for the navigation, visualization and analysis of the Linking Open Drug Data resources and other RDF datasets. <P> This presentation will provide examples of how to index and query RDF entities with Lucene and SIREn and demonstrate how these frameworks can complement existing methods of querying RDF data. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3867 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mike-hugo
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http://data.semanticuniverse.com/resource/semtech-2011-web-authoring-and-publishing http://www.w3.org/2000/01/rdf-schema#label Web Authoring and Publishing
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords web-developers
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/dc/elements/1.1/description Google, Facebook and others are asking websites to put simple annotations (e.g. RDFa) on web pages. Turns out there are other unexpected reasons why this can bring value and customers. <P> We will being by showing in practice what these annotations are, what direct benefits they bring and certain advanced tools to explore and validate them. <P> We will then show how said annotations further enable the "import of value" from the rest of the "Web of Data" to gain recommendations, information boxes, and custom faceted browsers based on relevant data your website/database never had directly. <P> We will also show how, as you do this, your site becomes itself a datasource which can be used in other people's mashups and as such be rewarded with visitors, recognition and possibly direct revenues. <P> * Lightweight web markup: basics, common uses, direct benefits * Getting recommendations, information boxes and more leveraging the rest of the Web of Data (and your simple web page markup) * Providing widgets with the content of your site to others * Your pages as a dataset for others to integrate: get visitors and value * Case Studies: ecommerce and multimedia content annotations * hands on example, creating your own company semantic embeddable widget <P>
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://www.w3.org/2000/01/rdf-schema#label Lightweight Web Markup: Services and Values Beyond Expected
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/dc/elements/1.1/title Lightweight Web Markup: Services and Values Beyond Expected
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords sindice
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords mashup
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http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords rdfa
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/giovanni-tummarello
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords rich-snippets
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/dc/elements/1.1/abstract Google, Facebook and others are asking websites to put simple annotations (e.g. RDFa) on web pages. Turns out there are other unexpected reasons why this can bring value and customers.
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords web-of-data
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords webmasters
http://data.semanticuniverse.com/resource/semtech-2011-4024 http://swrc.ontoware.org/ontology#keywords custom-search
http://data.semanticuniverse.com/resource/semtech-2011-3807 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T14:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3807 http://purl.org/dc/elements/1.1/description Much of the value proposition of semantic technology centers on the idea that data is more accessible, interlinked and open for re-use, and that as a result, gains can be made through increased information leverage, better informed decision making, lower operational latency etc. However, with the rapid emergence of large public or semi-public data collections, and the increased prevalence of semantic machinery by which this data can be collected, integrated and analysed, there is also the risk that the very same semantic data and technologies can be applied for other less desirable purposes. This presentation will consider a number of case studies where availability of enterprise and personal information in the public or semi-public web, combined with freely available semantic analytics tools can be used to determine ?interesting? facts about organisations and individuals, at a level of confidence that will be alarming. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3807 http://www.w3.org/2000/01/rdf-schema#label When Good Semantic Data and Tools Turn Bad
http://data.semanticuniverse.com/resource/semtech-2011-3807 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-personal-data-and-identity
http://data.semanticuniverse.com/resource/semtech-2011-3807 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-3807 http://purl.org/dc/elements/1.1/audience Business
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http://data.semanticuniverse.com/resource/semtech-2011-3807 http://purl.org/dc/elements/1.1/title When Good Semantic Data and Tools Turn Bad
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http://data.semanticuniverse.com/resource/semtech-2011-3807 http://purl.org/dc/elements/1.1/abstract The objective of this presentation is to raise awareness of the potential for misuse of openly available semantically linked data and tools.
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http://data.semanticuniverse.com/resource/semtech-2011-3783 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2011-3783 http://www.w3.org/2000/01/rdf-schema#label Integrating Software and Knowledge Engineering at Sallie Mae: From Structured and Unstructured Data to Semantic Information Architecture
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://swrc.ontoware.org/ontology#keywords collaboration
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://purl.org/dc/elements/1.1/abstract The presentation describes post SOA methods and focuses on the changes related to Enterprise Information, from semantic enrichments and business-friendly knowledge acquisition processes to integration of ontology of ontologies
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://purl.org/dc/elements/1.1/title Integrating Software and Knowledge Engineering at Sallie Mae: From Structured and Unstructured Data to Semantic Information Architecture
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-information-architecture
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://purl.org/dc/elements/1.1/description This presentation will discuss tools and methods that have been developed by Sallie Mae to assist Business Architects in creating shared artifacts for their integration environment. Sallie Mae is involved in a major initiative to semantically enhance their integration capability. As we performed the analysis we recognized that there were tools needed to help with the sheer volume of distinctions that are made in the many different systems that need to be integrated. <P> These tools draw together metadata from artifacts that describe the different systems and prompt Business Architects to more precisely define them and how to map the transform from one to the other. <P> The tool also considers that in a large scale environment there will be many ontologies, each focused on a different context or part of the overall architecture. The tools draw together needed concepts from multiple different ontologies as part of the analysis. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3783 http://swrc.ontoware.org/ontology#keywords standards
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http://data.semanticuniverse.com/resource/semtech-2011-3934 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kendall-grant-clark
http://data.semanticuniverse.com/resource/semtech-2011-3934 http://purl.org/dc/elements/1.1/audience Case Study
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http://data.semanticuniverse.com/resource/semtech-2011-3934 http://swrc.ontoware.org/ontology#keywords owl
http://data.semanticuniverse.com/resource/semtech-2011-3934 http://purl.org/dc/elements/1.1/abstract Spanner is a system in use at NASA that turns ordinary documents into a full-featured Linked Data application that is easily customized via JavaScript.
http://data.semanticuniverse.com/resource/semtech-2011-3934 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2011-3934 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3934 http://purl.org/dc/elements/1.1/title Spanner @ NASA: Using Enterprise Semantics to Turn Documents into Linked Data
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http://data.semanticuniverse.com/resource/semtech-2011-3934 http://swrc.ontoware.org/ontology#keywords rdf
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http://data.semanticuniverse.com/resource/semtech-2011-3934 http://purl.org/dc/elements/1.1/description Spanner is a Semantic ECM system in use at NASA that turns documents into a full-featured Linked Data application that is easily customized via JavaScript. <P> Spanner extracts information from any kind of document and converts that information into RDF and OWL. Spanner uses machine learning to discover connections between documents, entities, and between entities and documents; it will also learn categories or tags for documents if some of the documents are already tagged. Finally, it will extract keywords and a single key sentence from every document. <P> This is Linked Data Bootstrapping and it's fully automated. <P> Spanner answers key objections to Semantic Technology: <P> 1. We Just Want to Publish Linked Data: The core of Spanner is a Linked Data publishing solution. <P> 2. Making an Ontology is Too Hard: You don't need an ontology or schema before Spanner performs data bootstrapping. But if you have one, even a partial one, the data bootstrapping process works better. <P> 3. My Org isn't Full of SemWeb Developers: Spanner can be customized by writing JavaScript code against the RESTful Spanner APIs, which include: <ul><li>semantic search <li>faceted browsing <li>auto-generated edit forms <li>SPARQL query <li>OWL reasoning <li>RDF & OWL-aware machine learning <li>integrity constraint validation <li>role-based access controls <li>asynchronous job service</ul> <P> 4. What About Data Quality? Any system that helps you pivot from document-based information management to semi-structured data management is will require data curation. Using some clever machine learning tricks, Spanner offers users a flexible means to improve data quality explicitly, while also allowing automated data quality improvements, too. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4066 http://purl.org/dc/elements/1.1/abstract This panel will focus on how and where 1-year-old W3C RIF is being used for semantic web, and what are its prospects and directions, from viewpoints of vendors and users.
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http://data.semanticuniverse.com/resource/semtech-2011-4066 http://purl.org/dc/elements/1.1/description Rules are perhaps the most important frontier today for structured knowledge management on the web and in enterprise clouds. As W3C Rule Interchange Format reaches its first birthday, this panel will focus on how and where RIF is being used for semantic web rules interchange, and what are its prospects and directions. Panelists from several leading organizations will discuss and debate the topic from the viewpoint of vendors, end users, and standards makers. We will explore the current challenges for adoption and integration with related technologies and standards efforts in areas such as privacy, security, healthcare, finance, and government. We will also touch upon roadmapping of extensions to the RIF standard itself, and needs for outreach & education. Background: At SemTech last year (2010), RIF was announced by W3C as a finalized standard (i.e., ?Recommendation?). Several presentations explained the standard itself at the Rules Track then. <P>
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http://data.semanticuniverse.com/resource/scott-henninger http://www.w3.org/2001/vcard-rdf/3.0#org TopQuadrant, Inc.
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http://data.semanticuniverse.com/resource/semtech-2011-4036 http://swrc.ontoware.org/ontology#keywords journalism
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http://data.semanticuniverse.com/resource/semtech-2011-4036 http://purl.org/dc/elements/1.1/description As Tim Berners-Lee pointed out this past year, ?Journalism is going to be about poring over data and equipping yourself with the tools to analyze it and picking out what's interesting. And keeping it in perspective, helping people out by really seeing where it all fits together, and what's going on in the country.? This fundamental shift is changing the landscape of how news is discovered and even created. Data journalism manifests not only when journalists themselves become more proficient in RDF and Python, but when the tools of the trade are custom-made for journalistic use, allowing writers to discover those stories lurking within the data itself. During this panel we'll discuss the most innovative, affordable and user-friendly text analysis tools on the market and the ways journalism can and will evolve as data drives the news. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4036 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-4036 http://www.w3.org/2000/01/rdf-schema#label Analyzing All That?s Fit to Print ? Text Analysis and Journalism
http://data.semanticuniverse.com/resource/semtech-2011-4036 http://purl.org/dc/elements/1.1/abstract Text analysis has risen in importance in the world of data-informed news. Join us to discuss data journalism tools and methods for piecing together information to tell compelling, new stories.
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http://data.semanticuniverse.com/resource/semtech-2011-3795 http://purl.org/dc/elements/1.1/abstract Come find out how the W3C standard Simple Knowledge Organization System can help you ease into semantic technology and better manage vocabularies at both small and large scales.
http://data.semanticuniverse.com/resource/semtech-2011-3795 http://swrc.ontoware.org/ontology#keywords thesaurus
http://data.semanticuniverse.com/resource/semtech-2011-3795 http://purl.org/dc/elements/1.1/title Vocabulary Management, SKOS, and the Semantic Web
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http://data.semanticuniverse.com/resource/semtech-2011-3795 http://purl.org/dc/elements/1.1/description You manage a taxonomy, thesaurus, or some other kind of controlled vocabulary using a proprietary tool or perhaps even by emailing spreadsheets to each other. You've heard about the Simple Knowledge Organization System standard, but what does it have to do with your vocabularies, and what does it have to do with the semantic web? If SKOS is an ontology for managing taxonomies and thesauri, what's the difference between an ontology, a thesaurus, and a taxonomy, and for that matter, a controlled vocabulary? Is there any connection between SPARQL and SKOS, and if so, how can SPARQL help to manage vocabularies? What organizations are using SKOS now, and for what? How do you get started with SKOS? <P> Come learn how this W3C standard can help you ease into semantic technology and better manage your vocabularies at both small and large scales. <P> We'll also look at: <P> - SKOS's relationship to previous taxonomy standards <P> - How to extend SKOS to account for your own customized metadata <P> - Management of terms versus management of concepts, and how the latter makes multilingual support easier <P> - What kind of SKOS tool support is available <P> - How SKOS enables the networking of departmental vocabularies <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3850 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T11:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords organization-structure
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords collaboration-applications
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http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/vanessa-clark
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords social-graph
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/description Cisco?s business model has shifted from ?command and control? to one that?s driven by boards and councils that employ collaboration and teamwork to drive key business initiatives. This new business model enables agility in decision making and positions Cisco to respond rapidly to market transitions and opportunities. To fuel this shift, semantic technology is being used to dynamically manage Cisco?s collaborative, networked business model. Decison making and resource allocation is accelerated by providing a centralized source of interlinked data unearthing and capturing the dynamic and complex relationships within the enterprise. How semantic technology effectively breaks silos buried within organization hierarchies and enables the new business model Benefits of a relationship-rich data model The business value of interacting with and visualizing the social graph How semantically enabled recommendations surface important decision parameters Creating and standardizing an Enterprise social graph <P>
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords semantics-technology-business-value
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords enterprise-applications
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/vladimir-mikhailov
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T10:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords enterprise-data-silos
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/gerard-s-regnier
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/title Using Semantic Technology to Revolutionize Traditional Business Models
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://purl.org/dc/elements/1.1/abstract Learn how Cisco is using semantically enabled collaboration technology to assist in its evolution from a ?Command and Control? driven organization to a ?Dynamic Networked? driven organization
http://data.semanticuniverse.com/resource/semtech-2011-3850 http://swrc.ontoware.org/ontology#keywords enterprise-semantic-architecture
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T16:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mary-catherine-parmelee
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/dc/elements/1.1/title Agile Development Meets Ontology as a Service: A Cyber-Security Example
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords cyber-security
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords service-oriented-architecture-(soa)
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-networked-knowledge
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords owl
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/dc/elements/1.1/abstract We demonstrate the value of this fast and effective methodology for large-scale OWL ontology implementation and deployment by applying it to a real world cyber-security implementation.
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords applied-ontology
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords service-oriented-computing-(soc)
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://www.w3.org/2000/01/rdf-schema#label Agile Development Meets Ontology as a Service: A Cyber-Security Example
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords semantic-information-architecture
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords agile-development-process
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://purl.org/dc/elements/1.1/description The Web Ontology Language (OWL) is a powerful mechanism for making the semantics of digital information self-describing and executable. As OWL transitions from academia and research to widespread commercial application, there is a need for systematic methods that provide a clear path for large-scale implementation and deployment while quickly demonstrating added value to the customer and the end user. This presentation introduces a methodology for the incremental implementation and deployment of OWL ontologies in large-scale information domains. We apply service oriented computing and Agile Development process techniques to quickly deploy new capability while incrementally building an inventory of loosely-coupled reusable ontologies. As the ontology inventory grows, it gradually reduces the development cost of future applications while improving cross-application semantic interoperability. We demonstrate the methodology?s value by stepping through a real world cyber-security example from concept to application deployment; including a live demonstration of the resulting semantic application. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4006 http://swrc.ontoware.org/ontology#keywords enterprise-semantic-application-development
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-linked-data
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/dc/elements/1.1/abstract We will present the informatics approaches utilized in building the NIF, specifically the semantic tools that have been employed and will also highlight the NeuroLex semantic wiki.
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jeffrey-s-grethe
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://swrc.ontoware.org/ontology#keywords semantic-wiki
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/dc/elements/1.1/title Case Study: The Neuroscience Information Framework - A Unified Semantic Framework for Discovery and Integration of Biomedical Data and Resources
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://swrc.ontoware.org/ontology#keywords biology
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://www.w3.org/2000/01/rdf-schema#label Case Study: The Neuroscience Information Framework - A Unified Semantic Framework for Discovery and Integration of Biomedical Data and Resources
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/dc/elements/1.1/description Informatics and new semantic technologies are becoming increasingly important to biomedical researchers. An initiative of the NIH Blueprint for Neuroscience Research, the Neuroscience Information Framework (NIF; http://neuinfo.org) enables discovery and access to public research data, contained in databases and structured web resources (e.g. queryable web services) that are sometimes referred to as the deep or hidden web, and resources through an open source semantic inventory of biomedical resources that are annotated and integrated with a unified system of biomedical terminology. <P> The NIF Data Federation (with more than 60 independent databases) allows for direct search, discovery and integration of data content. Search and annotation of resources and resource content is enhanced through the utilization of a comprehensive ontology (NIFSTD; http://purl.org/nif/ontology/nif.owl), built as a set of modular ontologies. To enable broad community contribution to NIFSTD, NeuroLex (http://neurolex.org) is available as a wiki that provides an easy entry point for the community. NIF?s environment draws upon NIFSTD and the NIF data federation to provide the basis for linking results into the large ecosystem of linked data. <P> In this case study, we will introduce the problem and describe our novel approach. The presentation will: <ul><li>Review the basic concepts and approach that underpin the design of NIF <li>Introduce the architecture of the NIF and how this could be generalised for other uses <li>Illustrate how semantic wikis can be utilized in the biomedical community <li>Describe NIF?s ontology and how it is used to enhance the environment for the biomedical researcher <li>Present NIF?s approach for growing and inter-linking data in the linked-data cloud</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T17:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3976 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/bill-guinn http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/bill-guinn http://www.w3.org/2000/01/rdf-schema#label Bill Guinn
http://data.semanticuniverse.com/resource/bill-guinn http://xmlns.com/foaf/0.1/name Bill Guinn
http://data.semanticuniverse.com/resource/bill-guinn http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/2975.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/bill-guinn http://www.w3.org/2001/vcard-rdf/3.0#title CTO Product Enablers
http://data.semanticuniverse.com/resource/bill-guinn http://www.w3.org/2001/vcard-rdf/3.0#org Amdocs Product Business Unit
http://data.semanticuniverse.com/resource/dominic-difranzo http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/dominic-difranzo http://www.w3.org/2000/01/rdf-schema#label Dominic DiFranzo
http://data.semanticuniverse.com/resource/dominic-difranzo http://xmlns.com/foaf/0.1/name Dominic DiFranzo
http://data.semanticuniverse.com/resource/dominic-difranzo http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3373.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/dominic-difranzo http://www.w3.org/2001/vcard-rdf/3.0#title Graduate Research Assistant
http://data.semanticuniverse.com/resource/dominic-difranzo http://www.w3.org/2001/vcard-rdf/3.0#org Tetherless World Constellation (RPI)
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://purl.org/dc/elements/1.1/description How can brands turn raw social media comment data from Twitter, Facebook, Blogs and Forums into actionable business inights? Core Analytics demonstrates the process of building a social media datamart using raw comment data from healthcare insurers and grocery brands, to show how customer brand activation and loyalty metrics are developed and map to consumer strategies as well as measurement of these efforts. This is an advanced version of the 10 minute talk given at SemTech2010, a 25 minute overview of the BrandMeter (TM), developed by Core Analytics, that shows a step-wise approach to driving customer activation and loyalty through the semantic manipulation of raw comment data. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T11:40:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords social-media-analytics
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords social-media-activation
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T11:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://purl.org/dc/elements/1.1/abstract Detail how raw comment data is transformed through text mining to populate a social media brand datamart, providing the basis for customer micro-segmentation and predictive modeling through each social media channel. This has been accepted for SXSW Interactive in March.
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords customer-loyalty
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-social-networks-and-collaboration
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://purl.org/dc/elements/1.1/title Social Media: Driving Customer Brand Activation and Loyalty
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kimberly-chulis
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://www.w3.org/2000/01/rdf-schema#label Social Media: Driving Customer Brand Activation and Loyalty
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords brandmeter
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords text-mining-social-media
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords core-analytics
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http://data.semanticuniverse.com/resource/semtech-2011-3765 http://swrc.ontoware.org/ontology#keywords social-media-loyalty
http://data.semanticuniverse.com/resource/mills-davis http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/mills-davis http://www.w3.org/2000/01/rdf-schema#label Mills Davis
http://data.semanticuniverse.com/resource/mills-davis http://xmlns.com/foaf/0.1/name Mills Davis
http://data.semanticuniverse.com/resource/mills-davis http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3339.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/mills-davis http://www.w3.org/2001/vcard-rdf/3.0#title Founder and Managing Director
http://data.semanticuniverse.com/resource/mills-davis http://www.w3.org/2001/vcard-rdf/3.0#org Project10X
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/title Reasoning with SPARQL
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/scott-henninger
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/description The Semantic Web stack includes a number of inferencing specifications - OWL, RDFS and more recently RIF. But use of the query language SPARQL for inferencing is widespread. SPARQL 1.1 includes features that are common in mature rule languages, like arithmetic functions, aggregates and pattern matching. It was designed from the very start to integrate well with RDF, making it easy to use in a semantic web setting. <P> This half-day tutorial will focus on SPARQL as a core technology for expressing rules and inferences using the W3C standard SPARQL 1.1 Query Language. Various techniques for using SPARQL to process, modify, insert and remove data will be discussed. Approaches for representing and applying sets of SPARQL queries for rule-based and OWL reasoning will be detailed. <P> This tutorial assumes a basic familiarity with SPARQL. <ul><li>SPARQL-based inference with CONSTRUCT and SPARQL 1.1 Update <li>Data transformation with SPARQL <li>SPARQL as a constraint Language <li>Implementing other inferencing systems (e.g., OWL 2 RL) using SPARQL <li>Function calls and computations <li>SPARQL optimizations <li>Embedding SPARQL queries into Ontologies</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords rules
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://www.w3.org/2000/01/rdf-schema#label Reasoning with SPARQL
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#TutorialEvent
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-reasoning-and-inference
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http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dean-allemang
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords inference
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords reasoning
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/abstract The query language SPARQL includes a number of features that make it attractive as a rules language. This tutorial covers the basics of how to use SPARQL for inferencing.
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
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http://data.semanticuniverse.com/resource/semtech-2011-3946 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3946 http://swrc.ontoware.org/ontology#keywords owl-2-rl
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://purl.org/dc/elements/1.1/description By creating semantic objects from the world around us, techniques allow these objects to interact in realtime and on a continuous basis. Semantic objects can represent people, points of interest, events, products, services - in fact anything that can be represented digitally. <P> Such systems use semantic technologies to compare and match these objects in real-time for relevant and timely results. They also use artificial intelligence to expand and grow these objects as they interact and learn about the world around them. Applications include business networking, education, social and media entertainment. <ul> <li>Discover how these systems work and how the realtime web and the semantic web work together <li>Understand how matching can provide a better user experience through trust, anonymity and relevance <li>Learn how semantic technologies can be easily integrated into your business <li>Find out how to enhance your business matching capabilities with linked data <li>See how semantic learning can gain better insights into your customer's desires <li>Get a taste of the future with agent based computing in business</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-case-studies-use-cases
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://swrc.ontoware.org/ontology#keywords business
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/marcus-trevisani
http://data.semanticuniverse.com/resource/semtech-2011-4078 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-4078 http://purl.org/dc/elements/1.1/title Real World, Real Time Semantic Matching - Applications in Business
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http://data.semanticuniverse.com/resource/semtech-2011-4078 http://purl.org/dc/elements/1.1/abstract Provide 3 case studies of businesses that are using realtime semantic matchmaking as the under pinning of their service offering. Outline the drivers and benefits of using semantic in this way and how business in general can benefit.
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http://data.semanticuniverse.com/resource/semtech-2011-4133 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T10:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4133 http://purl.org/dc/elements/1.1/audience Business
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http://data.semanticuniverse.com/resource/semtech-2011-4133 http://purl.org/dc/elements/1.1/title The Next Generation Consumer Business ? Semantically Enabled for Real-Time Intelligence
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http://data.semanticuniverse.com/resource/semtech-2011-4133 http://purl.org/dc/elements/1.1/description Optimizing a customer oriented businesses requires real time contextual customer knowledge across all business channels. Plus it should factor in relevant social and competitive forces. And this knowledge must be used to guide the outcome of each business transaction. In complex, customer-centric businesses such as Telecommunications, Health Care, and Financial Services, the business needs to understand how every action affects the profitability of the business. Systems must holistically know what?s going on in real time, determine the meaning of these activities, decide what to do, and then take the optimal action to maximize profit and customer satisfaction. The result is complete awareness of the business theater. <P> Such systems are proactive, predictive, personalized, and optimized for each individual customer. And they can scale to billions of activities a day. Amdocs has accomplished this objective with real-time semantic technology, capable of directly driving the largest businesses in the world. The results can be amazing, including massive cost reductions improvements in customer care, better retention, up selling, and resource utilization. Bottom line profitability is improved, top line expansion is realized. Perhaps more important, the agility to accommodate business change and to differentiate is unprecedented. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4133 http://purl.org/dc/elements/1.1/abstract .
http://data.semanticuniverse.com/resource/semtech-2011-4133 http://www.w3.org/2000/01/rdf-schema#label The Next Generation Consumer Business ? Semantically Enabled for Real-Time Intelligence
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http://data.semanticuniverse.com/resource/semtech-2011-4133 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/bill-guinn
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http://data.semanticuniverse.com/resource/rensselaer-polytechnic-institute-and-mcguinness-associates-(rpi) http://xmlns.com/foaf/0.1/name Rensselaer Polytechnic Institute and McGuinness Associates (RPI)
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http://data.semanticuniverse.com/resource/semtech-2011-3892 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://purl.org/dc/elements/1.1/description There's now an amazing amount of data available as RDF from diverse sources such as the UK and US governments, media organisations like the BBC and New York Times, and a host of others. But many developers still struggle to use this data because the formats and access methods are typically alien. Query languages like SPARQL provide a rich way to interact with RDF data but developers must take time to learn the language, the data model being accessed, and the possibilities of each new dataset. In contrast the majority of web developers are much more comfortable working with simple RESTful APIs that allow them to quickly explore, navigate and use new data sources. <P> This talk will survey a number of different approaches for creating custom RESTful APIs over any SPARQL endpoint. These approaches allow the creation of data access options that are tailored for specific application use cases and provide a way for developers to engage with the growing web of data using existing skills and tools. By making it possible to create and share API configurations it also becomes possible to create multiple, community curated and tailored APIs over the web of data. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/leigh-dodds
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-web-services
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://swrc.ontoware.org/ontology#keywords web-service
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://purl.org/dc/elements/1.1/title Creating APIs over RDF Data Sources
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://purl.org/dc/elements/1.1/abstract Review techniques for creating custom RESTful APIs for accessing RDF data using existing SPARQL endpoints.
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3892 http://swrc.ontoware.org/ontology#keywords linked-data
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http://data.semanticuniverse.com/resource/semtech-2011-3892 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2011-4018 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T16:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/christine-jm-connors
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/abstract We expect the audience to leave with a knowledge of the tools and process to begin deploying their image sets into Pivot using applicable widely available ontologies. We also briefly discuss the implications for incorporating visual search capabilities into a larger enterprise search framework.
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/title Simple Visual Search Semantics
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-future-of-media
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/description With the 2010 introduction of Microsoft's freely available Pivot, and popularized by the Gary Flake TED video, visual search has become an implementation possibility for everyone. Pivot is a fast, intuitive faceted search capability for images, and the Pivot defaults are well-designed so that image metadata can be easily ingested by the tools and made available to end users. By itself, Pivot is not semantic, but the W3C's 2007 Image Annotation on the Semantic Web laid the groundwork for incorporating image semantics. This presentation demonstrates how the authors have incorporated semantics into Pivot implementations to quickly increase their utility, making visual search semantics accessible to a very wide audience with a minimum background in semantics or image annotation. <P> In this presentation, the authors discuss their work with multiple image sets, ranging from hundreds to hundreds of thousands of images. While Pivot design considerations are discussed, and we include Pivot-specific development tips, the focus is on the semantic design issues of application context, ontology selection, and mapping selected ontologies into Pivot. The mapping methods of several of our implementations will be discussed in detail so the audience can determine the applicability of each approach to their own image sets. We expect the audience to leave with a knowledge of the tools and process to begin deploying their image sets into Pivot using applicable widely available ontologies. We also briefly discuss the implications for incorporating visual search capabilities into a larger enterprise search framework. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://www.w3.org/2000/01/rdf-schema#label Simple Visual Search Semantics
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http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kevin-j-lynch
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-search
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http://data.semanticuniverse.com/resource/semtech-2011-4018 http://swrc.ontoware.org/ontology#keywords image-processing
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http://data.semanticuniverse.com/resource/semtech-2011-4018 http://swrc.ontoware.org/ontology#keywords semantic-search
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://swrc.ontoware.org/ontology#keywords mobile-applications
http://data.semanticuniverse.com/resource/semtech-2011-4018 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/joe-sortelli
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://www.w3.org/2000/01/rdf-schema#label Text Analytics and Auto-Categorization in Semantic Web Applications
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://swrc.ontoware.org/ontology#keywords text-analytics
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http://data.semanticuniverse.com/resource/semtech-2011-3988 http://purl.org/dc/elements/1.1/abstract This workshop examines how the use of text analytics can significantly enhance Semantic Web applications through identification, extraction, and auto-categorization of important information contained in textual content
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://swrc.ontoware.org/ontology#keywords unstructured-information
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/james-wessely
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://purl.org/dc/elements/1.1/description Use of text analytics for concept and topic identification, entity extraction, and auto-categorization have been strongly growing in popularity, and is providing high-value in enterprise-scale applications. But most of these applications are not yet based upon Semantic Web technologies. This workshop explains how to combine the power of text analytics and Semantic Web technologies. The workshop explains and demonstrates differences between text analytics tools like auto-categorization and entity extraction, and Semantic Web technologies. Take your applications to the next level by capturing the concepts, relationships, people, places, events, and other important things that are scattered inside and outside of your enterprise and buried in your content. <P> Attendees will gain an understanding of: <ul><li>Different applications of text analytics <li>What text analytics can and cannot do well <li>How entity extraction and text analysis (statistical, vector-based, semantics, etc.) work <li>Different types of text analysis algorithms and their strengths and weaknesses <li>When to use the different types of text analytics <li>How much metadata you can reasonably expect to extract from textual content <li>How much text analysis can (and cannot) be automated <li>Text mining vs. extraction of terms, phrases, and entities <li>How text analytics can help build vocabularies, taxonomies, and ontologies <li>What auto-categorization is, how it works, and when it works <li>How to use text analytics and auto-categorization in your Semantic Web application <li>auto-categorization and Semantic Web standards</ul> <P> If you want to understand the difference between the Semantic Web and semantic analysis, and how to use the power of text analytics in your Semantic Web applications, you don't want to miss this workshop. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#TutorialEvent
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://swrc.ontoware.org/ontology#keywords auto-categorization
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://purl.org/dc/elements/1.1/title Text Analytics and Auto-Categorization in Semantic Web Applications
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://swrc.ontoware.org/ontology#keywords application-design
http://data.semanticuniverse.com/resource/semtech-2011-3988 http://swrc.ontoware.org/ontology#keywords entity-extraction
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http://data.semanticuniverse.com/resource/semtech-2011-3988 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2011-3958 http://www.w3.org/2000/01/rdf-schema#label Adopting Semantics in the Enterprise
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http://data.semanticuniverse.com/resource/semtech-2011-3958 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/brian-sletten
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http://data.semanticuniverse.com/resource/semtech-2011-3958 http://purl.org/dc/elements/1.1/title Adopting Semantics in the Enterprise
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http://data.semanticuniverse.com/resource/semtech-2011-3958 http://purl.org/dc/elements/1.1/abstract A short collection of strategies for advocating and introducing Semantic Web technologies within an organization.
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http://data.semanticuniverse.com/resource/semtech-2011-3958 http://purl.org/dc/elements/1.1/description While there is a lot of interest in using Semantic Technologies in the Enterprise, there is very little guidance on how to go about doing so. It sounds like a scary Big Bang change, but the truth is, there are incremental steps that can be adopted gradually. <P> This talk will be an introduction of how you can begin to advocate and apply Semantic Web technologies iteratively both internally and on the public Web. <P> Topics will include: <ul><li>How to explain Semantic Web technologies to various stakeholders <li>Mapping these technologies into existing industry trends <li>Adopting a Resource-Oriented view of the world <li>Data Integration strategies <li>Using RDFa <li>Building and extending metadata repositories that unify your documents, data and services</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3832 http://purl.org/dc/elements/1.1/abstract Explains the Banking Industry Architecture Network's semantics-based approach to defining service oriented-architecture standards for the banking industry.
http://data.semanticuniverse.com/resource/semtech-2011-3832 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3832 http://purl.org/dc/elements/1.1/description The Banking Industry Architecture Network (BIAN) is developing a common architecture to facilitate interoperability among heterogeneous software components within a bank?s application landscape. BIAN?s approach to standardization is somewhat unusual in that it focuses on semantic interoperability and not on defining technical wire-level interoperability formats. This presentation explains the motivation for this approach, and describes the fundamentals of the architecture. Topics covered include: <ul><li>How BIAN describes service-oriented contracts in a manner that focuses on semantics <li>How BIAN identifies common service components <li>How BIAN?s standardized semantic service specifications can provide value to banks and banking software vendors despite the fact that BIAN does not produce lower-level technical interoperability standards <li>The effort BIAN is making to build a business vocabulary, and to apply the business vocabulary to the service definitions in a disciplined manner. <li>How BIAN?s approach aligns with other standards efforts in the financial services, manufacturing, retail, and consumer products industries. <li>An overview of the BIAN metamodel</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3832 http://purl.org/dc/elements/1.1/title Overview of BIAN's Semantics-Focused Architecture
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http://data.semanticuniverse.com/resource/semtech-2011-4061 http://www.w3.org/2000/01/rdf-schema#label Semantic Web UI Design Workshop: Show, Tell, Explore
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http://data.semanticuniverse.com/resource/semtech-2011-4061 http://purl.org/dc/elements/1.1/abstract An active session, this tutorial asks people to bring example sites and projects to share. Presenter and participants brainstorm design approaches, offer best practice advice, and everyone sees new things!
http://data.semanticuniverse.com/resource/semtech-2011-4061 http://swrc.ontoware.org/ontology#keywords user-experience
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http://data.semanticuniverse.com/resource/semtech-2011-4061 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2011-4061 http://purl.org/dc/elements/1.1/description The use of semantic technologies has grown significantly over the last few years, and with that growth we have also seen many questions about designing interactions and visualizations. Some of those questions can be answered by adopting interesting interaction styles from existing sites. Other design questions require considering the unique behaviors of semantically-enabled data, relationships and interactions. This session offers both. <P> You are encouraged to provide example sites/applications in advance, or bring them on the day. The format will be a workshop, where challenges are raised and ideas/examples are shared with the group. The presenter will offer approaches that can be used to review and understand user interface challenges, and the participants will join in offering solutions and examples that can help improve the user experience. Participants will: <ul><li>See what others are doing and what they think is interesting in the semantic web space today <li>Gain an understanding of techniques to tackle design questions for their own projects <li>Apply a framework for how to review site designs, looking at user goal accomplishment and the overall experience as a way of assessing what works <li>Possibly walk away with new insights that are directly applied to their current applications and projects</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4061 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-web-services
http://data.semanticuniverse.com/resource/semtech-2011-4061 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/duane-degler
http://data.semanticuniverse.com/resource/semtech-2011-4061 http://swrc.ontoware.org/ontology#keywords visualization
http://data.semanticuniverse.com/resource/semtech-2011-4061 http://purl.org/dc/elements/1.1/title Semantic Web UI Design Workshop: Show, Tell, Explore
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http://data.semanticuniverse.com/resource/semtech-2011-4031 http://purl.org/dc/elements/1.1/description Filoli is a historic site of the National Trust for Historic Preservation and one of the finest remaining country estates of the early 20th century. While the property itself is best known for its 36,000 square foot Georgian country house, a small army of dedicated gardeners and volunteer docents maintain and educate the public about its spectacular, 16-acre English Renaissance garden. For the last several years, in addition to his ?day job? at SRI International, Dr. Reginald Ford has been using OWL to construct horticultural ontologies and create knowledge bases describing Filoli gardens. Dr. Ford enlisted several fellow docents in an experiment that hopefully will prove useful for tour guides and serve as a prototype for horticultural ontology standards. <P> Garden docents are often asked questions about specific plants in the garden ? spectacular daffodils in the spring draw huge crowds, and many guests want to know how they can get similar effects at home. Filoli is an American Daffodil Society (ADS) Display Garden and grows a wide variety of daffodil cultivars with the purpose of educating visitors about daffodils and how they can be used effectively in the landscape. The American Camellia Society has established Filoli as one of the stops on the American Camellia Trail due to the number and variety (over 80 species) of plants in the garden. Capturing the detail in a knowledge base and making it accessible via queries and tailored extracts (e.g., details about plants blooming this month) can help docents answer questions quickly. Getting assistance to build and maintain the knowledge base is daunting, however, given that many of the volunteers are knowledgeable about horticulture but have had no exposure to semantic technologies. In this talk, we will describe: <ul><li>Challenges of enlisting non-geeks to formalize informal information <li>Use of UML diagrams to help garden information docents understand and evolve the ontologies and knowledge bases <li>Overview of the ontologies and reasoning, including SWRL-based query, illustrating the flexibility and power of the semantic technologies approach (demo) <li>Temporal reasoning to support seasonal question answering: what plants in the Filoli gardens flower in mid-spring <li>Long term vision, such as getting horticultural societies to commit to developing common description standards and broadly available ontologies</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4031 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/elisa-kendall
http://data.semanticuniverse.com/resource/semtech-2011-4031 http://purl.org/dc/elements/1.1/abstract A case study about bringing the benefits of semantic technologies to the popular horticulture domain. Creation of a knowledge base to assist garden docents at a major historic garden. Methods (e.g., visualization) to facilitate participation by non-technologists in ontology-based standards development.
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http://data.semanticuniverse.com/resource/semtech-2011-4031 http://purl.org/dc/elements/1.1/title Case Study: Ontology Maintenance by ?Normal People? ? A Passion for A Historic Garden Provides Motivation
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http://data.semanticuniverse.com/resource/semtech-2011-3814 http://purl.org/dc/elements/1.1/abstract An overview of the 'Clinical Quality Linked Data' project at the Centers for Medicare & Medicaid Services (cms.gov) and its publication on healthdata.gov will be given in this presentation.
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http://data.semanticuniverse.com/resource/semtech-2011-3814 http://purl.org/dc/elements/1.1/title Clinical Quality Linked Data on health.data.gov
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http://data.semanticuniverse.com/resource/semtech-2011-3814 http://purl.org/dc/elements/1.1/description CMS publishes the results of public surveys that measure and compare the performance of various clinical institutions. Survey data is accumulated through established channels on regular schedules and published either quarterly or annually. <P> Clinical Quality data provides customer satisfaction insight across participating Medicare institutions from and to the public. These data include treatment and cost statistics of common health conditions, each having standardized process and outcome measures and metrics, compared against state and national averages and means. <P> The goal is to enhance the utility and reusability of this data to increase the opportunity for secondary uses and cross domain correlation through public participation and community collaboration. In light of this and federal open data transparency initiatives like Data.gov, Linked Data is becoming an increasingly important implementation approach. <P> An overview of organizational and technical milestones achieved and the outlook for realizing future Government Open Linked Data goals will be given. <ul><li>Government Open Linked Data <li>Centers for Medicare and Medicaid Services <li>health.data.gov <li>People, Process, Technology <li>People and Process <li>Vocabularies and URI Schemes <li>Baselines and Targets</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4073 http://purl.org/dc/elements/1.1/title Design Patterns for Clinical Application Ontologies
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http://data.semanticuniverse.com/resource/semtech-2011-4073 http://purl.org/dc/elements/1.1/abstract Design patterns for leveraging application ontologies within real-world software applications both for data integration as well as UI needs without the need for full fledged DL processing.
http://data.semanticuniverse.com/resource/semtech-2011-4073 http://purl.org/dc/elements/1.1/description Although well known and widely used as 'reference models', biomedical ontologies such as SNOMED, FMA, GO, etc. are rarely used directly within software applications. This is despite the fact that all of them are available as OWL / RDF and thus can straightforwardly be used by Semantic Web tools. More commonly, terms are extracted into far simpler representations to be used as controlled vocabularies for annotating notes, as term lists within data entry systems, etc. Furthermore, these reference models lack constructs such as data types and measurements, which are the basic elements of clinical instance data. <P> Exploiting the knowledge within these models remains a challenge but much can be achieved via common patterns in how these models are used effectively. This presentation describes Application Ontology approaches that can be used to integrate clinical domain ontologies into real-world systems with examples from research work at the Cleveland Clinic and CWRU. <P> Topics covered include: * Differences between Domain vs Application models * Modular vs Monolithic Application ontologies. * Types of Data * Measurement Units * Leveraging Formulae and performing calculations * Using ontology to guide rendering of User Interfaces <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3856 http://purl.org/dc/elements/1.1/title SENSEnews: Semantic Search Technology for Financial Markets
http://data.semanticuniverse.com/resource/semtech-2011-3856 http://purl.org/dc/elements/1.1/description SENSEnews is a Web service that harnesses semantic technology to enable an investor to instantly assess the character and impact of all available information from traditional, online and social media on a company's valuation. Relying on well-established inefficiencies in the market for stocks, SENSEnews enables its users to track in real time the aggregate of all new information and commentary about a company, and in many cases before the market, as a whole, prices that information into the value of its stock. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3856 http://purl.org/dc/elements/1.1/abstract Valuation of securities solely based on analyzing aggregated news and social media content using semantic search technology.
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http://data.semanticuniverse.com/resource/semtech-2011-3911 http://purl.org/dc/elements/1.1/abstract To identify and describe significant use cases for the use of semantic technologies in the telecommunications domain.
http://data.semanticuniverse.com/resource/semtech-2011-3911 http://swrc.ontoware.org/ontology#keywords semantic-applications
http://data.semanticuniverse.com/resource/semtech-2011-3911 http://purl.org/dc/elements/1.1/description As the quantity of data continues to increase exponentially, there is no place where more of this information is flowing than in/over the world?s telecommunication networks. As such, huge potential exists for the application of semantic technologies to this domain, affording benefits such as data compression, improved interoperability, inferencing of latent relationships, etc. But what are the real use cases for semantic technologies in the realm of telecommunications, both in terms of today?s requirements and tomorrow?s potential opportunities? This talk will present a collection of key semantic use cases having particular relevance to the domain of telecommunications. Examples will be given of the types of telecommunications applications that might benefit most from semantic technologies and the specific semantic techniques that might be employed will be explored. The talk will also identify key challenges/open issues and will summarize on-going research efforts attempting to address theses areas. <ul><li>Telecommunications domain overview <li>Current applications requirements, future potential opportunities <li>Specific use cases for semantics in telecommunications <li>Challenges and open issues <li>Current research overview</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3911 http://purl.org/dc/elements/1.1/title Semantic Use Cases for the Telecommunications Domain
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http://data.semanticuniverse.com/resource/semtech-2011-3911 http://www.w3.org/2000/01/rdf-schema#label Semantic Use Cases for the Telecommunications Domain
http://data.semanticuniverse.com/resource/semtech-2011-3911 http://purl.org/dc/elements/1.1/audience Case Study
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http://data.semanticuniverse.com/resource/kavi-goel http://www.w3.org/2001/vcard-rdf/3.0#org Google Inc.
http://data.semanticuniverse.com/resource/semtech-2011-4043 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/yefim-zhuk
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http://data.semanticuniverse.com/resource/semtech-2011-4043 http://purl.org/dc/elements/1.1/description This presentation follows a case study by the EDM Council and others on semantic modeling of mortgage backed securities. The aim was to demonstrate the benefits of using semantic tagging of securities and mortgage loans information at source, to show how this would benefit systemic risk analysis. <P> The Proof of Concept used and extended the EDM Council Semantics Repository. We defined a "Semantic Data Model", being a model in class model format with the same content as the semantic model, as a basis for application development. <P> Participants contributed data elements they needed for systemic risk analysis. These were reverse engineered into the Semantics Repository, resulting in the addition of a new Loans section. This was subjected to formal subject matter expert review to refine and complete the loans ontology. We share some of our experiences in completing this new loans material with business domain experts. <P> <ul><li>Demonstrate benefits of semantic tagging of source documentation for systemic risk analysis of mortgage backed securities <li>Created a "Semantic Data Model" and identified the relationships between semantic model constructs and the corresponding data model constructs <li>Identified the physical data elements needed to feed systemic risk applications, working backwards from these to logical data model constructs and thence to semantic model constructs <li>Extended the EDM Council model to encompass loan and mortgage loan terms <li>Detailed experience in subject matter expert review of the new content</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4043 http://purl.org/dc/elements/1.1/abstract Case study on semantic modeling of mortgage backed securities, aimed at demonstrating the benefits of semantic tagging of securities and mortgage loans information at source to enable systemic risk analysis.
http://data.semanticuniverse.com/resource/semtech-2011-4043 http://swrc.ontoware.org/ontology#keywords systemic-risk
http://data.semanticuniverse.com/resource/semtech-2011-4043 http://purl.org/dc/elements/1.1/title Semantic Modeling of Mortgage Backed Securities: Case Study
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http://data.semanticuniverse.com/resource/semtech-2011-4043 http://www.w3.org/2000/01/rdf-schema#label Semantic Modeling of Mortgage Backed Securities: Case Study
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http://data.semanticuniverse.com/resource/semtech-2011-4013 http://purl.org/dc/elements/1.1/abstract The ?messy? text of our mobile lives doesn?t have to challenge today?s natural language processing systems. Learn how information extraction systems can successfully take on mobile text for the win.
http://data.semanticuniverse.com/resource/semtech-2011-4013 http://purl.org/dc/elements/1.1/title Extending Semantic Analysis to Mobile Texts
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http://data.semanticuniverse.com/resource/semtech-2011-4013 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2011-4013 http://purl.org/dc/elements/1.1/description Today, natural language processing (NLP) systems are successfully used to extract valuable semantic information from "clean" texts, such as newswire documents. However, most current NLP systems struggle mightily when faced with the "messy" text we interact with daily on mobile devices, including short text messages, Twitter "tweets", Facebook status messages, and e-mails. Unlike newswire documents, mobile texts feature jargon and abbreviations that can trip up even the most robust of information extraction systems. <P> In this talk, we will discuss the ways information extraction systems can be made robust enough to deal with mobile text. We will cover both statistical techniques that can be used to begin to model an individual's patterns of usage across different types of mobile text, as well as explore how data from personal data repositories (e.g. a personal contact database) or social networks can be used to improve the quality of extraction from "messy" text substantially. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4013 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mike-perkowitz
http://data.semanticuniverse.com/resource/semtech-2011-4013 http://www.w3.org/2000/01/rdf-schema#label Extending Semantic Analysis to Mobile Texts
http://data.semanticuniverse.com/resource/semtech-2011-4013 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://swrc.ontoware.org/ontology#keywords data-interoperability
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://purl.org/dc/elements/1.1/title Semantic Technologies and Statoil's Integration Layer for Plant Information Systems
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://purl.org/dc/elements/1.1/abstract To present experiences with using semantic technologies in the Oil and Gas industry and in particular to describe Statoil's challenges when mapping complex legacy data sources to a semantic model.
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http://data.semanticuniverse.com/resource/semtech-2011-3983 http://purl.org/dc/elements/1.1/description Statoil has approximately 40 plants connected to an infrastructure of fiber-optic cables. In an effort to support business needs globally, Statoil is currently implementing a new corporate integration layer for plant information systems. The vision is to provide enterprise-wide access to plant and equipment related data, through standardized information models combining data from different sources, to end-user applications. One of the key challenges has been to define and implement a semantic data model to support standardization of plant data using RDF/XML. This model has been populated in an RDF triple store for end user application and querying support. New applications to be put in production on top of the new integration layer are key drivers in the success of the project. For example, the Real Time Visualization project will deliver information work spaces for data visualization and collaboration. <P> Main topics to be presented: 1) Experiences with mapping legacy data to a semantic model, 2) Challenges and benefits of using semantic technologies in practice, 3) Nomenclature and standardization work using ISO 15926 - the Oil and Gas Ontology, 4) Future roadmap for semantic technologies in Statoil <P>
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://purl.org/dc/elements/1.1/audience Business
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http://data.semanticuniverse.com/resource/semtech-2011-3983 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jennifer-sampson
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3983 http://www.w3.org/2000/01/rdf-schema#label Semantic Technologies and Statoil's Integration Layer for Plant Information Systems
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http://data.semanticuniverse.com/resource/david-schairer http://www.w3.org/2001/vcard-rdf/3.0#title CTO & Co-founder
http://data.semanticuniverse.com/resource/david-schairer http://www.w3.org/2001/vcard-rdf/3.0#org TrapIt
http://data.semanticuniverse.com/resource/semtech-2011-3772 http://swrc.ontoware.org/ontology#keywords search-engines
http://data.semanticuniverse.com/resource/semtech-2011-3772 http://swrc.ontoware.org/ontology#keywords seo
http://data.semanticuniverse.com/resource/semtech-2011-3772 http://swrc.ontoware.org/ontology#keywords data
http://data.semanticuniverse.com/resource/semtech-2011-3772 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-3772 http://purl.org/dc/elements/1.1/description Semantic technologies are experiencing a "coming of age" and are more accessible to web developers than ever before. For the past several years, RDFa has been on the forefront of a growing web of data. Much of the focus of RDFa has been on it's use in search engine optimization, starting with Yahoo! Search Monkey, with more recent adoption from Google Rich Snippets and Facebook's Open Graph. While visibility on search engines is important to businesses, developers can use RDFa for a plethora of other purposes. In this session, we will take a deeper dive into RDFa examples and their output, and map these outputs to specific business use cases, which include: <ul><li>SEO implications and data rich markup results <li>Using RDFa as a data source for web applications <li>Replacing/augmenting traditional data APIs (XML/JSON) with "Human-Readable" APIs that are also accessible to machines <li>More!</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3772 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-3772 http://www.w3.org/2000/01/rdf-schema#label Practical Business Uses of RDFa: Search Engines and Beyond!
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http://data.semanticuniverse.com/resource/semtech-2011-3772 http://purl.org/dc/elements/1.1/title Practical Business Uses of RDFa: Search Engines and Beyond!
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http://data.semanticuniverse.com/resource/semtech-2011-3772 http://purl.org/dc/elements/1.1/abstract Objective: to expose developers and business leaders to the power and utility of RDFa
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http://data.semanticuniverse.com/resource/semtech-2011-4085 http://purl.org/dc/elements/1.1/title Seevl - Reinventing Music Discovery
http://data.semanticuniverse.com/resource/semtech-2011-4085 http://purl.org/dc/elements/1.1/description Music recommendation systems are often opaque, and do not give any clue to users why they recommend X if they like Y. Seevl tackles this problem by offering an explanatory recommendation system, based on the power of Linked Data and Semantic Web technologies. In this presentation, we will present Seevl's architecture and the possibilities it offers for the music industry and website owners that want to augment their website using such recommendations. In particular, we will discuss: - What data sources are currently available on the Web for describing musical knowledge - The Music Ontology - How we aggregate, interlink and curate the sources using MO - Semantic recommendations - The Seevl API <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4085 http://purl.org/dc/elements/1.1/abstract This presentation will describe Seevl, a spin-off of DERI currently in stealth mode, providing explanatory music recommendations using Linked Data.
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http://data.semanticuniverse.com/resource/semtech-2011-4140 http://purl.org/dc/elements/1.1/description With excessive volumes and increasing speeds of input channels, organizations no longer have to struggle to keep up. Adding better metadata to existing search engines can help alleviate some immediate issues, but in the long-term will not be adequate to deal with exponential content growth. This lightning talk will demonstrate how, rather than searching for information, you can now have intelligence delivered in real-time. Using automated semantic reasoning and information extraction, come and see how massive data, powered by SAS and enabled by VSTI, can be transformed to delivered intelligence. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3923 http://purl.org/dc/elements/1.1/title Semwebbers, LODers: What PubSubHubbub Can Do For You
http://data.semanticuniverse.com/resource/semtech-2011-3923 http://purl.org/dc/elements/1.1/description With the growth of microblogging services, information streams and more generally 'Citizen Sensing', there is a need for new architectures to enable real-time information syndication, discovery and notification on the Web. In this talk, we'll present how to combine PubSubHubbub - a simple, open, server-to-server web-hook-based pubsub (publish/subscribe) protocol - with Semantic with Semantic Web and Linked Data technologies to enable a real-time Semantic Web, making structured data usable in real-time on the Web. We'll present the combination of those approaches in the context of (1) real-time information monitoring (sparqlPush) and (2) distributed semantic social networking architectures (SMOB). In this talk attendees will learn: - What are the latest tends in citizen sensing and real-time information monitoring - What is the PubSubHubbub protocol and how it can be used for real-time notifications on the Web - How to use PubSubHubbub to monitor the result of SPARQL queries as data feeds - How to use PubSubHubbub to synchronise distributed Social Semantic Web data hub - How to enable a real-time Semantic Web <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3923 http://purl.org/dc/elements/1.1/abstract This talk sill discuss how PubSubHubbub can be used in combination with Semantic Web and Linked Data technologies to enable a real-time Semantic Web.
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http://data.semanticuniverse.com/resource/semtech-2011-4055 http://purl.org/dc/elements/1.1/abstract Linguistic semantic natural language processing interprets free text meaning accurately and scalably in large archives. The presentation describes current applications for search, auto-categorization, foldering, text analytics, filtering and sentiment analysis.
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http://data.semanticuniverse.com/resource/semtech-2011-4055 http://purl.org/dc/elements/1.1/title Managing Free Text Archives with Linguistic Semantics
http://data.semanticuniverse.com/resource/semtech-2011-4055 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kathleen-dahlgren
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http://data.semanticuniverse.com/resource/semtech-2011-4055 http://purl.org/dc/elements/1.1/description Semantic natural language processing interprets the meaning of free text and enables users to find, mine and organize very large archives quickly and effectively. Linguistic semantic processing finds all and only the desired information because it determines meaning in context and maps synonym and hyponym relationships. It avoids assigning incorrect relationships because meaning is precisely determined. At the same time it makes all the desired connections exhaustively because it is backed by a massive lexicon and semantic map. The key scalably of Cognition's linguistic semantic processing is bottom-up interpretation of the text, finding the meaning of words and phrases in the local context one at a time. The technology has a semantic map and algorithms that interpret language linguistically rather statistically, so that the meaning of a given document is independently determined. As a result the methods scale to a theoretically unlimited number of documents. Linguistic semantic NLP is being deployed in many applications that facilitate rapid and accurate management of very large archives. . 1. Free auto categorization - Texts are categorized into an existing ontology or a special client-defined ontology according to the salient concepts in them. <P> 2. Segregation by genre - The software determines which of a predetermined set of genres a documents falls into. In the legal domain, the genre set might be "contracts" and within "contracts", "employment contract", "services contract", etc., PPM, "pricing proposal", "mortgage agreement", and so on. <P> 3. Conceptual foldering (or tagging) - Documents are placed in conceptual folders using conceptual Boolean expressions that cover all of the topics desired for the folders. This is especially useful in e-Discovery, where documents can be culled leaving only the relevant portion to be reviewed. <P> 4. Intelligent search - The semantic search function retrieves almost all and only the desired documents. Very high precision is achieved by disambiguating words in context, and by phrasal reasoning. Very high recall is achieved by paraphrase and ontological reasoning. <P> 5. Text Analytics - Calculating the frequency and salience of words, word senses, concepts and phrases in a document or document base lays bare its significant semantic content. <P> 6. Sentiment analysis - With semantic processing, sentiments can be determined. Existing lexical resources identify the "pejorative" and "negative" words. <P> 7. Language monitoring - In some situations such as child chat or email, certain types of language may need to be blocked. Linguistic semantic processing detects undesirable (or desirable) language as defined by administrators. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3838 http://purl.org/dc/elements/1.1/description Today, we are inundated with information and have limited time to decipher which documents are of importance. This presentation will show how combining Natural Language Processing, Ontologies and Inference techniques help to identify key facts about a document; thus providing semantic context of the subject matter. We will demonstrate a tool that processes a list of documents to find the top ten documents of importance. We will also discuss how our Human Factors (HF) Ontology, represented in OWL, is utilized with Natural Language Processing to transform each document into a "semantic" model. By using these techniques, we are able to find the top three entities for several key concepts (like Location, Person, and Organization). Lastly, we will give you insights that we uncovered using SWRL rules process in the Pellet inference engine; the power of the discovery is in the inference techniques. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3838 http://purl.org/dc/elements/1.1/abstract This presentation will show how combining Natural Language Processing, Ontologies and Inference (Pellet) techniques help to identify key facts about a document; thus providing semantic context of the subject matter
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http://data.semanticuniverse.com/resource/semtech-2011-3808 http://www.w3.org/2000/01/rdf-schema#label 3 Case Studies Using Upper Ontologies
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http://data.semanticuniverse.com/resource/semtech-2011-3808 http://purl.org/dc/elements/1.1/description This presentation will briefly review gist, the minimalist upper ontology that was the basis of these three case studies and then describe each of the case studies in turn. Each of the case studies has very different outcomes and objectives and were in different industries and yet were able to benefit from the same upper ontology. The three case studies are: <ul><li>Sallie Mae/Automated the conversion of the OWL based Enterprise Ontology into a Message Model which was then the basis for their new SOA messages. New systems are in production and the ontology and messages are being evolved to meet changing requirements. <li>Procter and Gamble/Use of an OWL based Enterprise Ontology as the basis for organizing knowledge from departing researchers. The ontology has been built and extended for four research disciplines (Batteries, Toothbrushes, Feminine Care and Baby Care) and some limited prototypes of a larger scale knowledge sharing environment have been built. <li>LexisNexis/OWL based Enterprise Ontology as the basis for the next generation of LexisNexis core business. Project includes synthesizing hundreds of disparate knowledge sources and using the ontology as basis for advanced entity extraction. Project is also using high performance parallel process for the extraction process. </ul> The presentation will focus on how the upper ontology aided the conducting of the project, and will give attendees some real world examples they can take back to their own organizations. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3808 http://purl.org/dc/elements/1.1/abstract Educate attendees about three recent large scale projects that used an upper ontology as their basis.
http://data.semanticuniverse.com/resource/semtech-2011-3808 http://purl.org/dc/elements/1.1/title 3 Case Studies Using Upper Ontologies
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http://data.semanticuniverse.com/resource/semtech-2011-4152 http://purl.org/dc/elements/1.1/abstract In our talk, we present the Information Workbench as a self-service platform for the fast development of domain-specific Linked Data solutions.
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http://data.semanticuniverse.com/resource/semtech-2011-4152 http://purl.org/dc/elements/1.1/description Linked Data has become increasingly relevant for the Enterprise, allowing companies to integrate internal enterprise data and interlink it with external data. The development of concrete solutions implementing the Linked Data paradigm, though, is often a time-consuming and costly task. In our talk, we present the Information Workbench as a self-service platform for the fast development of domain-specific Linked Data solutions. Designed with the goal to leverage Linked Data deployment in the enterprise, the Information Workbench implements concepts and features for data integration, interactive visualization, exploration and analytics, as well as the collaborative acquisition and authoring of Linked Data. Built on an extensible platform, custom solutions can be realized in a self-service manner: Data sources can be dynamically integrated at the click of a button; the user interface can be flexibly customized based on a large, extensible collection of widgets supporting data visualization, exploration, and collaboration. <P> We present solutions and applications of the Information Workbench in a variety of domains, including the Life Sciences, Social Media, and Data Center Management. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4152 http://purl.org/dc/elements/1.1/title fluid Operations Sponsored Session: Everything Self-service: Linked Data Applications with the Information Workbench
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http://data.semanticuniverse.com/resource/semtech-2011-3935 http://purl.org/dc/elements/1.1/title Semantic Technologies in Practice: Transforming the Field by Taking the Pain out of Data Integration
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http://data.semanticuniverse.com/resource/semtech-2011-3935 http://purl.org/dc/elements/1.1/abstract Semantic technologies have moved from visionary concepts to practical, transformational applications for research and enterprise data integration. This talk reviews real industry cases where semantic technologies have positively impacted non-experts.
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http://data.semanticuniverse.com/resource/semtech-2011-3935 http://purl.org/dc/elements/1.1/description Traditional warehousing and federation methods are mature and suitable for many core data integration and federation applications. However, they are demonstrably unsuited for dynamic data integration and enterprise federation in many large markets, including massive niches within scientific research, healthcare, legal, and telecommunications. <P> Semantic technologies deliver faster, far more extensible data modeling and integration methods directly to subject matter experts as well as to formal ontologists and enterprise architects. Although seemingly modest and technical in presentation, these radical efficiency and extensibility benefits are particularly relevant in business and research environments that deal with time-sensitive integration requirements and changing data that span multiple information domains. <P> This talk describes use of specific semantic technologies such as IO Informatics? Knowledge Explorer? with customers such as Pfizer, FDA, and leading research hospitals. The talk demonstrates how semantic data integration methods have changed the playing field for rapid integration of complex, changing data. <P> Direct technology benefits reviewed include: <ul><li>Faster time to core integration: specific examples show how users have avoided the common pain of waiting until it is too late for the next data mart or federated middleware application <li>Reduced task burden on IT experts: domain subject matter experts can now do integration on the fly and make these integrations available to IT <li>Results in adaptable, extensible integrated knowledge bases: knowledge creators and consumers can now add new datasets and enrich existing knowledge bases on the fly, no more brittle applications and databases <li>Unexpected benefits of semantically linked data: including drag and drop connectivity to new data sources, visual network queries for pattern-based searching, and decision-support</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4037 http://purl.org/dc/elements/1.1/description While emerging content delivery engines promise more finely tuned personalization capabilities, most platforms today still rely heavily on collaborative concepts and crowdsourcing to produce a pseudo-personalized experience. Semantic innovations now allow for a fundamentally different, and better, surfacing engine, building a unique ontology around every individual user. How the user interacts with information leads to personalization rather than fitting the user into the nearest category. <P> This presentation will discuss how semantic surfacing can build a multidimensional ontological space around an individual, using the experience of SRI?s latest spinout, TrapIt, as a case study. Because TrapIt?s semantic surfacing engine is not based on collaborative ratings, it doesn't encounter the 'thick path' problem, where personalization tends to converge into popularity within localized topic areas. Instead, semantic surfacing provides the user with highly relevant results even though there is no clear path using traditional search and keyword discovery mechanisms back to the user's original topic. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4037 http://purl.org/dc/elements/1.1/abstract Using SRI's innovative spin-out Trapit as a case study, this presentation will discuss how semantic surfacing is being optimized for better personalization of real-time content delivery and recommendation.
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http://data.semanticuniverse.com/resource/semtech-2011-3851 http://purl.org/dc/elements/1.1/title Semantic Databases and Supercomputers
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http://data.semanticuniverse.com/resource/semtech-2011-3851 http://www.w3.org/2000/01/rdf-schema#label Semantic Databases and Supercomputers
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http://data.semanticuniverse.com/resource/semtech-2011-3851 http://purl.org/dc/elements/1.1/description For large-scale semantic database applications that involve complex queries and/or complex inferencing, the huge memories and parallel computing horsepower of supercomputers provide a significant advantage. The authors of this presentation have been exploring approaches to implementing semantic web databases on the Cray XMT supercomputer, a parallel system that can be configured with several terabytes of globally addressed, shared memory. We will describe some of our research results to date, including: <ul><li>Analyzing a full day?s worth of Twitter data, rapidly identifying the tree-structured news-dissemination portion as well as the conversation clusters. <li>Performing RDFS closure on a billion-triple data set, around 7x faster than previous results. <li>Performing prototype queries on a data set of 20 billion triples (all held in main memory), while scaling up to 512 processors. <li>Prototyping an API designed to facilitate porting commercial semantic web databases onto the XMT.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3851 http://swrc.ontoware.org/ontology#keywords supercomputers
http://data.semanticuniverse.com/resource/semtech-2011-3851 http://swrc.ontoware.org/ontology#keywords query-processing
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http://data.semanticuniverse.com/resource/semtech-2011-3851 http://purl.org/dc/elements/1.1/abstract The authors will describe several research results focused on ways to implement a semantic web RDF triples database on the Cray XMT, a highly multithreaded, shared memory supercomputer.
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http://data.semanticuniverse.com/resource/semtech-2011-4134 http://purl.org/dc/elements/1.1/description The BBC's World Cup web site was probably the first major implementation of semantic web technologies on a commercial media site. John was Chief Technical Architect, Journalism and Knowledge, BBC Future Media & Technology at the time, and recently joined the Press Association (UK's version of the Associated Press) where he is again working on integrating semantic technologies. Some background on his work is available in a "call to action" John issued on a BBC tech blog last year. It is available here: http://www.bbc.co.uk/blogs/bbcinternet/2010/07/the_world_cup_and_a_call_to_ac.html <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3917 http://www.w3.org/2000/01/rdf-schema#label The RDFA/SEO Wave - How to Catch it and Why
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http://data.semanticuniverse.com/resource/semtech-2011-3917 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://purl.org/dc/elements/1.1/abstract The Semantic web is now mainstream. When you shop online, odds are you are using Semantic Web technology. This development is primarily driven by Search Engine Optimization (SEO) considerations via the use of RDFa.
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://purl.org/dc/elements/1.1/title The RDFA/SEO Wave - How to Catch it and Why
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://swrc.ontoware.org/ontology#keywords semantic-seo
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://swrc.ontoware.org/ontology#keywords goodrelations
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://swrc.ontoware.org/ontology#keywords rdfa-production
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/barbara-h-starr
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://purl.org/dc/elements/1.1/description Linked Open Commerce (LOC) has been an amazing addition to the Linked Open Data (LOD) cloud. Companies like Overstock, BestBuy, Tesco and many others are using RDFa and microformats in their webpages to optimize search. Other companies are choosing to make their "metadata" (almost becoming a misnomer as it can be very specific) about their product catalogs available via downloadable RDF files. This development is primarily driven by Search Engine Optimization (SEO) considerations, however, there is a great opportunity to use this recently available metadata for new types of services. <P> Clearly, e-commerce is not the only domain. There are many vertical markets leveraging the technology. <P> In this presentation, we will discuss microformats and RDFa, the pattern of their adoption with major industry players (such as Google, Bing, and Facebook), as well as thoughts around applications one could build with the new exploding metadata sets. <P> - <P>
http://data.semanticuniverse.com/resource/semtech-2011-3917 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-search
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords opinion-mining
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords machine-learning
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://purl.org/dc/elements/1.1/title Geo-Social Semantics and Hybrid Reasoning for Smart Mobile Services
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-4049 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords hybrid-reasoning
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://purl.org/dc/elements/1.1/abstract In this presentation, we will focus on a hybrid reasoning technology and semantic interoperability between geo-location data and social network data. We will introduce developed commercial application working on the smart phone like Android.
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords smart-phone
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http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords social-network-analysis
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-social-networks-and-collaboration
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://www.w3.org/2000/01/rdf-schema#label Geo-Social Semantics and Hybrid Reasoning for Smart Mobile Services
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords geo-semantics
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://purl.org/dc/elements/1.1/description As smart phone and devices progressed and became popular, they offer innovative user experiences for sharing digital content and personal experiences in mobile environment. The emerging evolution of communication hardware, network and software infrastructures offer user-centric services which are able to smart interactions between people, content, services and physical things. We will introduce the concept of semantic interoperability and hybrid reasoning for heterogeneous social network data and geo-location data set. Developed hybrid reasoning engine consists of ontology and rule based deduction and machine learning based induction for dealing with huge and real time mobile data set. We?ll also demonstrate a personalized smart application including content, service and expert recommendation based on location and specified topics. <P> This presentation will cover the following topics: <ul> <li>Architecture for hybrid reasoning <li>Interoperability for heterogeneous mobile data <li>Mobile geo-context query and reasoning <li>Mobile social context reasoning <li>Opinion mining for social services <li>Mobile social network analysis and expert recommendation <li>Real time geo-social semantic service for Android phones</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://swrc.ontoware.org/ontology#keywords social-semantics
http://data.semanticuniverse.com/resource/semtech-2011-4049 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/tony-lee
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http://data.semanticuniverse.com/resource/digital-enterprise-research-institute http://xmlns.com/foaf/0.1/name Digital Enterprise Research Institute
http://data.semanticuniverse.com/resource/digital-enterprise-research-institute http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/nuno-lopes
http://data.semanticuniverse.com/resource/digital-enterprise-research-institute http://www.w3.org/2000/01/rdf-schema#label Digital Enterprise Research Institute
http://data.semanticuniverse.com/resource/digital-enterprise-research-institute http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/axel-polleres
http://data.semanticuniverse.com/resource/mark-greaves http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/mark-greaves http://www.w3.org/2000/01/rdf-schema#label Mark Greaves
http://data.semanticuniverse.com/resource/mark-greaves http://xmlns.com/foaf/0.1/name Mark Greaves
http://data.semanticuniverse.com/resource/mark-greaves http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/652.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/mark-greaves http://www.w3.org/2001/vcard-rdf/3.0#title Director, Knowledge Systems
http://data.semanticuniverse.com/resource/mark-greaves http://www.w3.org/2001/vcard-rdf/3.0#org Vulcan Inc.
http://data.semanticuniverse.com/resource/jans-aasman http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/jans-aasman http://www.w3.org/2000/01/rdf-schema#label Jans Aasman
http://data.semanticuniverse.com/resource/jans-aasman http://xmlns.com/foaf/0.1/name Jans Aasman
http://data.semanticuniverse.com/resource/jans-aasman http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3404.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/jans-aasman http://xmlns.com/foaf/0.1/onlineAccount http://www.linkedin.com/company/167333
http://data.semanticuniverse.com/resource/jans-aasman http://www.w3.org/2001/vcard-rdf/3.0#title CEO
http://data.semanticuniverse.com/resource/jans-aasman http://www.w3.org/2001/vcard-rdf/3.0#org Franz Inc
http://data.semanticuniverse.com/resource/mark-crawford http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/mark-crawford http://www.w3.org/2000/01/rdf-schema#label Mark Crawford
http://data.semanticuniverse.com/resource/mark-crawford http://xmlns.com/foaf/0.1/name Mark Crawford
http://data.semanticuniverse.com/resource/mark-crawford http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3411.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/mark-crawford http://www.w3.org/2001/vcard-rdf/3.0#title Standards Strategist
http://data.semanticuniverse.com/resource/mark-crawford http://www.w3.org/2001/vcard-rdf/3.0#org SAP Labs
http://data.semanticuniverse.com/resource/playence-gmbh http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/playence-gmbh http://xmlns.com/foaf/0.1/name playence GmbH
http://data.semanticuniverse.com/resource/playence-gmbh http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/sinuhe-arroyo
http://data.semanticuniverse.com/resource/playence-gmbh http://www.w3.org/2000/01/rdf-schema#label playence GmbH
http://data.semanticuniverse.com/resource/cambridge-semantics-inc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/cambridge-semantics-inc http://xmlns.com/foaf/0.1/name Cambridge Semantics Inc
http://data.semanticuniverse.com/resource/cambridge-semantics-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/lee-feigenbaum
http://data.semanticuniverse.com/resource/cambridge-semantics-inc http://www.w3.org/2000/01/rdf-schema#label Cambridge Semantics Inc
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/dc/elements/1.1/description Drawing on real world examples, this presentation covers many of the potential pitfalls that can torpedo an ontology project. We will look at the political and business issues that often arise in these types of projects and discuss how a well developed communications and governance plans can be an essential set of tools for maintaining support for ontology initiatives. Being able to articulate the business goals, organizational impacts, usage and management of the ontology is an essential part of any enterprise ontology project. The process of creating these tools will surface many of the potential political, financial and technical problems and provides an excellent opportunity to social and evangelize the project. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-09T11:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://www.w3.org/2000/01/rdf-schema#label Negotiating Business and Political Realities in an Ontology Project
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/gary-carlson
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-project-management
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/dc/elements/1.1/abstract Overview / discussion of key strategies for successfully implementing an ontology
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-09T10:10:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://swrc.ontoware.org/ontology#keywords business-justification
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://swrc.ontoware.org/ontology#keywords standards
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://swrc.ontoware.org/ontology#keywords governance
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2011-4019 http://purl.org/dc/elements/1.1/title Negotiating Business and Political Realities in an Ontology Project
http://data.semanticuniverse.com/resource/syngenta http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/syngenta http://xmlns.com/foaf/0.1/name Syngenta
http://data.semanticuniverse.com/resource/syngenta http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/derek-scuffell
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http://data.semanticuniverse.com/resource/self http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/self http://xmlns.com/foaf/0.1/name self
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http://data.semanticuniverse.com/resource/self http://www.w3.org/2000/01/rdf-schema#label self
http://data.semanticuniverse.com/resource/forbescom http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/forbescom http://xmlns.com/foaf/0.1/name forbes.com
http://data.semanticuniverse.com/resource/forbescom http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/steve-bond
http://data.semanticuniverse.com/resource/forbescom http://www.w3.org/2000/01/rdf-schema#label forbes.com
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords excel
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords cambridge-semantics
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/dc/elements/1.1/title 5 Minutes to the Epiphany: Lightning Fast Data Integration for Business
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/dc/elements/1.1/description The world stores most of its valuable business data in relational database systems. The key challenge to effectively integrating relational data with the Semantic Web world is expressing the mapping between low level relational constructs and ontological data models. Traditionally?even in non-semantic ETL?this type of process can eat up a lot of calendar time because the subject matter experts in the business, database administrators, and ETL specialists must go back and forth to ensure that any mapping meets business requirements. <P> Ben will demonstrate that Semantic Web technologies can dramatically reduce the cost of relational data integration. In particular he'll show how a non-technical business user can use Microsoft Excel and Anzo ETL to intuitively create these mappings. In this 5 minute lightning session, he will, from scratch, define mappings from an existing clinical database to the industry standard SDTM ontology and load the data into Anzo for live analysis. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords rdfrdb
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords semantic-application-development
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ben-h-szekely
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-enterprise-data-management
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords semantic-relational-mapping
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://purl.org/dc/elements/1.1/abstract In many Semantic Web applications, the first step is mapping and integrating data from a relational database. Ben will show you how it?s done in under 5 minutes.
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://www.w3.org/2000/01/rdf-schema#label 5 Minutes to the Epiphany: Lightning Fast Data Integration for Business
http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords anzo
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http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords data-integration
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http://data.semanticuniverse.com/resource/semtech-2011-3833 http://swrc.ontoware.org/ontology#keywords semantic-etl
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http://data.semanticuniverse.com/resource/nuno-lopes http://xmlns.com/foaf/0.1/name Nuno Lopes
http://data.semanticuniverse.com/resource/nuno-lopes http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/2592.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/nuno-lopes http://www.w3.org/2001/vcard-rdf/3.0#title PhD Student
http://data.semanticuniverse.com/resource/nuno-lopes http://www.w3.org/2001/vcard-rdf/3.0#org Digital Enterprise Research Institute
http://data.semanticuniverse.com/resource/vistology-inc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/vistology-inc http://xmlns.com/foaf/0.1/name VIStology, Inc.
http://data.semanticuniverse.com/resource/vistology-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/brian-ulicny
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http://data.semanticuniverse.com/resource/matthias-kaiser http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3412.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/matthias-kaiser http://www.w3.org/2001/vcard-rdf/3.0#title Technology Strategist
http://data.semanticuniverse.com/resource/matthias-kaiser http://www.w3.org/2001/vcard-rdf/3.0#org SAP Labs
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://purl.org/dc/elements/1.1/abstract Open APIs are hot. What are the key trends, the players, the strategies, and what does this mean to the semantic web? This session brings you up to speed on the fast moving world of open APIs.
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-web-services
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://swrc.ontoware.org/ontology#keywords web-services
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://purl.org/dc/elements/1.1/description Open APIs are hot. They?re everywhere these days and are rapidly becoming the development platform of the future. And they're important to the future of the semantic web. We?re seeing APIs for semantic tagging, open graphs of linked data, support of RDF and standards, and a host of other semantic web-related trends. And whether it?s APIs from big players like Facebook and Google, or specialized APIs from companies like Zemanta, Calais, and Freebase, there are lots of moving parts. <P> But it's a complex, fast-moving market with lots of questions: Who are the winning companies, what are the business models and what are the key technology trends? Using data and resources from ProgrammableWeb.com, this talk takes a top-down look at this space in order to get an up-to-date overview of major players, technologies and trends. <P> Key questions covered include: <ul><li>Who are the leaders in open APIs and why? <li>What are the business models and technology trends? <li>What semantic web technologies are being supported (or not)? <li>What are the key open API developments the semantic web community should be paying attention to?</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://swrc.ontoware.org/ontology#keywords mashups
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://swrc.ontoware.org/ontology#keywords apis
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://swrc.ontoware.org/ontology#keywords trends
http://data.semanticuniverse.com/resource/semtech-2011-3803 http://purl.org/dc/elements/1.1/title Open APIs&amp;the Semantic Web: State of the Market
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http://data.semanticuniverse.com/resource/semtech-2011-3803 http://swrc.ontoware.org/ontology#keywords platforms
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http://data.semanticuniverse.com/resource/semtech-2011-4146 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/lin-clark
http://data.semanticuniverse.com/resource/semtech-2011-4146 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-4146 http://www.w3.org/2000/01/rdf-schema#label Drupal: Easy Integration with the Web of Data
http://data.semanticuniverse.com/resource/semtech-2011-4146 http://purl.org/dc/elements/1.1/title Drupal: Easy Integration with the Web of Data
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http://data.semanticuniverse.com/resource/semtech-2011-4146 http://purl.org/dc/elements/1.1/description With the release of Drupal 7 in January, Drupal became the first mainstream CMS to enable RDFa publishing by default. In this session you will learn how to easily publish content in RDFa using Drupal and how to seamlessly integrate data from other sites and SPARQL endpoints into your Drupal site. <P> Participants may want to create a test site on their local computer. While not necessary for the session, it will help participants follow along. Installation instructions can be found at http://drupal.org/documentation/install. <P>
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http://data.semanticuniverse.com/resource/jennifer-sampson http://xmlns.com/foaf/0.1/name Jennifer Sampson
http://data.semanticuniverse.com/resource/jennifer-sampson http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3383.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T14:10:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://www.w3.org/2000/01/rdf-schema#label Personalization Without Tears
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://swrc.ontoware.org/ontology#keywords information-extraction
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/dc/elements/1.1/title Personalization Without Tears
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http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/dc/elements/1.1/description The internet is no longer ?one size fits all.? Today, personalization services are using publicly available personal data to enhance the quality of recommendations and/or to improve the relevance of search results. <P> While personalization algorithms have shown promise, most current algorithms require significant effort from users in order to return the best results. Personalization systems require users to click special links (e.g. Facebook ?likes?), share content with their social networks, answer potentially lengthy questionnaires, or share significant amounts of their personal data. <P> In this talk, we will discuss how information extraction, semantic search, and natural language processing technology can improve the quality of recommendations provided by personalization services ? without requiring any additional effort on the part of the user. We will talk about how current unsupervised systems can be used to build nuanced models of a user?s preferences and interests ? and the actions that they are likely to engage in. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4020 http://swrc.ontoware.org/ontology#keywords recommendation-engines
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://swrc.ontoware.org/ontology#keywords semantic-search
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://swrc.ontoware.org/ontology#keywords personalization-services
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T13:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/andrew-hickl
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://purl.org/dc/elements/1.1/abstract Today?s Internet isn?t ?one size fits all!? Learn how semantic technologies can help personalization services enhance the quality of recommendations and improve the relevancy of search results without burdening users.
http://data.semanticuniverse.com/resource/semtech-2011-4020 http://swrc.ontoware.org/ontology#keywords nlp
http://data.semanticuniverse.com/resource/semantrix http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/semantrix http://xmlns.com/foaf/0.1/name Semantrix
http://data.semanticuniverse.com/resource/semantrix http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/michael-f-mcgrath
http://data.semanticuniverse.com/resource/semantrix http://www.w3.org/2000/01/rdf-schema#label Semantrix
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http://data.semanticuniverse.com/resource/revelytix-inc http://xmlns.com/foaf/0.1/name Revelytix, Inc.
http://data.semanticuniverse.com/resource/revelytix-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/jon-modell
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http://data.semanticuniverse.com/resource/semtech-2011-3960 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#TutorialEvent
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http://data.semanticuniverse.com/resource/semtech-2011-3960 http://purl.org/dc/elements/1.1/title Semantic Architecture: Composing Resource-Oriented Environments
http://data.semanticuniverse.com/resource/semtech-2011-3960 http://purl.org/dc/elements/1.1/abstract A vision of how to apply modern technologies to solve conventional software problems.
http://data.semanticuniverse.com/resource/semtech-2011-3960 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3960 http://www.w3.org/2000/01/rdf-schema#label Semantic Architecture: Composing Resource-Oriented Environments
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http://data.semanticuniverse.com/resource/semtech-2011-3960 http://purl.org/dc/elements/1.1/description At the beginning of the 21st Century, we are still suffering from this Software Problem. Expensive, fragile and over budget software initiatives continue to plague the industry. There is no end of speculation of what might help solve the problem. Software engineering practices have been introduced, adopted and modified for years but the issues persist. <P> I will present a combination of technologies that I think will be a taste of the solution in the future. Resource-oriented architectures help unify software and the data that flows through it. New metadata languages such as RDF, SKOS and OWL provide standardized and edge-driven metadata schemes to help us organize all of these resources. Using NetKernel (http://netkernel.org) as a playground to explore these ideas, I will present some examples with flavors of Model-Driven Architecture (MDA), Aspect-Oriented Programming (AOP), REST and the Semantic Web woven together to produce some real progress. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3960 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/brian-sletten
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http://data.semanticuniverse.com/resource/ian-bailey http://www.w3.org/2001/vcard-rdf/3.0#org Model Futures
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http://data.semanticuniverse.com/resource/semtech-2011-4062 http://purl.org/dc/elements/1.1/abstract This session presents demonstrations from two industry use cases to illustrate the benefits of integrating semantic technologies along the whole chain, from knowledge acquisition to knowledge management to business application.
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://www.w3.org/2000/01/rdf-schema#label The ONTORULE Project: Where Ontology Meets Business Rules
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://swrc.ontoware.org/ontology#keywords ontologies
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/christian-de-sainte-marie
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http://data.semanticuniverse.com/resource/semtech-2011-4062 http://swrc.ontoware.org/ontology#keywords knowledge-management
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http://data.semanticuniverse.com/resource/semtech-2011-4062 http://purl.org/dc/elements/1.1/title The ONTORULE Project: Where Ontology Meets Business Rules
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http://data.semanticuniverse.com/resource/semtech-2011-4062 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/roman-korf
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://purl.org/dc/elements/1.1/description The ONTORULE project was initiated by a consortium of leading vendors of semantic technologies and business rules management systems, of top research institutions and of large industrial companies representing the user's side, to develop the integrated methodology and implementation technology that will enable users, from business executives over business analysts to IT developers, to interact in their own way with the part of a business application that is relevant to them. <P> We believe that one essential step towards achieving that objective is the ability to separate cleanly the representation of the knowledge at the business, operational and execution levels, on the one hand; and the business vocabulary from the business rules, on the other hand. <P> In this session, we will describe our results after two years of the project. Based on demonstrations from a steel industry and an automotive industry use cases, the session will cover: - The ONTORULE approach to business user's empowerment through semantic technologies; - The technology that is integrated in an ONTORULE platform, and how it is integrated using open standards: from business modelling and from ontology and rule acquisition from policy texts, to knowledge management, consistency maintenance across ontologies and rules, knowledge integration and combined execution; - The benefits from the approach, and the typical use cases. At the end of the project, the ONTORULE consortium will publish the specification of the integrated platform. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://swrc.ontoware.org/ontology#keywords knowledge-acquisition
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http://data.semanticuniverse.com/resource/semtech-2011-4062 http://swrc.ontoware.org/ontology#keywords knowledge-integration
http://data.semanticuniverse.com/resource/semtech-2011-4062 http://swrc.ontoware.org/ontology#keywords business-rules
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://www.w3.org/2000/01/rdf-schema#label Citizen Sensing, Social Media Analytics, and Applications
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/title Citizen Sensing, Social Media Analytics, and Applications
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/karthik-gomadam
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/selvam-velmurugan
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/description With rapid rise of social media popularity (500M+ Facebook users,100M+ twitter users) and near ubiquitous mobile access (4.1 billion actively-used mobile phones), sharing of observations and opinions has become common-place (nearly 100M tweets a day, 1.8 trillion SMSs in US last year). This has given us an unprecedented access to the pulse of a populace and the ability to perform analytics on social data to support a variety of socially intelligent applications -- be it towards targeted online content delivery or promoting social development in underdeveloped and developing countries. <P> This tutorial weaves three themes and respective topics: <ul><li>Opportunity in exploiting massive amounts of social data from participation of millions of users through a wide variety of on-line interaction mechanisms: SMS through simple mobile phones, tweets with time and location coordinates as well as multi-sensory metadata from sophisticated mobile devices. <li>Technical challenges and recent research efforts in extracting metadata from casual/informal user-generated content on social media platforms. <li>Experiences in building robust and scalable platforms and applications serving needs of: <ul><li>multi-nationals in developed countries and technologically sophisticated users and <li>crisis management and development-centric applications that involve and benefit the common man in developing countries.</ul> <P> Although the tutorial covers a broad range of topics, we will cover the following research efforts in sufficient depth: 1) understanding and analysis of informal text, esp. microblogs (e.g., issues of cultural entity extraction and role of semantic/background knowledge enhanced techniques), and 2) building complex social media analytics platforms. Technical insights will be coupled with identification of computational techniques and real-world examples. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2011-3845 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#TutorialEvent
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http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3845 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/amit-p-sheth
http://data.semanticuniverse.com/resource/tony-lee http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/tony-lee http://www.w3.org/2000/01/rdf-schema#label Tony Lee
http://data.semanticuniverse.com/resource/tony-lee http://xmlns.com/foaf/0.1/name Tony Lee
http://data.semanticuniverse.com/resource/tony-lee http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/832.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/tony-lee http://xmlns.com/foaf/0.1/onlineAccount http://twitter.com/Tosajang
http://data.semanticuniverse.com/resource/tony-lee http://www.w3.org/2001/vcard-rdf/3.0#title CEO and President
http://data.semanticuniverse.com/resource/tony-lee http://www.w3.org/2001/vcard-rdf/3.0#org Saltlux, Inc.
http://data.semanticuniverse.com/resource/giovanni-tummarello http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/giovanni-tummarello http://www.w3.org/2000/01/rdf-schema#label Giovanni Tummarello
http://data.semanticuniverse.com/resource/giovanni-tummarello http://xmlns.com/foaf/0.1/name Giovanni Tummarello
http://data.semanticuniverse.com/resource/giovanni-tummarello http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/2190.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/giovanni-tummarello http://www.w3.org/2001/vcard-rdf/3.0#title Research Fellow
http://data.semanticuniverse.com/resource/giovanni-tummarello http://www.w3.org/2001/vcard-rdf/3.0#org Digital Enterprise Research Institute (DERI), National University of Ireland, Galway
http://data.semanticuniverse.com/resource/giovanni-tummarello http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3424.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/giovanni-tummarello http://www.w3.org/2001/vcard-rdf/3.0#org Digital Enterprise Research Institute, Galway
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://swrc.ontoware.org/ontology#keywords c#
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/rob-vesse
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://swrc.ontoware.org/ontology#keywords dotnetrdf
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://purl.org/dc/elements/1.1/abstract To present the dotNetRDF Core Library and some of its associated tool suite to raise awareness of its availability as a free and open source resource for .Net developers working with Semantic Web/RDF technologies.
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://purl.org/dc/elements/1.1/description dotNetRDF is a free and open source project intended to be a .Net equivalent of projects like Jena and Sesame. It provides a Core RDF/Semantic Web API and a suite of tools aimed at providing the bulk of the tools and APIs a .Net developer needs to work with RDF and the Semantic Web in their applications. The presentation will highlight the major features of the project and new features coming to future releases. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-software-development
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://purl.org/dc/elements/1.1/audience Product/Service Offering
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://swrc.ontoware.org/ontology#keywords .net
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#ConferenceEvent
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://purl.org/dc/elements/1.1/title dotNetRDF - A Semantic Web/RDF Library for .Net Developers
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T17:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://swrc.ontoware.org/ontology#keywords development
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://swrc.ontoware.org/ontology#keywords microsoft
http://data.semanticuniverse.com/resource/semtech-2011-3900 http://www.w3.org/2000/01/rdf-schema#label dotNetRDF - A Semantic Web/RDF Library for .Net Developers
http://data.semanticuniverse.com/resource/evan-william-patton http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/evan-william-patton http://www.w3.org/2000/01/rdf-schema#label Evan William Patton
http://data.semanticuniverse.com/resource/evan-william-patton http://xmlns.com/foaf/0.1/name Evan William Patton
http://data.semanticuniverse.com/resource/evan-william-patton http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3374.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/evan-william-patton http://www.w3.org/2001/vcard-rdf/3.0#title Graduate Research Assistant
http://data.semanticuniverse.com/resource/evan-william-patton http://www.w3.org/2001/vcard-rdf/3.0#org Tetherless World Constellation (RPI)
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/dc/elements/1.1/description Many businesses have processes that need to apply rules to distributed data, requiring both data interoperatbility and remote accessibility. W3C standards address all of these requirements, with RDF providing data interoperability, SPARQL providing remote accessibility, and RIF offering a rule framework that is compatible with these standards. <P> Revelytix has built a rules engine called "Rex" for applying rule documents in RIF to multiple data sources accessible through SPARQL. Rex reads all of the published RIF formats enabling both ease of development and maximum interoperability. By mapping RIF logic onto RDF forms, Rex is able to apply with arbitrary RIF to almost any RDF document, and can handle both logic and production rule dialects. <P> This talk will present: <ul><li>The concrete benefits of each of the various RIF formats. <li>How general RIF, particularly Frames and N-ary predicates, can be mapped to apply to almost any RDF. <li>How Rex uses SPARQL 1.1 to apply RETE principles and semi-naive evaluation in a distributed environment for maximum efficiency of logic rules. <li>How Rex addresses various types of Production Rules efficiently in a distributed environment. <li>The benefits and approaches needed to implement Rex in a functional programming language.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://www.w3.org/2000/01/rdf-schema#label RIF Execution on Distributed RDF
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/dc/elements/1.1/abstract Describes Rex, a system for efficiently running RIF rules on arbitrary distributed RDF, using SPARQL 1.1.
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/paul-gearon
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-3815 http://swrc.ontoware.org/ontology#keywords rules
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://swrc.ontoware.org/ontology#keywords federated
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://swrc.ontoware.org/ontology#keywords clojure
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://swrc.ontoware.org/ontology#keywords rif
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/dc/elements/1.1/title RIF Execution on Distributed RDF
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T15:05:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3815 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-rules
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://purl.org/dc/elements/1.1/title Enhancing Search Results with Linked Data in NASA's Mission Control Center
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://swrc.ontoware.org/ontology#keywords similarity-analysis
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://purl.org/dc/elements/1.1/description This presentation describes a specialized link-enhanced search system developed for NASA's International Space Station (ISS) Mission Control Center. The system, called XSearch, melds conventional text-based search with link extraction and textual similarity analysis to augment search results with relevant linked data. The linked data (in the form of flight control documents, anomaly reports, action-tracking records, etc.) provide users with additional context for understanding and interpreting the search results. Links are extracted from unstructured text fields in over one million mission control database records and documents, creating a web of ISS flight control information. In addition to extracting explicit links from text fields, the system performs text-based similarity analysis to identify implicit linkages among records and/or documents using standard information retrieval methods. Pairs of records and/or documents with high similarity scores are interpreted as being linked. XSearch has been in daily use by ISS flight controllers since July 2008. <P> This presentation will cover: <ul><li>user requirements <li>architecture <li>user interface <li>link detection methods <li>text analysis methods</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://swrc.ontoware.org/ontology#keywords search
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http://data.semanticuniverse.com/resource/semtech-2011-3791 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://purl.org/dc/elements/1.1/abstract This presentation describes a NASA-deployed search system that enhances its search results by displaying linked ancillary records discovered via text analysis and link extraction.
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T14:40:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://swrc.ontoware.org/ontology#keywords citation-analysis
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://swrc.ontoware.org/ontology#keywords automated-link-extraction
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/richard-m-keller
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://www.w3.org/2000/01/rdf-schema#label Enhancing Search Results with Linked Data in NASA's Mission Control Center
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3791 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-linked-data
http://data.semanticuniverse.com/resource/richard-lee http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/richard-lee http://www.w3.org/2000/01/rdf-schema#label Richard Lee
http://data.semanticuniverse.com/resource/richard-lee http://xmlns.com/foaf/0.1/name Richard Lee
http://data.semanticuniverse.com/resource/richard-lee http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3358.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/richard-lee http://www.w3.org/2001/vcard-rdf/3.0#title Senior Ontologist
http://data.semanticuniverse.com/resource/richard-lee http://www.w3.org/2001/vcard-rdf/3.0#org Booz Allen Hamilton
http://data.semanticuniverse.com/resource/semantic-systems-llc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/semantic-systems-llc http://xmlns.com/foaf/0.1/name Semantic Systems LLC
http://data.semanticuniverse.com/resource/semantic-systems-llc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/marcus-trevisani
http://data.semanticuniverse.com/resource/semantic-systems-llc http://www.w3.org/2000/01/rdf-schema#label Semantic Systems LLC
http://data.semanticuniverse.com/resource/booz-allen-hamilton http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/booz-allen-hamilton http://xmlns.com/foaf/0.1/name Booz Allen Hamilton
http://data.semanticuniverse.com/resource/booz-allen-hamilton http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/richard-lee
http://data.semanticuniverse.com/resource/booz-allen-hamilton http://www.w3.org/2000/01/rdf-schema#label Booz Allen Hamilton
http://data.semanticuniverse.com/resource/booz-allen-hamilton http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/john-hebeler
http://data.semanticuniverse.com/resource/tran-and-associates http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/tran-and-associates http://xmlns.com/foaf/0.1/name Tran and Associates
http://data.semanticuniverse.com/resource/tran-and-associates http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/bao-tran
http://data.semanticuniverse.com/resource/tran-and-associates http://www.w3.org/2000/01/rdf-schema#label Tran and Associates
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords hadoop
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jans-aasman
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/dc/elements/1.1/abstract How do you execute queries over hundreds of billions of triples distributed over dozens of machines? We discuss strategies for a streaming query flow mechanism that allows more parallelism and less copying than map/reduce principles used in NoSQL databases
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/dc/elements/1.1/title Querying a Trillion Triples
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://www.w3.org/2000/01/rdf-schema#label Querying a Trillion Triples
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-enterprise-data-management
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T10:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords database
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/dc/elements/1.1/description A complex graph database query is a collection of two types of primitive operations: primitives that generate possible solutions and primitives that constrain those solutions by rejecting solutions that are invalid. One approach to a distributed query engine is running each primitive operation in its own process and creating a graph of these processes by linking them together with network streams. Solutions flow from process to process, some primitives increasing the solution set and some reducing the solution set. Other processes in the graph perform operations on the solution stream such as sorting values or distributing values to database servers holding the best index for the next step. All processes potentially running at the same time if they have work to do. Out of the last process in the graph comes the solution to the query. The concepts we discuss work for SPARQL, Prolog, Common Logic and Social Network Analysis. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords map-reduce
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords nosql
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://swrc.ontoware.org/ontology#keywords query-processing
http://data.semanticuniverse.com/resource/semtech-2011-4002 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T11:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/anne-jude-hunt
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/simon-g-handley
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords data-warehouse
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords semantic-interoperability
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords linked-open-commerce
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords etl
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T14:40:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-3972 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords goodrelations
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords linked-open-data
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/title Real-time Semantic ETL
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/description With the spread of semantic markup across the Web, there is a growing need for extraction, transformation and loading (ETL) of very large volumes of streaming semantic data. The confluence of Linked Open Data (LOD) and Linked Open Commerce has created the opportunity to generate unprecedented value from triple-stores that correspond to the traditional data warehouse. These triple stores represent a logically-centralized view of cleansed, normalized data. In this presentation we describe our experiences with, and learnings from, building very large real-time semantic ETL systems. <P> We cover the following phases of semantic ETL: <ul><li>Extraction and cleansing: Acquiring and basic cleaning of raw semantic data. We cover such techniques as scraping Web pages and querying databases and Web APIs. We also consider the use of standard ontologies (e.g. GoodRelations), NLP, crowd-sourcing, hand-written rules, and machine learning to clean data. <li>Transformation: Semantic integration among many disparate vocabularies. We consider the use of a lingua franca such as GoodRelations as well as the use of semantic rules to achieve interoperability. <li>Load: The loading of the semantic data into distributed, scalable triple stores.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords federated-data
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://purl.org/dc/elements/1.1/abstract Large-scale, real-time semantic ETL is a necessity. E-commerce demands an integrated view into high volumes of streaming data. In these contexts, decision-making must be online and immediate. We describe our experiences with, and learnings from, building semantic ETL systems.
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords semantic-etl
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://swrc.ontoware.org/ontology#keywords real-time-semantics
http://data.semanticuniverse.com/resource/semtech-2011-3972 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-enterprise-data-management
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http://data.semanticuniverse.com/resource/semtech-2011-3972 http://www.w3.org/2000/01/rdf-schema#label Real-time Semantic ETL
http://data.semanticuniverse.com/resource/ulrich-reimer http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/ulrich-reimer http://www.w3.org/2000/01/rdf-schema#label Ulrich Reimer
http://data.semanticuniverse.com/resource/ulrich-reimer http://xmlns.com/foaf/0.1/name Ulrich Reimer
http://data.semanticuniverse.com/resource/ulrich-reimer http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3322.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/ulrich-reimer http://www.w3.org/2001/vcard-rdf/3.0#title Prof. Dr.
http://data.semanticuniverse.com/resource/ulrich-reimer http://www.w3.org/2001/vcard-rdf/3.0#org University of Applied Sciences St. Gallen
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-09T21:55:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://swrc.ontoware.org/ontology#keywords eclass-and-goodrelations-ontologies semantic-framework-for-medical-product-catalog-management collaborative-development-of-a-medical-device-catalog
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/abstract Implementing GoodRelations and eCl@ss ontologies to capture medical device information to facilitate integration with other contextual information, searchability across the web and easy to manage data.
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/description GoodRelations ontology has picked up significant interest in the semantic community, specifically in the context of publishing product-related data on the web in a way that enhances precise agent-based information discovery and search engine optimization (SEO). It is sufficiently abstract and extensible to be applicable in a wide range of e-commerce applications. Built upon GoodRelations is the eCl@ss ontology, based upon the eclass specification -- a comprehensive product classification system that is comprised of over 30,000 products and services and over 5,000 properties. Together, these ontologies form a powerful semantic framework for representing highly extensible products and services catalogs for any domain. This presentation will discuss implementation specifics related to these ontologies in the context of the development of a medical device reference application. This application, referred to as the Orthopaedia Device Reference (ODR), is hosted in a semantically-enabled Wiki, and provides a collaborative platform for the management of medical device information targeted primarily towards orthopaedic surgeons. ODR also implements publication of device information using RDFa for agent-based discovery and SEO, as well as a faceted and category-based search for products across all manufacturers based upon precise attribute data. The framework can be easily applied to other product domains. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/title Implementing GoodRelations and eCl@ss Ontologies for a Medical Device Reference Application
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-case-studies-use-cases
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http://data.semanticuniverse.com/resource/semtech-2011-3887 http://www.w3.org/2000/01/rdf-schema#label Implementing GoodRelations and eCl@ss Ontologies for a Medical Device Reference Application
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/christian-veillette
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-3887 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/sanjiva-nath
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-web-services
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/christopher-woodruff
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://purl.org/dc/elements/1.1/description The Open Data Protocol (OData) is an open protocol for sharing data. It provides a way to break down data silos and increase the shared value of data by creating an ecosystem in which data consumers can interoperate with data producers in a way that is far more powerful than currently possible, enabling more applications to make sense of a broader set of data. Every producer and consumer of data that participates in this ecosystem increases its overall value. <P> OData is consistent with the way the Web works ? it makes a deep commitment to URIs for resource identification and commits to an HTTP-based, uniform interface for interacting with those resources (just like the Web). This commitment to core Web principles allows OData to enable a new level of data integration and interoperability across a broad range of clients, servers, services, and tools. <P> In this talk Chris will provide an in depth knowledge to this protocol and how to implement an OData service for user consumption. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://purl.org/dc/elements/1.1/abstract The Open Data Protocol gives data producers and consumers a way to share and benefit from this new protocol. With OData there can be a new path of sharing and understanding data better and more efficiently.
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2011-3761 http://swrc.ontoware.org/ontology#keywords open-data-protocol
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://swrc.ontoware.org/ontology#keywords odata
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://purl.org/dc/elements/1.1/title Breaking Down "Data Silos" with the Open Data Protocol (OData)
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://www.w3.org/2000/01/rdf-schema#label Breaking Down "Data Silos" with the Open Data Protocol (OData)
http://data.semanticuniverse.com/resource/semtech-2011-3761 http://swrc.ontoware.org/ontology#keywords open-data
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http://data.semanticuniverse.com/resource/soonho-kim http://www.w3.org/2000/01/rdf-schema#label Soonho Kim
http://data.semanticuniverse.com/resource/soonho-kim http://xmlns.com/foaf/0.1/name Soonho Kim
http://data.semanticuniverse.com/resource/soonho-kim http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/3295.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/soonho-kim http://www.w3.org/2001/vcard-rdf/3.0#title Information Management Specialist
http://data.semanticuniverse.com/resource/soonho-kim http://www.w3.org/2001/vcard-rdf/3.0#org Food and Agricultural Organization of the United Nations
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http://data.semanticuniverse.com/resource/christian-de-sainte-marie http://www.w3.org/2001/vcard-rdf/3.0#title Program Manager
http://data.semanticuniverse.com/resource/christian-de-sainte-marie http://www.w3.org/2001/vcard-rdf/3.0#org IBM
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords instant-messaging
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/alexandre-passant
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords opo
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/owen-friel
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://www.w3.org/2000/01/rdf-schema#label Presence in the Enterprise: From State to Meaning
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords ontologies
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/description Presence, in an enterprise context refers to the availability of a person or entity to communicate, typically using instant messaging (but not restricted to IM). Currently this presence is largely derived from device state in a communication system. Presence is often presented to the user using ?traffic signal? like user interfaces where red shows a given user as busy, amber refers to away or idle and green signals a user to be available to communicate. While this colour coded representation can accurately reflect the state of a communication device, this state does not reflect the actual availability of a user. In this session we consider how the use of semantic web and linked data techniques can be utilized by reusing existing industry standards such as XMPP with Semantic Web vocabularies (OPO, SIOC) and dedicated privacy to provide a more intelligent and integrated representation of presence in a policy controlled enterprise communication system. This session will cover: Background on presence in the context of Enterprise Communications Standards and state of the art (XMPP, SIP, etc.) A unified presence architecture Semantic extensions to presence standards and integration with Semantic Web technologies (RDF, OWL, SPARQL) An architecture proposal for semantic presence and instant messaging. Demo of semantically enabled presence and instant messaging. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-social-networks-and-collaboration
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/keith-griffin
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/title Presence in the Enterprise: From State to Meaning
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords sioc
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/abstract This session demonstrates how the concept of presence in an enterprise communication system can be enhanced with meaning through the use of linked data and semantic web techniques.
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T17:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords presence
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/axel-polleres
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#ConferenceEvent
http://data.semanticuniverse.com/resource/semtech-2011-3942 http://swrc.ontoware.org/ontology#keywords xmpp
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords social-networks
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://www.w3.org/2000/01/rdf-schema#label Social Commerce and Semantic Web
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T12:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/dc/elements/1.1/description Commerce, or exchange of goods and service with some form of value, has been evolving for thousands of years both by creating new types of goods and services, as well as new forms of values. One of the latest phenomenon impacting commerce is the formation of pervasive social networks and the emergence of "Social Graphs". Consequently the term "Social Commerce", referring to the interaction between commercial world and variety of social graphs, generated a lot of excitement. In this session, we will discuss and introduce how the three essential components of a Social Graph - Identity, Relationships and Discoverability - relate to Social Commerce, and how various Semantic Web technologies help in making that happen. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords social-commerce
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords payments
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords micro-formats
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords commerce
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords rdfs
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords good-relations
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://swrc.ontoware.org/ontology#keywords open-graph
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-social-networks-and-collaboration
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http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/dc/elements/1.1/title Social Commerce and Semantic Web
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/dc/elements/1.1/abstract Semantic Web is one of the core foundations for Social Commerce phenomenon today. This session introduces you to the various stages involved in a eCommerce transaction, and how Semantic Web technologies not only helps in improving those, but also adds the Social element to them.
http://data.semanticuniverse.com/resource/semtech-2011-4074 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/praveen-p-alavilli
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T19:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://www.w3.org/2000/01/rdf-schema#label Combining Ontologies and Natural Language Processing for Knowledge Retrieval
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://swrc.ontoware.org/ontology#keywords knowledge-extraction
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://purl.org/dc/elements/1.1/abstract discussion of methods and exchange of experiences with the use of ontologies and NLP techniques to extract knowledge from large document collections
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T18:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://swrc.ontoware.org/ontology#keywords linguistics
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://purl.org/dc/elements/1.1/title Combining Ontologies and Natural Language Processing for Knowledge Retrieval
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-text-analysis
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://swrc.ontoware.org/ontology#keywords natural-language-processing-(nlp)
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/franz-j-kurfess
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3857 http://purl.org/dc/elements/1.1/description The most prevalent representation of knowledge in documents accessible to computers is in natural-language text form. In order to convert this knowledge into a format that computers can process more easily, the combination of linguistic methods and tools with ontologies promises to be mutually beneficial for both sides: NLP methods get assistance with issues like disambiguation, and ontologies can be expanded and instantiated with information extracted from documents. The goal of this discussion session is to provide an opportunity for practitioners and researchers to share ideas and experiences regarding: <ul><li>Natural language processing methods and tools for knowledge extraction from text documents <li>Named entity extraction and consolidation <li>Population of repositories with extracted information according to structures defined via ontologies <li>Augmentation of existing ontologies with concepts and relations derived from documents (ontology learning) <li>Integration of statistical methods into knowledge extraction</ul> <P>
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http://data.semanticuniverse.com/resource/ohio-center-of-excellence-in-knowledge-enabled-computing-(knoesis)-wright-state-university http://xmlns.com/foaf/0.1/name Ohio Center of Excellence in Knowledge-enabled computing (Kno.e.sis) , Wright State University
http://data.semanticuniverse.com/resource/ohio-center-of-excellence-in-knowledge-enabled-computing-(knoesis)-wright-state-university http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/amit-sheth
http://data.semanticuniverse.com/resource/ohio-center-of-excellence-in-knowledge-enabled-computing-(knoesis)-wright-state-university http://www.w3.org/2000/01/rdf-schema#label Ohio Center of Excellence in Knowledge-enabled computing (Kno.e.sis) , Wright State University
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http://data.semanticuniverse.com/resource/joe-devon http://xmlns.com/foaf/0.1/name Joe Devon
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http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/dc/elements/1.1/description The environmental and agricultural sciences, industrial processes and consumer gadgetry are increasingly relying on live data streams generated by large numbers of sensors to deliver knowledge and services. All the traditional problems of data management and data integration arise with real time data problems, plus some. Semantic technologies can help. The W3C has been developing an OWL ontology to describe sensors and sensor networks through its Incubator Group SSN-XG. <P> I will introduce the SSN ontology, its intended purpose, and its links to other standards and technologies especially those arising from the Open Geospatial Consortium. I will also talk about some of the ways this ontology is already being used in research projects --- from improving weather prediction, to animating knives, to feeding the world. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T17:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords sensors
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/dc/elements/1.1/title Semantic Sensor Networks: The W3C SSN-XG Ontology and How to Semantically Enable Real Time Sensor Feeds
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords semantics
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords environment
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords time-series
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords interoperabilty
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://www.w3.org/2000/01/rdf-schema#label Semantic Sensor Networks: The W3C SSN-XG Ontology and How to Semantically Enable Real Time Sensor Feeds
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-real-time-and-continuous-semantics
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords real-time
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kerry-lea-taylor
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://swrc.ontoware.org/ontology#keywords science
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://purl.org/dc/elements/1.1/abstract The W3C SSN-XG has developed an ontology for describing sensor networks. I will talk about the ontology and things for which it is used. My aim is to promote uptake of the developing "standard" and to promote longevity and maintenance.
http://data.semanticuniverse.com/resource/semtech-2011-4044 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-text-analysis
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/tom-reamy
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords categorization
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords software
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords entity-extraction
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/dc/elements/1.1/abstract This presentation surveys the range of text analytics software and develops a methodology for selecting the right type of software for your needs using a short proof of concept.
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords noun-phrase-extraction
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://www.w3.org/2000/01/rdf-schema#label Text Analytics Software: Selecting the Right Fit
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords sentiment-analysis
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords text-analytics
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-07T11:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords software-evaluation
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/dc/elements/1.1/title Text Analytics Software: Selecting the Right Fit
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://swrc.ontoware.org/ontology#keywords text-analytics-software
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T10:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://purl.org/dc/elements/1.1/description Text analytics software comes in a variety of options and selecting the right one for your organization has gotten more complex over the last couple of years. Almost everyone offers some form of noun phrase extraction, but beyond that there is little uniformity. Search and content management vendors have begun offering some text analytics capabilities but they typically lack a full development environment of auto-categorization, concept extraction, summarization, and sentiment analysis. Adding to the complexity is the issue of integration with existing enterprise software. <P> This session, using a number of recent examples, presents a methodology for making sense of the complexity and picking the right type of software for your current and future needs. The basic approach is to start with typical software evaluation, looking at general requirements and capabilities, but then adding a second phase of a Proof of Concept with your actual content. Since text analytics is all about semantics, this is the only realistic way to evaluate this type of software. We will cover how to set up and run a text analytics POC and how to get meaningful results. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3827 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/daniel-l-rubin http://www.w3.org/2000/01/rdf-schema#label Daniel L Rubin
http://data.semanticuniverse.com/resource/daniel-l-rubin http://xmlns.com/foaf/0.1/name Daniel L Rubin
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http://data.semanticuniverse.com/resource/daniel-l-rubin http://www.w3.org/2001/vcard-rdf/3.0#title Assistant Professor
http://data.semanticuniverse.com/resource/daniel-l-rubin http://www.w3.org/2001/vcard-rdf/3.0#org Stanford University
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http://data.semanticuniverse.com/resource/semtech-2011-3984 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/chary-tamirisa
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://purl.org/dc/elements/1.1/abstract Designed for IT professionals who have gained an understanding of semantic web technology and would like to bring it to their organization.
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-3984 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T07:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/yijing-(jenna)-zhou
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://purl.org/dc/elements/1.1/title Launching Semantic Web Technology in Enterprise IT - Lessons Learned From Leading/Managing Semantic Projects
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-3984 http://purl.org/dc/elements/1.1/description In today?s digital world, data is growing explosively and with it, the challenges of managing, searching and sharing data are growing painfully acute. Semantic web technology is enabling us to address these challenges in a novel way. Applications of the semantic web technologies are all around us in the Internet today. We have heard about social media and semantic search, ontology, etc. <P> As an IT professional, you have seen the trend and would like to bring the new ideas to your organization. So, where do you start? How do you justify the exploration of this new area? How do you gather momentum and management support around semantic web technology projects? If you are in a big corporation, how do you go about making progress? <P> Designed for IT professionals who have gained an understanding of semantic web technology and would like to bring it to their organization, this presentation will draw from the speakers? firsthand experience and help them make their vision a reality! <P> This presentation will cover the following topics: <ul><li>Potential applications of Semantic Web Technology <li>Potential barriers to adoption <li>Where to start <li>How to manage semantic projects <li>Lessons learned in managing semantic projects</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://swrc.ontoware.org/ontology#keywords semant-project-managment
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://www.w3.org/2000/01/rdf-schema#label Launching Semantic Web Technology in Enterprise IT - Lessons Learned From Leading/Managing Semantic Projects
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://swrc.ontoware.org/ontology#keywords lessons-learned
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-project-management
http://data.semanticuniverse.com/resource/semtech-2011-3984 http://swrc.ontoware.org/ontology#keywords barrier-for-adoption
http://data.semanticuniverse.com/resource/todd-pehle http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/todd-pehle http://www.w3.org/2000/01/rdf-schema#label Todd Pehle
http://data.semanticuniverse.com/resource/todd-pehle http://xmlns.com/foaf/0.1/name Todd Pehle
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http://data.semanticuniverse.com/resource/semtech-2011-3773 http://purl.org/dc/elements/1.1/title PANEL: Is Semantic Technology Strategic for Financial Services?
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http://data.semanticuniverse.com/resource/semtech-2011-3773 http://purl.org/dc/elements/1.1/abstract This session will provide an examination of the value proposition offered by semantic technology for the financial services industry, including discussion of applicable financial services use cases and governance challenges.
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http://data.semanticuniverse.com/resource/semtech-2011-3773 http://purl.org/dc/elements/1.1/description This session will examine the value proposition that semantic technology offers to the financial services industry. We will contrast semantic and conventional technologies from business and technical perspectives, and explore relevant financial service use cases that can benefit from the application of semantic technologies. We will also identify realistic cautions. Some areas covered will include: <ul><li>Semantic tagging for online banking and applications <li>Semantically enabled enterprise information management <li>Knowledge representation and risk management <li>Fraud, credit risk, product eligibility and other use cases <li>Business semantics management and governance challenges</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3954 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2011-3954 http://purl.org/dc/elements/1.1/description The Good Relations ontology has enjoyed considerable success with over 10,000 web pages making use of it to mark up products and services. The potential use of Good Relations markup goes well beyond reported SEO applications to supporting real interchange between vendors; comparison shopping, supply chain management, and deal negotiation. A barrier to these sorts of data sharing applications is aligning units - if one offering is given in terms of hours but another is given in terms of minutes, no exchange can be evaluated until some conversion is made to make the offerings comparable. Good Relations includes a way to reference standard units, but doesn't - and shouldn't - include conversion utilities. <P> QUDT is an ontology of Quantities, Units, Dimensions and Types that provides comprehensive information about units, their dimensions and conversions. In this presentation, we will show how Good Relations and QUDT can be used together. We will demonstrate the synergy with a comparison shopping application. <P> - Applications of Good Relations: Supply chain, Comparison, Negotiation - Quantities, Units, Dimensions and Types: QUDT - Controlled Vocabularies of Units - Further applications - dimensional analysis - Ontologies for Linked Data <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3954 http://purl.org/dc/elements/1.1/abstract The Good Relations ontology for commerce, combined with the QUDT ontology for quantities and units combine to produce an effective comparison shopping application.
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http://data.semanticuniverse.com/resource/semtech-2011-3954 http://purl.org/dc/elements/1.1/title Enhancing the Use of the Good Relations Ontology Using QUDT
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http://data.semanticuniverse.com/resource/semtech-2011-4086 http://purl.org/dc/elements/1.1/description Discussion will focus on applications of semantic technology to the rich patent corpus to aid in interpretation and analysis of intellectual property. A semantic patent analysis and automated patent generation system demo will be done. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4086 http://www.w3.org/2000/01/rdf-schema#label Semantic Technology and Patent Analysis
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http://data.semanticuniverse.com/resource/semtech-2011-4086 http://purl.org/dc/elements/1.1/abstract Presentation will discuss various applications of semantic technology to the rich patent corpus to aid in interpretation and analysis of intellectual property
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http://data.semanticuniverse.com/resource/semtech-2011-4086 http://purl.org/dc/elements/1.1/title Semantic Technology and Patent Analysis
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http://data.semanticuniverse.com/resource/semtech-2011-4141 http://www.w3.org/2000/01/rdf-schema#label Semantic Knowledge in a Mobile InfoApp
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http://data.semanticuniverse.com/resource/semtech-2011-4141 http://purl.org/dc/elements/1.1/title Semantic Knowledge in a Mobile InfoApp
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http://data.semanticuniverse.com/resource/semtech-2011-4141 http://purl.org/dc/elements/1.1/description InfoApps are mobile apps which deliver a diverse set of news, information, and entertainment while helping users create new content about the information delivered. Mobile tablets and smartphones provide new platforms for social networking, ranking, crowdsourcing, sentiment & emotion analysis. The mobile platform encourages more immediate and reactive response to news, events, and opinions. Providing interaction and management of this knowledge sharing is a task well suited to semantic technologies. A new InfoApp which selects, filters, and delivers content based on the semantics of its user, environment, history, and community will be described (quickly) with some slides of the app in action. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3996 http://purl.org/dc/elements/1.1/abstract This tutorial will provide an introduction to semantic wikis, as well as applications that use or are built on top of semantic wikis.
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http://data.semanticuniverse.com/resource/semtech-2011-3996 http://purl.org/dc/elements/1.1/title Semantic Wikis and Applications
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http://data.semanticuniverse.com/resource/semtech-2011-3996 http://www.w3.org/2000/01/rdf-schema#label Semantic Wikis and Applications
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http://data.semanticuniverse.com/resource/semtech-2011-3996 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/daniel-hansch
http://data.semanticuniverse.com/resource/semtech-2011-3996 http://purl.org/dc/elements/1.1/description This tutorial will provide an introduction to semantic wikis and applications that use or are built on top of semantic wikis. Semantic wikis combine the power of semantic technologies with the broad flexibility and usability of wikis. This tutorial will cover the origins and use cases for semantic wikis, the current state of art, case studies and examples, popular software extensions, semantic wiki based applications, and future trends. We will focus on the most used semantic wiki software package (the open-source Semantic MediaWiki, or SMW). We will go deep into SMW and its extension suite, e.g. extensions for editing, data integration, forms-based input, visualizations, linked data. We will also describe some real-world applications, including one integrating SMW with Microsoft Office applications. Attendees will learn how to build a semantic wiki application in as short as 30 minutes, with freely-downloadable software. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3996 http://swrc.ontoware.org/ontology#keywords semantic-wikis
http://data.semanticuniverse.com/resource/semtech-2011-3996 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/denny-vrandecic
http://data.semanticuniverse.com/resource/blue-ocean-semantic-web-solutions-gmbh-zürich-switzerland http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/blue-ocean-semantic-web-solutions-gmbh-zürich-switzerland http://xmlns.com/foaf/0.1/name Blue Ocean Semantic Web Solutions GmbH Zürich-Switzerland
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http://data.semanticuniverse.com/resource/blue-ocean-semantic-web-solutions-gmbh-zürich-switzerland http://www.w3.org/2000/01/rdf-schema#label Blue Ocean Semantic Web Solutions GmbH Zürich-Switzerland
http://data.semanticuniverse.com/resource/semtech-2011-3809 http://purl.org/dc/elements/1.1/description The Internet Archive hosted an international gathering of information professionals and administrators within libraries, archives, and museums May 19-20, 2011 in San Francisco to discuss technical, legal, and practical considerations in moving toward Linked Open Data publishing within this sector. The group examined issues pertaining to technical, legal, and educational aspects critical to move the field toward widespread adoption of Linked Open Data. Professionals from organizations such as the Smithsonian, MIT Libraries, German National Library, Creative Commons, and many more were present. This presentation will provide a comprehensive view of the current state of Linked Open Data in libraries, archives, and museums and review proceedings of this summit. The presentation will cover: <ul><li>Making a distinction between metadata about collection holdings and digital representations of collection holdings <li>What tools and techniques are being employed or explored for publishing LAM metadata <li>What licensing and copyright tools are being employed to create Open Data, and how widespread is this adoption <li>How is the field being defined so as to create private and federal grant funding of Linked Open Data projects and initiatives in both the sciences and humanities <li>What use cases are being developed to demonstrate the importance and potential of Linked Open Data across libraries, archives, and museums</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3809 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-3809 http://purl.org/dc/elements/1.1/title The State of Linked Open Data in Libraries, Archives, and Museums
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http://data.semanticuniverse.com/resource/semtech-2011-3809 http://www.w3.org/2000/01/rdf-schema#label The State of Linked Open Data in Libraries, Archives, and Museums
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http://data.semanticuniverse.com/resource/semtech-2011-3809 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jon-voss
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http://data.semanticuniverse.com/resource/semtech-2011-3809 http://purl.org/dc/elements/1.1/abstract Highlights of proceedings from the first international Linked Open Data in Libraries, Archives, and Museum Summit.
http://data.semanticuniverse.com/resource/semtech-2011-3809 http://swrc.ontoware.org/ontology#keywords archives
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http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords systemic-risk
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords credit
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/title Semantics for Risk Analysis ? From Individual Portfolios to Entire Markets
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/adam-greissman
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http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords trading
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords financial
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http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/description <h4>PART I (30 minutes) | What Color is Your Portfolio?</h4> <P> This presentation answers the question, ?How can the Semantic Web be used to reduce systemic risk in capital markets?? <P> This presentation demonstrates that it is possible to associate portfolio risk sensitivity to real time news events. In this case a model portfolio is used to extract parametric model input including issuers, counterparties, currencies, credit and interest rate curves. These sensitivities are related to a semantic network model ? a self-organizing map that related topical information to financial impact. The end result is an iPad based dashboard of green-yellow-red news events that are linked to a graphical display of trend analysis. <P> 1. Extract position information from a model portfolio using issuers, countries, currencies, rates and counterparties 2. Link that information to a semantic network model that can grade news events by positive and negative impact 3. Construct an iPad based application that will allow the user to view news events graded by importance (green, yellow, red) 4. Link to graphs showing trends in market data, news events, market sentiment, etc. <P> Background: Financial derivative instruments have been at the center of the news ever since the collapse of the global credit markets in 2008. These products include credit and interest rate derivatives such as Credit Default Swaps (CDS) and Collateralized Debt Obligations (CDOs). They have complex risk sensitivities that include financial exposure to default events, credit spreads, currency and interest rate movements, etc. However the defining characteristic of the emerging markets is secondary exposure to political upheaval, corruption and acts of war or terrorism. <P> <hr width="10%" /> <P> <P> <h4>PART II (30 minutes) | Avoiding the Next Financial Crisis: Applying Semantic Technology to Access Systemic Risk in Capital Markets</h4> <P> Systemic risk was at the heart of the financial crisis of 2008, and Enterprise Data Management, particularly of reference data - the instruments, counterparties and other building blocks of trading transactions - is essential to getting a handle on risks that go beyond the individual trading desk. Current regulatory and industry efforts are therefore focusing on proper management of reference data to provide more accurate view of risk exposures across asset classes and across lines of business and firms. <P> This session will examine how semantic technologies can provide financial firms and regulators with efficient reference data management that enables comprehensive and timely risk analysis across the board, Case studies and examples will be discussed. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords counterparty
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords real-time
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords middleware
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/james-zucker
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://www.w3.org/2000/01/rdf-schema#label Semantics for Risk Analysis ? From Individual Portfolios to Entire Markets
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://swrc.ontoware.org/ontology#keywords portfolio
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/amir-halfon
http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/abstract Two approaches to using semantic technologies for risk assessment in the financial services industry. One at a portfolio level, the other at a system-wide level.
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http://data.semanticuniverse.com/resource/semtech-2011-3870 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/warren-buckley
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http://data.semanticuniverse.com/resource/yefim-(jeff)-zhuk http://www.w3.org/2001/vcard-rdf/3.0#org Sallie Mae
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http://data.semanticuniverse.com/resource/semtech-2011-marketing-and-advertising http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#TrackEvent
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http://data.semanticuniverse.com/resource/jeffrey-s-grethe http://www.w3.org/2000/01/rdf-schema#label Jeffrey S Grethe
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http://data.semanticuniverse.com/resource/jeffrey-s-grethe http://www.w3.org/2001/vcard-rdf/3.0#title Associate Director
http://data.semanticuniverse.com/resource/jeffrey-s-grethe http://www.w3.org/2001/vcard-rdf/3.0#org Center for Research in Biological Systems, UCSD
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http://data.semanticuniverse.com/resource/semtech-2011-3840 http://www.w3.org/2000/01/rdf-schema#label SemTech 201: Taming the Open World
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://swrc.ontoware.org/ontology#keywords open-world
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://swrc.ontoware.org/ontology#keywords semantic-technology
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://swrc.ontoware.org/ontology#keywords software-development
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://swrc.ontoware.org/ontology#keywords owl
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://purl.org/dc/elements/1.1/description In the OWL language, information is modeled with an implicit open-world assumption (OWA), in which everything is assumed to be possible unless it is proven false by the data. The OWA has traditionally been presented as an obstacle to be overcome, but in fact it is a powerful tool that sets OWL apart from other data-modeling paradigms. Making use of it, however, requires that we change the way we think about how information is represented. <P> The ability to usefully ask what might be true has many potential applications, but modeling in an open-world has many pitfalls for the unwary. This talk will cover: <ul><li>How to prevent the OWL reasoner from believing 'satisfiable nonsense' by selectively closing the world where appropriate <li>How to explicitly model that which is known not to be true <li>Practical applications for ontologies modeled to take full advantage of the open-world assumption</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://purl.org/dc/elements/1.1/title SemTech 201: Taming the Open World
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3840 http://purl.org/dc/elements/1.1/abstract Learn tips and techniques for modeling data in the context of an open-world assumption. Learn how to create OWL ontologies that provide useful satisfiable inference.
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http://data.semanticuniverse.com/resource/semtech-2011-3840 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/tim-swanson
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http://data.semanticuniverse.com/resource/edward-swing http://www.w3.org/2001/vcard-rdf/3.0#org Vision Systems & Technology, Inc./SAS
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http://data.semanticuniverse.com/resource/semtech-2011-4153 http://purl.org/dc/elements/1.1/abstract .
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http://data.semanticuniverse.com/resource/semtech-2011-4153 http://purl.org/dc/elements/1.1/title Creating, Publishing and Consuming Linked Data
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http://data.semanticuniverse.com/resource/semtech-2011-4153 http://purl.org/dc/elements/1.1/description Linked Data refers to a set of best practices for publishing and linking structured data on the Web. By publishing data on the web as Linked Data, the web appears as a giant global database. In this tutorial, we will cover: <P> <li>historical overview of Linked Data <li>introduction to key technologies (URIs, HTTP, RDF, SPARQL) <li>how to create linked data <li>how to publish linked data on the web <li>how to consume linked data <li>linked data applications <P> The intended audience is expected to have basic knowledge about the web. <P>
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http://data.semanticuniverse.com/resource/said-tabet http://www.w3.org/2001/vcard-rdf/3.0#org Inferware Corp.
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http://data.semanticuniverse.com/resource/semtech-2011-3906 http://swrc.ontoware.org/ontology#keywords rdfa
http://data.semanticuniverse.com/resource/semtech-2011-3906 http://purl.org/dc/elements/1.1/description The FAO Country Profiles portal was launched in 2002 to offer decision-makers a fast and reliable way to access FAO's country-specific information produced by the Organization on the areas of Food and Agriculture from a single entry point, without the need to search individual databases and systems. Since then, the portal's knowledge base has been growing incorporating more and more FAO data sources thanks to the extensive use of international standards and the geopolitical ontology. <P> Now, the Linked Open Data cloud allows organizations like FAO going beyond just publishing and re-packaging its own information, to dramatically extend and complement the information provided to decision-makers by selecting and integrating resources from the LOD's large and interoperable information base. <P> This presentation describes how users benefit from a LOD approach in the FAO Country Profiles and in particular it focuses on how the system: <ul><li>Exploits the LOD resources within the portal to provide enhanced country profiles in the area of Food and Agriculture. <li>Contributes to the LOD cloud with an RDF version of FAO's master reference data used to manage country-based information, and other key resources. <li>Exposes FAO Country Profiles data in RDFa to improve search and reuse.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3906 http://purl.org/dc/elements/1.1/abstract This presentation describes how the FAO Country Profiles portal publishes FAO's country-based information on the LOD world, and how it integrates other LOD resources to provide enhanced country profiles in the areas of Food and Agriculture.
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http://data.semanticuniverse.com/resource/semtech-2011-3906 http://purl.org/dc/elements/1.1/title Linked Open Data for the Food and Agriculture Country Profiles
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http://data.semanticuniverse.com/resource/semtech-2011-4038 http://purl.org/dc/elements/1.1/title Rich Snippets
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http://data.semanticuniverse.com/resource/semtech-2011-4038 http://purl.org/dc/elements/1.1/description A discussion of Google's Rich Snippets and the growing use of structured data in Google search results. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4038 http://purl.org/dc/elements/1.1/abstract A discussion of Google's Rich Snippets and the growing use of structured data in Google search results.
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http://data.semanticuniverse.com/resource/semtech-2011-3882 http://purl.org/dc/elements/1.1/title Panel: Serious Semantics, Serious Ontologies
http://data.semanticuniverse.com/resource/semtech-2011-3882 http://purl.org/dc/elements/1.1/description Panel: Serious Semantics, Serious Ontologies <P> Chairman: Ken Orr, Chief Scientist, The Ken Orr Institute John Sowa, Independent Consultant David Hay, President, Essential Strategies, Inc. Tom Velez, Chairman and Founder, CTA <P>
http://data.semanticuniverse.com/resource/semtech-2011-3882 http://swrc.ontoware.org/ontology#keywords semantic-based-applications
http://data.semanticuniverse.com/resource/semtech-2011-3882 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3882 http://purl.org/dc/elements/1.1/abstract This panel addresses the different between "naive" and "serious" semantics and ontologies and what they and their colleagues have been learning about developing advanced semantic-based products and theories . The panelists include 4 leading researchers in semantics, ontologies, automatic database design and AI.
http://data.semanticuniverse.com/resource/semtech-2011-3882 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dave-hay
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http://data.semanticuniverse.com/resource/yijing-(jenna)-zhou http://www.w3.org/2001/vcard-rdf/3.0#org DELL Inc.
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http://data.semanticuniverse.com/resource/semtech-2011-3978 http://swrc.ontoware.org/ontology#keywords ontologies
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http://data.semanticuniverse.com/resource/semtech-2011-3978 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2011-3978 http://www.w3.org/2000/01/rdf-schema#label OWLGrEd - A Compact UML Style Editor for OWL 2.0
http://data.semanticuniverse.com/resource/semtech-2011-3978 http://purl.org/dc/elements/1.1/description We present OWLGrEd - a compact OWL ontology editor that is based on combining extended UML class diagram notation and textual OWL Manchester syntax. During the presentation we demonstrate the use of OWLGrEd in creating, visualizing and editing OWL ontologies. There are two main scenarios of OWLGrEd use: 1. Visualization of imported OWL 2.0 ontology; the ontology needs to be loaded into Protege 4.1 tool first and then exported to OWLGrEd using OWLGrEd Protege plugin; the visual ontology layout is created automatically; the ontology is then open for editing in OWLGrEd (this includes both visual presentation and layout, as well as ontology contents editing; the ontology can later be exported back to Protege). 2. Development of new OWL ontology in OWLGrEd using its advanced graphical notation; the interoperability with Protege is used for checking the ontology consistency, as well as exporting it to different formats. We explain briefly also the open architecture principles and extensibility of the OWLGrEd editor. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3978 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/karlis-cerans
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http://data.semanticuniverse.com/resource/semtech-2011-3978 http://purl.org/dc/elements/1.1/abstract We present a compact graphical notation for OWL 2.0 and its implementation in OWLGrEd editor, based on combination of UML class diagrams and textual OWL Manchester syntax.
http://data.semanticuniverse.com/resource/semtech-2011-3978 http://purl.org/dc/elements/1.1/title OWLGrEd - A Compact UML Style Editor for OWL 2.0
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http://data.semanticuniverse.com/resource/semtech-2011-3948 http://www.w3.org/2000/01/rdf-schema#label Translating Business Vocabulary and Rules to the Semantic Web
http://data.semanticuniverse.com/resource/semtech-2011-3948 http://purl.org/dc/elements/1.1/abstract Discussion and demonstration of a framework for using Semantic Web tools and technologies to encode business vocabularies and rules
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http://data.semanticuniverse.com/resource/semtech-2011-3948 http://purl.org/dc/elements/1.1/title Translating Business Vocabulary and Rules to the Semantic Web
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http://data.semanticuniverse.com/resource/semtech-2011-3948 http://purl.org/dc/elements/1.1/description This session is a demonstration and discussion of various natural language and Semantic Web tools and technologies. There are four areas of focus for the talk. The first is an overview of the problem domain - the need to move from natural language definitions of business vocabularies and rules, to machine-processable encodings (that can be analyzed for correctness, consistency and completeness). The second part of the session demonstrates this capability using freely available Semantic Web tooling, integrated with Microsoft Word document processing and business-user-friendly conventions. The third section addresses the conversion of the natural language vocabularies and rules to a machine-readable encoding, based on OWL and SWRL. Then, in the conclusion, future work on ontology alignment for vocabulary and policy integration is discussed. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4135 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
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http://data.semanticuniverse.com/resource/semtech-2011-4135 http://purl.org/dc/elements/1.1/title Dynamic Semantic Publishing
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http://data.semanticuniverse.com/resource/semtech-2011-4135 http://www.w3.org/2000/01/rdf-schema#label Dynamic Semantic Publishing
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http://data.semanticuniverse.com/resource/semtech-2011-4135 http://purl.org/dc/elements/1.1/description A talk describing the transformational technology strategy the BBC Future Media & Technology department is using to evolve from a relational content model and static publishing framework to a fully dynamic semantic publishing (DSP) architecture. This approach uses linked data technology to automate the aggregation, publishing and re-purposing of interrelated content objects according to an ontological domain-modelled information architecture. Providing a greatly improved user experience and high levels of user engagement. The DSP architecture curates and publishes HTML and RDF aggregations based on embedded Linked Data identifiers, ontologies and associated inference. RDF semantics improve navigation, content re-use, re-purposing, search engine rankings, journalist determined levels of automation (?edited by exception?) and support semantic advertisement placement for audiences outside of the UK. The DSP approach facilitates multi-dimensional entry points and a richer navigation, greatly improving user experience and levels of engagement. This strategy was used to deliver the BBC World Cup 2010 architecture, and Is currently being used to deliver a significant percentage of the BBC Sport site. Future plans Include delivering the BBC Olympics 2012 online coverage. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3918 http://purl.org/dc/elements/1.1/title Searching the Web-of-Things
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http://data.semanticuniverse.com/resource/semtech-2011-3918 http://purl.org/dc/elements/1.1/abstract This presentation highlights the importance of putting semantics for objects from the real-world (e.g. TV, alarm-clock) that have been offered to third parties through Web services (e.g. REST)
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http://data.semanticuniverse.com/resource/semtech-2011-3918 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/benoit-christophe
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http://data.semanticuniverse.com/resource/semtech-2011-3918 http://purl.org/dc/elements/1.1/description With the decrease of hardware production costs, putting connection capabilities to appliances has become affordable. At the same time, the widespread acceptance of the web has gained on Internet users. At the convergence of these two facts, the idea of a ?Web of Things? has emerged; unleashing the current Internet of Things solutions by exposing connected objects as Web resources, paving the way to novel Web Applications. While quite promising ? now appliances are able to interoperate whatever their hardware or Operating Systems, using Web protocols stack ? this vision still needs practical mechanisms to allow users and even machines to search and interact with connected objects. Some initiatives attempted to realize such a vision by making use of the classical "Service Oriented Computing" paradigm. Although their prototypes prove that the approach was realizable, none of them paid sufficient attention to the importance of a highly capable discovery of objects for both machines and end users, taking into account specific facets of objects such as ownership or location through semantics. The presentation will cover the following: <ul><li>An architecture of models to build a semantic Web of Things <li>Transforming a "Physical object" into a "Virtual object" using semantics <li>Deployment of a semantically described object into a "smart place" and navigation between smart places using ontological properties <li>Strategies using semantics to discover objects and to combine them with others <li>Limitations of current semantic engines and strategies to adopt</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3894 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3894 http://swrc.ontoware.org/ontology#keywords text-mining
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http://data.semanticuniverse.com/resource/semtech-2011-3894 http://www.w3.org/2000/01/rdf-schema#label Semantic Search and Discovery as a Powerful Business Tool in Pharmaceutical Product Development
http://data.semanticuniverse.com/resource/semtech-2011-3894 http://purl.org/dc/elements/1.1/description When testing for drug safety, the FDA analyzes the observed interactions of the drug in question and compares it to that of other drugs. Because test records are often in the form of written sentences, rather than data in tables, the critical interaction information contained within them is not easily extracted. Text mining is the key to unlocking important information within records without resorting to an army of readers, recorders or translators. <P> Without the efficiency of this text mining approach, FDA researchers and managers may explore many useless dead-ends. Worse, they may miss unforeseen outcomes of drug-drug interactions altogether until they show up more prominently in the population after many years of use. The health risks, not to mention the liability and negative publicity costs, are unacceptable to drug companies. <P> The use of Semantic Search and Analytical Text Mining to find cause and effect is not limited to safety concerns. Using the same methods to model preparatory steps among competitors leads to: <P> - New insight into strategic or product direction. <P> - Real time innovation monitoring. Applying the technique to public patent information is a form of Technology Sequence Analysis revealing the technology basis for future developments. <P> - A higher standard for new State or Federal regulatory policies. Investigative concentrations tell us where standards bodies might be several quarters from now. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3894 http://purl.org/dc/elements/1.1/title Semantic Search and Discovery as a Powerful Business Tool in Pharmaceutical Product Development
http://data.semanticuniverse.com/resource/semtech-2011-3894 http://swrc.ontoware.org/ontology#keywords drug-safety
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http://data.semanticuniverse.com/resource/semtech-2011-3894 http://purl.org/dc/elements/1.1/abstract In this presentation, we will show how text mining can radically reduce the time and cost of ensuring drug safety.
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http://data.semanticuniverse.com/resource/semtech-2011-3864 http://purl.org/dc/elements/1.1/abstract The convergence of telecommunications, media and entertainment present unprecedented challenges and opportunities for both consumers and providers. This presentation explores an effort to leverage semantic technology and ontologies to build applications and integrate applications that respond to and support this convergence.
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http://data.semanticuniverse.com/resource/semtech-2011-3864 http://swrc.ontoware.org/ontology#keywords media
http://data.semanticuniverse.com/resource/semtech-2011-3864 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3864 http://purl.org/dc/elements/1.1/title Semantic Technology and the Convergence of Telecommunications, Entertainment, and Media
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http://data.semanticuniverse.com/resource/semtech-2011-3864 http://purl.org/dc/elements/1.1/description The convergence of telecommunications, media and entertainment present unprecedented challenges and opportunities for both consumers and providers. New ways of building and integrating applications will be required to adapt and thrive in this rapidly changing landscape. Semantic technology provides a foundation for the flexible representation of the underlying information model that these new applications will require. <P> Several major information models have grown and matured over the last decade, including the TM Forum Information Framework (SID) and the Distributed Management Task Force (DMTF) Common Information Model (CIM). As verticals converge (e.g. communications, media, entertainment) and concepts are absorbed across many verticals (e.g. ITIL), it is increasingly important to be able to bridge large, disparate, overlapping information models. <P> This presentation explores recent work by members of the TM Forum and the DMTF in forming ontologies that correspond to the SID and CIM. We will: </ul><li>Review the available techniques <li>Evaluate the relative effort and value of several approaches <li>Recommend next steps to leverage semantic technology to build and integrate applications that will respond and support this vertical convergence</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3864 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/fran-clark
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http://data.semanticuniverse.com/resource/semtech-2011-3779 http://www.w3.org/2000/01/rdf-schema#label InSciTe: Technology Intelligence Service in R&D
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http://data.semanticuniverse.com/resource/semtech-2011-3779 http://purl.org/dc/elements/1.1/title InSciTe: Technology Intelligence Service in R&D
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http://data.semanticuniverse.com/resource/semtech-2011-3779 http://purl.org/dc/elements/1.1/abstract To show an technology intelligence service for supporting R&D strategy planning Contents: information service trends, Semantic Web-based service platform, related technology intelligence projects, development of InSciTe service
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http://data.semanticuniverse.com/resource/semtech-2011-3779 http://purl.org/dc/elements/1.1/description This presentation describes how to improve research productivity of researchers as well as to support systematic research and development using InSciTe as a technology intelligence service, which aims to support decision-making processes, especially in establishing R&D strategy. It has been implemented by combining Semantic Web and text mining technologies, analyzes relations among technologies, research agents and research outcomes and provides killer services in the viewpoints of discovery, combination and comparison. Comparison with existing analytic tools will be presented. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4021 http://purl.org/dc/elements/1.1/title SIREn: A Solr Extention for Enterprise Semantic Search
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http://data.semanticuniverse.com/resource/semtech-2011-4021 http://www.w3.org/2000/01/rdf-schema#label SIREn: A Solr Extention for Enterprise Semantic Search
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http://data.semanticuniverse.com/resource/semtech-2011-4021 http://purl.org/dc/elements/1.1/abstract In this presentation we will introduce and demonstrate SIREn, an Open Source project which leverages the power of the Apache Solr for enterprise semantic search.
http://data.semanticuniverse.com/resource/semtech-2011-4021 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-4021 http://purl.org/dc/elements/1.1/description The open-source search server Apache Solr is today powering countless businesses and enterprises in their document search needs. While Solr can provide search also on semantically structured documents, its out of the box capabilities and scalabilty in this task are limited.  In this presentation we will introduce and demonstrate the Open Source SIREn Semantic Information Retrieval Solr Plugin. With SIREn it becomes possible to search across millions of highly and diversely structured records having possibly millions of different attributes. As such SIREn can be used as an enterprise grade backbone to cover high scalability Semantic Information Retrieval scenarios. <P> The following aspects will be discussed: <ul><li>Issues with Apache Solr for indexing RDF data <li>Overview of SIREn <li>Integrating SIREn within Solr <li>SIREn Query Parser <li>Building Custom Semantic Search Applications <li>Leveraging Solr: Replication and Distributed Search <li>A case study: loading and quering over 150 millions of highly diverse semantic documents</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3991 http://purl.org/dc/elements/1.1/abstract This presentation describes a framework and ontology for cached RDF data production pipelines based on RESTful HTTP and SPARQL. Incremental data changes automatically ripple through the pipelines to consuming applications.
http://data.semanticuniverse.com/resource/semtech-2011-3991 http://www.w3.org/2000/01/rdf-schema#label RDF Data Pipelines for Semantic Data Federation
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http://data.semanticuniverse.com/resource/semtech-2011-3991 http://purl.org/dc/elements/1.1/description Experience in applying semantic web technology to clinical health care research has revealed the need for a more consistent approach to RDF data production. <P> Data originating in diverse clinical systems, formats and data models typically must be transformed to hub ontologies, merged, inferenced, selected and finally transformed to consuming applications' ontologies and data formats for productive use. The process is quite repetitive: similar transformations are often performed each day, week or month with only slight variations to the data windows and queries. Ad hoc data production scripts can be created to help automate this process, but they tend to be fragile, inefficient, difficult to maintain and hard to visualize. <P> This presentation describes a simple framework and ontology for cached RDF data production pipelines, based on RESTful HTTP and SPARQL. These pipelines are easily visualized, and incremental data changes automatically propagate through to consuming applications. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3991 http://purl.org/dc/elements/1.1/title RDF Data Pipelines for Semantic Data Federation
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http://data.semanticuniverse.com/resource/semtech-2011-3804 http://purl.org/dc/elements/1.1/abstract This presentation features NASA Johnson Space Center?s use of semantic technology, lessons learned, and information practices used to harness over 50 years of manned space flight research.
http://data.semanticuniverse.com/resource/semtech-2011-3804 http://swrc.ontoware.org/ontology#keywords semantic-systems-&-tools
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http://data.semanticuniverse.com/resource/semtech-2011-3804 http://purl.org/dc/elements/1.1/description NASA Johnson Space Center (JSC), utilizes semantic systems to capitalize on the research, development and accomplishments of yesterday while maintaining the flexibility needed for the evolving information environment of today. The challenges of building an infrastructure that accurately represents over 50 years of manned space flight are as varied as the multiple domains it envelopes. Semantics help define a roadmap for the future and return value for the investment in information management, which cannot be accomplished with traditional systems alone. <P> The integration of semantic technology and information architecture brings significant opportunities for success for the organization as well as its information workers. Sarah Berndt, JSC Taxonomist, and Jeremy Bentley, CEO of Smartlogic, present educational and relevant lessons learned throughout the project; including Smartlogic?s Semaphore Enterprise Semantic Platform used at JSC to compliment the Google Search Appliance. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3804 http://swrc.ontoware.org/ontology#keywords text-analysis
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http://data.semanticuniverse.com/resource/semtech-2011-3804 http://purl.org/dc/elements/1.1/title NASA Johnson Space Center, Enterprise Semantics and Tales of the Unexpected
http://data.semanticuniverse.com/resource/semtech-2011-3804 http://purl.org/dc/elements/1.1/audience Case Study
http://data.semanticuniverse.com/resource/semtech-2011-3804 http://www.w3.org/2000/01/rdf-schema#label NASA Johnson Space Center, Enterprise Semantics and Tales of the Unexpected
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http://data.semanticuniverse.com/resource/gary-l-katz http://www.w3.org/2001/vcard-rdf/3.0#org Mark Logic Corporation
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http://data.semanticuniverse.com/resource/kathleen-dahlgren http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/kathleen-dahlgren http://www.w3.org/2000/01/rdf-schema#label Kathleen Dahlgren
http://data.semanticuniverse.com/resource/kathleen-dahlgren http://xmlns.com/foaf/0.1/name Kathleen Dahlgren
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http://data.semanticuniverse.com/resource/kathleen-dahlgren http://www.w3.org/2001/vcard-rdf/3.0#title CTO
http://data.semanticuniverse.com/resource/kathleen-dahlgren http://www.w3.org/2001/vcard-rdf/3.0#org Cognition Technologies, Inc.
http://data.semanticuniverse.com/resource/semtech-2011-3780 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T07:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-3780 http://purl.org/dc/elements/1.1/description Programmers know that a set of simple command-line tools can be very useful for rapid prototyping tasks. If each small tool does one thing well, these tools can be piped together in novel ways to accomplish tasks that would otherwise require more lengthy programming. <P> The Jena Semantic Web Framework includes a set of command line utilities. In this session we show how to use the Jena Command Line Utilities for: <ul><li>Transforming RDF files between various formats (RDF/XML, Turtle/N3, N-Triples) <li>Merging multiple RDF files <li>Issuing SPARQL queries against RDF Files <li>Filtering triples</ul> In addition, we show how to create and use the one tool that seems to be missing: a command line reasoner tool. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3780 http://purl.org/dc/elements/1.1/abstract A tutorial on using the Jena Command Line Utilities for rapid prototyping of RDF and OWL ontologies. Includes RDF format conversion, file merging, SPARQL query, triple filtering, and reasoning.
http://data.semanticuniverse.com/resource/semtech-2011-3780 http://purl.org/dc/elements/1.1/title Rapid Prototyping with the Jena Command Line Utilities
http://data.semanticuniverse.com/resource/semtech-2011-3780 http://www.w3.org/2000/01/rdf-schema#label Rapid Prototyping with the Jena Command Line Utilities
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http://data.semanticuniverse.com/resource/cognition-technologies-inc http://xmlns.com/foaf/0.1/name Cognition Technologies, Inc.
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http://data.semanticuniverse.com/resource/semtech-2011-3876 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://swrc.ontoware.org/ontology#keywords xml
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://purl.org/dc/elements/1.1/description Chances are good that XQuery is currently not on your radar. Chances are better that by 2012 it will be. XQuery based data systems are emerging not only as ways of storing XML content, but are increasingly full featured web application development environments capable of interfacing not only with XML content but also email systems, JSON, LDAP and SQL databases, and are also providing bridges and nodes for developing rich forms and data interaction systems. This talk focuses on the state of the XQuery sector, showcases ways where XQuery can help build traditional and semantically enhanced applications, looks at the business case for XQuery and discusses improvements in the language that will expand its potential and appeal. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T11:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://swrc.ontoware.org/ontology#keywords w3c
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://swrc.ontoware.org/ontology#keywords json
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http://data.semanticuniverse.com/resource/semtech-2011-3876 http://purl.org/dc/elements/1.1/title Why XQuery Will Be In Your Business
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://swrc.ontoware.org/ontology#keywords xquery
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://www.w3.org/2000/01/rdf-schema#label Why XQuery Will Be In Your Business
http://data.semanticuniverse.com/resource/semtech-2011-3876 http://purl.org/dc/elements/1.1/abstract Completed in 2007, XQuery has been quietly gaining momentum, but is already beginning to explode into Enterprise usage. This talk focuses on the business case for XQuery, and what's in store for XQuery 3.0.
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http://data.semanticuniverse.com/resource/semtech-2011-3876 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/kurt-cagle
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http://data.semanticuniverse.com/resource/semtech-2011-3846 http://purl.org/dc/elements/1.1/description The demonstration will show how to use the tool to graphically author and test an ontology in Visio 2007 amd then serialize it as XML/RDF. The tool is intended to be used in combination with other ontology editors such as Protege or Top Braid. The poster presentation will include examples of large-scale enterprise ontologies developed with the tool, and the diagramming conventions it uses. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://purl.org/dc/elements/1.1/title Graphically Authoring OWL Ontologies in Visio
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-semantic-software-development
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://www.w3.org/2000/01/rdf-schema#label Graphically Authoring OWL Ontologies in Visio
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#ConferenceEvent
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T10:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-3846 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/simon-robe
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://purl.org/dc/elements/1.1/abstract Demonstration of a Microsoft Visio-based addin for graphically authoring OWL 2 ontologies.
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T03:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3846 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2011-3846 http://swrc.ontoware.org/ontology#keywords owl-visio-ontology-authoring-visualization-editor
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ulrich-reimer
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/dc/elements/1.1/description The paper introduces a web-based eHealth platform currently being developed that will assist patients with certain chronic diseases. The ultimate aim is behavioral change. This is supported by online assessment and feedback which visualizes actual behavior in relation to target behavior. Disease specific information is provided through an information portal that utilizes lightweight ontologies (associative networks) in combination with text mining. The paper argues that classical word-based information retrieval is often not sufficient for providing patients with relevant information, but that their information needs are better addressed by concept-based retrieval. The focus of the paper is on the semantic retrieval component and the learning of a lightweight ontology from text documents, which is achieved by using a biologically inspired neural network. The paper concludes with preliminary results of the evaluation of our approach in comparison with traditional approaches. This presentation will be relevant to those developing or maintaining semantic applications requiring ontologies. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-09T00:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/dc/elements/1.1/abstract Learning a Lightweight Ontology for Semantic Retrieval in Patient-Centered Information Systems
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://swrc.ontoware.org/ontology#keywords ehealth
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
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http://data.semanticuniverse.com/resource/semtech-2011-3931 http://swrc.ontoware.org/ontology#keywords ontology
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http://data.semanticuniverse.com/resource/semtech-2011-3931 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://purl.org/dc/elements/1.1/title EHealth: How Semantic Retrieval Benefits Patients
http://data.semanticuniverse.com/resource/semtech-2011-3931 http://www.w3.org/2000/01/rdf-schema#label EHealth: How Semantic Retrieval Benefits Patients
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http://data.semanticuniverse.com/resource/thomas-valez http://xmlns.com/foaf/0.1/name Thomas Valez
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http://data.semanticuniverse.com/resource/thomas-valez http://www.w3.org/2001/vcard-rdf/3.0#org CTA Inc.
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://purl.org/dc/elements/1.1/abstract The talk will demonstrate the NoTube platform and showcase three NoTube example scenarios: personalised semantic news (with our partner RAI), personalised TV guide with adaptive advertising (with our partner Stoneroos) and Internet TV in the Social Web (with our partner BBC).
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://purl.org/dc/elements/1.1/title NoTube: Using the Synergy of Broadcast, Internet and Social TV
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://www.w3.org/2000/01/rdf-schema#label NoTube: Using the Synergy of Broadcast, Internet and Social TV
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://swrc.ontoware.org/ontology#keywords personalised-media
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://swrc.ontoware.org/ontology#keywords semantic-tv
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/lora-aroyo
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://purl.org/dc/elements/1.1/description In 2011 we expect to see a major push on Internet TV as well as hybrid broadcast/broadband TV. The introduction of Internet capabilities to Television has so much more potential than just seeing Web pages on TV or having on screen widgets connecting to Web content. Emerging Web trends such as the social Web and the semantic Web can enable new and exciting types of service for Television based on knowing the viewer and the content, and linking this to what the viewer does and who the viewer knows elsewhere on the Web. <P> This talk will describe the activities and expected results of NoTube, a European project exploring television's future in the ubiquitous Web. NoTube is developing a platform which will use a service oriented architecture to integrate already existing functionalities such as EPG as well as advanced functionalities such as broadcaster metadata mediation, TV and multimedia content adaptation, various delivery mechanisms, semantic user profiling and recommendation. This service oriented platform, based on the hybrid broadcast/broadband TV provides the viewer in addition to program recommendations, personalised EPG and advertising with personalized multimedia programmes and social TV (bookmarking and sharing TV programs with one?s friends). <P>
http://data.semanticuniverse.com/resource/semtech-2011-4063 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2011-4063 http://swrc.ontoware.org/ontology#keywords tv-web-convergence
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http://data.semanticuniverse.com/resource/semtech-2011-4063 http://swrc.ontoware.org/ontology#keywords social-tv
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http://data.semanticuniverse.com/resource/semtech-2011-4063 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T10:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/ron-daniel http://xmlns.com/foaf/0.1/name Ron Daniel
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http://data.semanticuniverse.com/resource/semtech-2011-3901 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-3901 http://purl.org/dc/elements/1.1/title Global Counterparty Risk and Exposure - A Semantic Solution
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http://data.semanticuniverse.com/resource/semtech-2011-3901 http://purl.org/dc/elements/1.1/abstract One of the most significant problems facing the financial services industry today is counterparty risk and exposure. Semantic Technologies provide the most efficient, timely, comprehensive, and cost effective solution to this dilemma.
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http://data.semanticuniverse.com/resource/semtech-2011-3901 http://purl.org/dc/elements/1.1/description One of the most significant problems facing the financial services industry today is counterparty risk and exposure. To illustrate: when the Madoff ponzi scheme became known, it took most large financial firms 3 to 4 weeks to determine what they had at risk, information that should be instantly available. It is impossible to manage risk of any kind if you don't know what that risk entails. Counterparty risk and exposure consists of three components: <ul><li>Determination of Exposure: for most firms this entails accessing and aggregating data from multiple silos. The issue is further compounded by the addition of silos from subsidiaries and affiliates. A large financial services firm can be faced with the integration of data from over 50 sources. <li>Counterparty Identification: this requires the ability to link issues to issuers, issuers to their parent companies, and parent companies to their ultimate parent companies. <li>Monitoring of Risk: What is risk and how is it defined? The answer is it does not have a universal definition. Risk and its definition vary from investment manager to investment manager. The models and theories that drive the various investment strategies inherently contain risk interpretation as perceived by a specific manager, firm or model. An investment manager assesses risk at the time of the investment decision based on a wealth of information derived from many sources and generally consolidated in a Bloomberg or Thompson type of product. A given manager is generally managing only a handful of securities at any point in time. Counterparty risk requires the same wealth of information, not for a handful of positions but for millions of positions, not at a point in time, but rather over time. </ul> <P> This presentation will discuss each of these components, how they are currently handled, and how semantic technologies can solve the problem. Actual applications already developed will be presented for the problem as a whole and for individual components or sub-components that prove particularly problematic. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3901 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-4033 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-4033 http://purl.org/dc/elements/1.1/abstract This talk will provide a quick introduction to current activities at the Object Management Group related to semantic technologies. It is intended to bring folks up to date on what we are doing, and encourage participation.
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http://data.semanticuniverse.com/resource/semtech-2011-4033 http://purl.org/dc/elements/1.1/description The Ontology Platform Special Interest Group (PSIG) at the Object Management Group (OMG) is an active and growing community developing specifications that marry semantic technologies with well-known standards for software and systems engineering as well as business process modeling and management. The first standard developed by this group, the Ontology Definition Metamodel (ODM), was published several years ago and is currently undergoing revision to support OWL 2. In addition to ODM maintenance, a number of new initiatives are in work or just getting underway. These include a new standard for application programming interfaces (APIs) for knowledge base accessibility, ontologies for policy specification to support interoperability, ontologies for business terminology, and domain-specific standards such Common Terminology Services for healthcare. <P> This short talk is intended to: - Introduce the Ontology PSIG and OMG to potential members - Bring attendees up to date on current and planned activities - Solicit input for the Ontology PSIG roadmap - Encourage attendees to consider participation <P>
http://data.semanticuniverse.com/resource/semtech-2011-4033 http://swrc.ontoware.org/ontology#keywords bpmn
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http://data.semanticuniverse.com/resource/semtech-2011-4033 http://www.w3.org/2000/01/rdf-schema#label OMG Ontology PSIG: An Invitation to Participate
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http://data.semanticuniverse.com/resource/semtech-2011-4033 http://purl.org/dc/elements/1.1/title OMG Ontology PSIG: An Invitation to Participate
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http://data.semanticuniverse.com/resource/semtech-2011-4129 http://www.w3.org/2000/01/rdf-schema#label Recollection: A Linked Data Platform of America's Memory
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http://data.semanticuniverse.com/resource/semtech-2011-4129 http://purl.org/dc/elements/1.1/title Recollection: A Linked Data Platform of America's Memory
http://data.semanticuniverse.com/resource/semtech-2011-4129 http://purl.org/dc/elements/1.1/description The mission of the National Digital Information Infrastructure and Preservation Program (NDIIPP) is to develop a national strategy to collect, preserve and make available significant digital content, especially information that is created in digital form only, for current and future generations. In 2008, the NDIIPP partners shared content through a simple web page. In order to explore more useful tools and processes for sharing diverse content across partners' collections, the Library began the Project Recollection Pilot in 2009 with Zepheira to develop a proof of concept that can be used to collect and explore information about digital collections. <P> The Recollection platform has grown beyond its pilot phase and has begun to provide the tools and environment that will enable NDIIPP Partners to showcase their collections and data from a central point. Recollection is a free platform for generating and customizing views, (interactive maps, timelines, facets, tag clouds) that allow users to experience their digital collections. This presentation will discuss the architecture and features of the Recollection platform, highlight work done to date, discuss future directions of this work and gather input from the audience on how to build interest and involvement from the community. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3762 http://swrc.ontoware.org/ontology#keywords r2rml
http://data.semanticuniverse.com/resource/semtech-2011-3762 http://purl.org/dc/elements/1.1/description This tutorial gives an overall view of W3C's Semantic Web technologies. The requested background knowledge is minimal, essentially a proper computer science or programming background. The tutorial would start with a thorough overview of RDF, then touch upon the essential technologies like RDFS, OWL, RIF, RDFa, R2RML, SKOS, etc. <P> It is obviously impossible to learn all technologies in all the details in the course of one tutorial. The goal is that the participants would leave with a good overall understanding on how the different technology pieces fit together, what specific usages they have for which type of applications, etc. Participants should be able to grasp the essential issues for each of technologies, thereby gaining a better understanding of the SemTech presentations overall, and knowing which areas they would have to dig in further for the specific application and/or deployment goals they may have. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3762 http://swrc.ontoware.org/ontology#keywords linked-data
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http://data.semanticuniverse.com/resource/semtech-2011-3762 http://purl.org/dc/elements/1.1/title Introduction to the Semantic Web
http://data.semanticuniverse.com/resource/semtech-2011-3762 http://purl.org/dc/elements/1.1/abstract The aim is to give an overall view of the W3C Semantic Web technologies from bottom up. Requested ackground knowledge is minimal, essentially a proper computer science or programming background.
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http://data.semanticuniverse.com/resource/semtech-2011-3943 http://purl.org/dc/elements/1.1/title Pellet Meets Stardog: Semantic Reasoning and Query for the Enterprise
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http://data.semanticuniverse.com/resource/semtech-2011-3943 http://swrc.ontoware.org/ontology#keywords query-answering
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http://data.semanticuniverse.com/resource/semtech-2011-3943 http://purl.org/dc/elements/1.1/description Enterprise Pellet 3 is a leading OWL 2 reasoner for use in semantic applications where automated reasoning is crucial. Stardog is our new, world-class RDF database featuring fast SPARQL query performance for semantic applications where data integration is crucial. <P> In this talk the two lead developers of Pellet and Stardog talk about the opportunities and challenges that arise from integrating in-memory OWL reasoning with disk-based SPARQL query answering. <P> Some of the subjects to be addressed include: <ul><li>Insanely fast SPARQL query answering with Stardog <li>Unifying the Semweb Stack: OWL-based integrity constraint validation in Stardog <li>Query-time reasoning in Stardog <li>Schema-only reasoning using Enterprise Pellet 3.0's new features <li>Some joys of closed world reasoning <li>Ortiz: one API to bind them all</ul> <P> This talk is for anyone who thinks that OWL and RDF are too slow or not sufficiently scalable to build serious semantic technology applications. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3943 http://www.w3.org/2000/01/rdf-schema#label Pellet Meets Stardog: Semantic Reasoning and Query for the Enterprise
http://data.semanticuniverse.com/resource/semtech-2011-3943 http://purl.org/dc/elements/1.1/abstract Introduce audience to Enterprise Pellet and Stardog, an integrated system for world-class OWL reasoning and RDF query answering.
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http://data.semanticuniverse.com/resource/semtech-2011-3943 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-h-grove
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http://data.semanticuniverse.com/resource/semtech-2011-4075 http://www.w3.org/2000/01/rdf-schema#label Civet - From Content to Linked Open Data
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http://data.semanticuniverse.com/resource/semtech-2011-4075 http://purl.org/dc/elements/1.1/abstract Our new services called Civet is a solution which turns an ordinary text into a RDFa document linked with concepts from vocabularies published as Linked Open Data, such as with our the OpenVocabulary service.
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http://data.semanticuniverse.com/resource/semtech-2011-4075 http://swrc.ontoware.org/ontology#keywords vocabularies
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http://data.semanticuniverse.com/resource/semtech-2011-4075 http://purl.org/dc/elements/1.1/title Civet - From Content to Linked Open Data
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http://data.semanticuniverse.com/resource/semtech-2011-4075 http://purl.org/dc/elements/1.1/description Civet uses NLP techniques to determine the keywords in the provided text. But it does not stop there: it analyzes these words and determines the most appropriate meanings linked to concepts from vocabularies, such as WordNet and Polish version of the OpenThesaurus, both published as RDF/SKOS graphs on Linked Open Data. <P> Civet also discovers names of people and places, and uses other LOD sources, such as DBPedia or GeoNames, to annotate these names with concepts from those vocabularies. <P> The initial plain text becomes an RDFa document with key words, phrases and names referencing Linked Open Data concepts. Civet uses repository of previously analyzed texts to recommend semantically similar texts to the given one. <P> Civet was build to work with Polish texts, but we currently work on the English and Italian version of the service. <P> We plan the presentation as follows: * Discuss the main design objectives of both the annotation and the vocabulary publishing service * Give an overview of the algorithms we use to extract the meaningful concepts from given text * Present how to turn legacy vocabularies into RDF/SKOS graphs. * Discuss various pitfalls one can stumble upon when building such services. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4130 http://purl.org/dc/elements/1.1/title Exhibit3: Publishing Framework for Large Scale Data-Rich Interactive Web Pages
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http://data.semanticuniverse.com/resource/semtech-2011-4130 http://purl.org/dc/elements/1.1/description In January 2011, MIT and Zepheira began work on Exhibit 3.0, a new project funded by the Library of Congress to redevelop the popular Exhibit tool from the MIT Simile Project. Exhibit was originally developed as an ambitious collaboration of the MIT Libraries, the MIT CSAIL, and the World Wide Web Consortium (W3C) to explore applications of the Semantic Web to problems of information management across both large-scale digital libraries and small-scale personal collections. <P> Exhibit runs inside a Web browser and supports many types of information using common Web standards for data publishing. Since its release, Exhibit has been used by thousands of websites worldwide across a range of diverse industries including cultural heritage, libraries, publishers, medical research, life science and government. <P> Exhibit 3.0 will fix many shortcomings of the original Exhibit work, making it far more scalable, modular, and feature rich than the original tool, and the work is being done as broadly inclusive open source software development. This presentation will discuss the new architecture and features, highlight work done to date, demonstrate some of Exhibit 3.0 capabilities and gather input from the audience on how to build interest and involvement from the community in this work. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3913 http://purl.org/dc/elements/1.1/title Realizing the Semantic Web Promise in the Oil and Gas Industry Domain: Challenges and Experiences
http://data.semanticuniverse.com/resource/semtech-2011-3913 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/frank-chum
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http://data.semanticuniverse.com/resource/semtech-2011-3913 http://purl.org/dc/elements/1.1/description The tutorial will be divided into two parts. In the first part, we will focus on the ontology modeling aspects including the advantages and shortcomings of ontology languages, rule frameworks, ontology development tools, and management frameworks in the context of the real-world industrial environment. The second part of the tutorial will focus on emerging application areas. This will include using semantic Web technologies and services computing for data integration, complex metadata management, data provenance, data mining / text analytics, semantic-based knowledge extraction, and social computing in the energy enterprise. <P> 1. Ontology modeling in the oil and gas domain. 2. Advantages and shortcomings of ontology languages 3. Applications of semantic Web to knowledge extraction 4. Examples illustrating the applications of semantic Web techniques. 5. Sharing of the lessons learned. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3913 http://www.w3.org/2000/01/rdf-schema#label Realizing the Semantic Web Promise in the Oil and Gas Industry Domain: Challenges and Experiences
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http://data.semanticuniverse.com/resource/semtech-2011-4045 http://purl.org/dc/elements/1.1/description Semantrix' SM3 ?Social and Multimedia Metadata Manager? delivers enhanced content value through metadata extraction, annotation and cross-referencing using NLP, Search, Ontology and proprietary concept extraction techniques. <P> SM3 is designed to be used standalone or fronting a Digital-Asset Management System (DAMS). SM3 provides enhanced content metadata and delivers search and indexing capabilities beyond typical commercial DAMS?. This enhanced concept cross-referencing facilitates representing and relating concepts in ways not typically available to social networks or asset-management systems. For example, blog references to football-team members are cross-referenced to current news articles and video clips related to that team. <P> The SM3 core supports automated and manual analysis, tagging, cross-referencing and search across a range of content types, using NLP and semantic models of domains to facilitate linking user-generated document and multimedia content. <P> SM3 provides an integrated recommendation model and also supports a pluggable recommendation and search core allowing the integration of third-party services. Semantrix has generalized the SM3 core to support integration with key industry standards, vendors and products as required. <P> SM3 capabilities: <ul><li>Able to access and utilise external information, including commercial and open-source linked-data video and related content references such as IMDB <li>Supports hierarchical social networks, using FOAF and ACL models to represent users, groups, relationships and item- level content access control <li>SM3 uses a rules-based approach to combine weighted recommendations from a range of inputs, including individual and group content ratings</ul> The SM3 core can be tailored to integrate with: <ul><li>Indexing and search of Social Networks, Blogs, UGC and Video-Management Systems <li>Enterprise Content Management and search, linking corporate information sources to related news, blogs and corporate videos for publicity, internal staff awareness, and training purposes <li>Commercial Video Management and Publishing Systems, providing the missing linkage between video-specific metadata and 3rd-party content sources</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4045 http://purl.org/dc/elements/1.1/abstract The Semantrix SM3 platform delivers enhanced value for both text and multimedia digital assets. This improves the user experience by enhancing content metadata for better search, cross-referencing and content-targeted advertising
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http://data.semanticuniverse.com/resource/semtech-2011-4015 http://www.w3.org/2000/01/rdf-schema#label Querying Tuples in an XML Store and SPARQL to XQuery Translation
http://data.semanticuniverse.com/resource/semtech-2011-4015 http://purl.org/dc/elements/1.1/abstract A detailed overview of current research and results into XML tuple querying and storage, as well as recent explorations into automated SPARQL to XQuery query translation.
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http://data.semanticuniverse.com/resource/semtech-2011-4015 http://purl.org/dc/elements/1.1/title Querying Tuples in an XML Store and SPARQL to XQuery Translation
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http://data.semanticuniverse.com/resource/semtech-2011-4015 http://purl.org/dc/elements/1.1/description MarkLogic Corporation has been funding research that explores semantic tuple storage and querying inside its scalable XML database. By representing tuples as XML documents, MarkLogic has been able to efficiently store and query against large tuple sets, including running both the Billion Triple Challenge and the Lehigh University Benchmark. In this session you will learn about current efforts in XML representations with semantic querying, as well as funded research on connecting XML stores to semantic technologies via automated SPARQL to XQuery translation with Professor Jim Hendler and Dr. Li Ding. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4015 http://swrc.ontoware.org/ontology#keywords xquery-sparql
http://data.semanticuniverse.com/resource/semtech-2011-4015 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2011-4015 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/gary-l-katz
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http://data.semanticuniverse.com/resource/semtech-2011-4015 http://swrc.ontoware.org/ontology#keywords lubm
http://data.semanticuniverse.com/resource/semtech-2011-3985 http://swrc.ontoware.org/ontology#keywords innovation-in-a-box
http://data.semanticuniverse.com/resource/semtech-2011-3985 http://www.w3.org/2000/01/rdf-schema#label Innovation in a Box: Providing Semantic Innovation on Demand
http://data.semanticuniverse.com/resource/semtech-2011-3985 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2011-3985 http://purl.org/dc/elements/1.1/abstract In this poster, we describe several use cases in which we provided semantic technology on demand to e-Commerce organizations.
http://data.semanticuniverse.com/resource/semtech-2011-3985 http://purl.org/dc/elements/1.1/description Software research projects can be long and risky, but vital as a source of competitive advantage. Especially in the specialized world of semantic engineering, an e-commerce organization may need innovative jump-starting to take advantage of the enormous value that semantics can offer on the Web. First Retail, Inc., provides expert teams that deliver carefully scoped and managed semantic solutions. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3985 http://purl.org/dc/elements/1.1/title Innovation in a Box: Providing Semantic Innovation on Demand
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http://data.semanticuniverse.com/resource/fernando-p-carolo http://www.w3.org/2000/01/rdf-schema#label Fernando P Carolo
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http://data.semanticuniverse.com/resource/fernando-p-carolo http://www.w3.org/2001/vcard-rdf/3.0#title Product Owner, Search and Semantic Tools
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http://data.semanticuniverse.com/resource/semtech-2011-3774 http://purl.org/dc/elements/1.1/abstract In this talk, I will discuss the current state of the data environment, the challenges of finding and integrating good data, and some solutions for meeting these challenges.
http://data.semanticuniverse.com/resource/semtech-2011-3774 http://purl.org/dc/elements/1.1/title Facing the Big Data Challenge
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http://data.semanticuniverse.com/resource/semtech-2011-3774 http://purl.org/dc/elements/1.1/description In today's environment of accelerating consumer expectations, anyone building an app or service must continuously look for data which adds value to the end-user. In other words, they must continuously look for good, structured data at reasonable terms. <P> Several companies, Factual being one, have been tackling this issue, attempting to build services and components for developers large and small. Meanwhile, the walls between data silos are crumbling - open government data, API platforms, etc. - creating greater opportunities, as well as challenges, in this new data environment. <P> My goal with this talk will be to inform the SemTech audience of the current state of the data environment, the challenges that lie ahead, and the efforts many of us are engaged in to meet these challenges through a variety of tools and approaches. <P> The structure of the talk will be as follows: <ul><li>Discuss the current data landscape <li>Explore the challenges of finding and integrating good data <li>Discuss new algorithmic approaches to handing data, such as rules-based and machine-learned data structuring, and de-duplication algorithms <li>Discuss the opportunities and challenges of enhancing data through crowdsourcing </ul> <P>
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http://data.semanticuniverse.com/resource/shion-deysarkar http://www.w3.org/2001/vcard-rdf/3.0#title CEO, Extractiv
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http://data.semanticuniverse.com/resource/semtech-2011-3955 http://swrc.ontoware.org/ontology#keywords books
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/dc/elements/1.1/title Discovering and Using RDF for Books at O'Reilly Media
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/dc/elements/1.1/abstract How O'Reilly Media uses RDF and SPARQL to sell and deliver Ebooks
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-case-studies-use-cases
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2011-future-of-media
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2011
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://swrc.ontoware.org/ontology#keywords ebooks
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://swrc.ontoware.org/ontology#keywords metadata
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://swrc.ontoware.org/ontology#keywords publishing
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/gavin-james-carothers
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T08:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/dc/elements/1.1/description Today O'Reilly Media has a Linked Data, Semantic, RESTful, URI-based, highly buzz-wordy solution mostly by accident and through ruthless pragmatism. This is the story of how O'Reilly Media began using RDF, SPARQL, and other semantic technology to sell $4 million in Ebooks. From early experiments using XML and XQuery to parse RDF/XML(Don't) to the successful delivery of hundreds of thousands of ebooks. <P> Learn from our missteps, disasters, and Really Bad Ideas(TM). We'll also show off some of the open source tools we built that will help other folks walking down this path. You'll also learn about how easy it is to teach English majors and editors SPARQL. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/dc/elements/1.1/audience Case Study
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://swrc.ontoware.org/ontology#keywords content
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://www.w3.org/2000/01/rdf-schema#label Discovering and Using RDF for Books at O'Reilly Media
http://data.semanticuniverse.com/resource/semtech-2011-3955 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/charles-greer
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http://data.semanticuniverse.com/resource/bao-tran http://www.w3.org/2001/vcard-rdf/3.0#org Tran & Associates
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://swrc.ontoware.org/ontology#keywords content-curation
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://swrc.ontoware.org/ontology#keywords news-filtering
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http://data.semanticuniverse.com/resource/semtech-2011-4087 http://purl.org/dc/elements/1.1/title Detecting the "Slant" of Blogs and News: Case Study with Odewire.com
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T12:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://swrc.ontoware.org/ontology#keywords bias-detection
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://purl.org/dc/elements/1.1/abstract Newly launched Odewire.com uses FM's "slant" engine to find optimistic, solutions-oriented content from news sources, via semantic technology that goes beyond topic classification and sentiment analysis to detect the attitudinal bias of text.
http://data.semanticuniverse.com/resource/semtech-2011-4087 http://purl.org/dc/elements/1.1/description The task of content curation in many cases is unmanageable when viewed from an editorial perspective, either because there is just too much content to read through on a daily basis, or because the desired type of content is so sparse that finding it is like ?looking for a needle in a haystack,? for example, trying to gather only politically conservative (or liberal, or libertarian) articles about the environment, or trying to gather dining reviews that specifically appeal to the college-age crowd. In these cases, where a certain interpretive stance, attitudinal tone, or ideological position (a ?slant?) is desired, basic classification and tagging tools fall short. This presentation shows a new tool, called the Slant Engine, that separates texts exhibiting the desired slant and supplies a score representing the confidence level assigned to one or more slants. We?ll see a live case study, the newly launched odewire.com, which gathers optimistic, solutions-oriented news from over 100 mainstream sources and is updated around the clock, with very little human monitoring. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4087 http://www.w3.org/2000/01/rdf-schema#label Detecting the "Slant" of Blogs and News: Case Study with Odewire.com
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http://data.semanticuniverse.com/resource/semtech-2011-4142 http://purl.org/dc/elements/1.1/abstract The purpose of this workshop is to educate participants on how to install, configure and use Oracle Database Semantic Technologies.
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http://data.semanticuniverse.com/resource/semtech-2011-4142 http://purl.org/dc/elements/1.1/title Oracle Database Semantic Technologies: Understanding How to Install, Load, Query and Inference
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http://data.semanticuniverse.com/resource/semtech-2011-4142 http://purl.org/dc/elements/1.1/description The purpose of this workshop is to educate participants on how to install, configure and use Oracle Database Semantic Technologies. <P> Through the use of live demos, detailed scripts and screen shots, it will be shown how to set up the database, populate with RDF/OWL data, add user defined rules in addition to those specified in RDFS/OWL/SKOS, gather statistics, create entailments with native inferencing and external inference engines, query using SQL and SEM_MATCH, query using Jena or Sesame with SPARQL, and query execution control including parallel execution, timeout, and abort with SPARQL service endpoints. <P> Additional capabilities that may be included: Semantic indexing of documents: How to define a semantic index, how to use of an external entity/concept extraction tool to populate the index, and how to use the set of index entries as a knowledge base on its own right. Ontology-assisted SQL queries on relational data. Triple-level security: How to define triple-level security using both Mandatory Access Control (with Oracle Label Security) and Discretionary Access Control (with Oracle Virtual Private Database). Graph visualization using Cytoscape: How to use the Oracle plug-in for the open source visualization tool Cytoscape to explore massive RDF graphs in the limited real estate of a computer monitor. Ontology editing using TopBraid Composer Presentation of query results and click through navigation of RDF data using the Sesame Workbench As the Oracle RDF/OWL store is finding increasing adoption, questions and issues have been raised by users on set up, usage and performance. An FAQ list will be presented, and individual questions will be answered through live demos, scripts, usage tips, performance tips, and screen shots. <P> In summary, participants will have the opportunity to obtain a comprehensive understanding of how to use an Oracle database to effectively store, manage, inference and query RDF/OWL data for enterprise applications, and also how to use RDF graphs and OWL ontologies for more effective use of existing relational databases. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3997 http://www.w3.org/2000/01/rdf-schema#label NO-SQL Metadata Management
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http://data.semanticuniverse.com/resource/semtech-2011-3997 http://purl.org/dc/elements/1.1/description For large organizations the "metadata registry" is becoming the central focus for semantic-driven strategies and the key to lowering integration costs. <P> This presentation will show how the true requirements of enterprise metadata management dictate that new schema-free web application architectures are frequently better suited to metadata management tasks than traditional relational databases. These new "zero translation" web application architectures combine some of the best aspects of enterprise search, document management and powerful query languages but without the complexity of traditional multi-tier architectures. <P> This presentation will compare and contrast highly rigid SQL-centric six-translation systems to simple and elegant systems that provide a flexible metadata management by non-programmers. We also demonstrate how document-style data can provide high-precision structured search and prevent duplication of data elements. <P> After this presentation users will be able to: <P> <ul><li>Understand the flexibility of schema-free databases <li>See how zero-translations systems provide more agility than six-translation systems <li>Understand how non-programmers can be empowered to managed metadata registries built with NO-SQL technologies <li>Appreciate how enterprise messaging and rules-based systems can leverage NO-SQL technologies <li>Find resources to set up a NO-SQL enterprise-scale metadata registry</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3997 http://purl.org/dc/elements/1.1/title NO-SQL Metadata Management
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http://data.semanticuniverse.com/resource/semtech-2011-3997 http://purl.org/dc/elements/1.1/abstract NO-SQL schema-free systems can provide a more agile development environment than rigid multi-translation systems that depend on tabular data storage. These systems empower the non-programmer to control enterprise metadata management.
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http://data.semanticuniverse.com/resource/semtech-2011-3786 http://www.w3.org/2000/01/rdf-schema#label playence media: Semantic Multimedia Annotation and Search in the Media Sector
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http://data.semanticuniverse.com/resource/semtech-2011-3786 http://purl.org/dc/elements/1.1/title playence media: Semantic Multimedia Annotation and Search in the Media Sector
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http://data.semanticuniverse.com/resource/semtech-2011-3786 http://purl.org/dc/elements/1.1/description As rich medium, video and audio can transport and conserve more information than text ever could. Consequently, its use in corporate settings and on the Web is rapidly and inexorably gaining momentum. This new type of content also creates new issues with respect to integration and annotation: up until now, heterogeneous data formats in text-based resources were a major challenge, now integration of non-textual contents has to be tackled. Naturally, a rich media asset is related to information and data residing in various information systems. While text analysis has been researched since years and mature solutions for tackling text annotation exist, the semantic annotation and management of multimedia is a field with ample room for growth. <P> This tutorial will explain playence?s approach to the semantic annotation, search and browsing of multimedia content (i.e. video, audio and text) as applied to one of our customers in the media sector. It will also discuss challenges, such as how to evolve the subjacent ontological model to meet new annotation requirements, how to create cross-language queries that land at the precise second a character is pronouncing a word, or how exploit the benefits of the LOD in the context of professional multimedia asset management. By the end you will understand how semantic technology can leverage multimedia through a real use case in the media industry. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3786 http://purl.org/dc/elements/1.1/abstract Provide an overview of the problems solved and goals achieved (i.e. cost cutting, reduced annotation time, improved information access) by our media customer by using playence media to manage its multimedia content.
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http://data.semanticuniverse.com/resource/semtech-2011-3967 http://purl.org/dc/elements/1.1/title A Platform for Integrating Public Data into NYC.gov
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http://data.semanticuniverse.com/resource/semtech-2011-3967 http://purl.org/dc/elements/1.1/abstract This presentation is about a solution created for the City of New York to enable distributed communities of people to collaboratively integrate public data sets so that they can be used for analysis.
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http://data.semanticuniverse.com/resource/semtech-2011-3967 http://purl.org/dc/elements/1.1/description This solution provides a canonical model of an enterprise in OWL, called a "domain ontology." This ontology is developed with the assistance of subject-matter experts using Knoodl, a web-based tool for collaborative ontology development. In addition to the domain ontology, a mapping ontology is created for each of the public data sets. The mapping ontology relates concepts in the domain ontology to concepts in the data sources. Revelytix software uses the mapping ontology to transform SPARQL queries addressed to the domain ontology into SQL queries at query time. If multiple data sources are included, an additional piece of Revelytix software is used for query costing and planning, integrating result sets, and caching for performance optimization. Because the domain ontology is OWL-based, it is both flexible and extensible, providing a key advantage over traditional ETL or data warehousing solutions for a range of analytic applications. <P> Presentation will include: <ul><li>Demonstration of how subject matter experts and ontologists develop ontologies collaboratively <li>Demonstration of a dashboard displaying real-time, federated, SPARQL-driven analytics across the NYC data sets <li>Detailed explanation of how the ontology architecture and middleware support the dashboard <li>Discussion of the range of analysis enabled by federated SPARQL queries, performance limitations, and business applications</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3967 http://swrc.ontoware.org/ontology#keywords analytics
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http://data.semanticuniverse.com/resource/semtech-2011-3967 http://www.w3.org/2000/01/rdf-schema#label A Platform for Integrating Public Data into NYC.gov
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http://data.semanticuniverse.com/resource/semtech-2011-3967 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-09T10:10:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/todd-pehle
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http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/title GeoSPARQL: An OGC Standard for Spatial Query on the Web of Linked Data
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/description As massively large geospatial datasets begin to flood the Web of Linked Data and vendors begin to implement proprietary geospatial extensions to SPARQL, standardization efforts are becoming increasingly important. This presentation introduces GeoSPARQL, an emerging Open Geospatial Consortium (OGC) standard that defines an RDFS/OWL vocabulary and a set of spatial extension functions for SPARQL. GeoSPARQL standardization began in summer 2010 and is expected to be completed in 2011. Offering rich spatial queries of RDF, GeoSPARQL will increasingly blur the line between the Semantic Web and the Geo Web. Linked Data applications will be able to find New York skyscrapers in DBPedia within a Data.gov city block which is adjacent to a street in Open Street Map. As the Web of Linked Data grows, standards such as GeoSPARQL will be critical for data integration and interoperability. <P> This presentation will illustrate the following aspects of GeoSPARQL: o Background of geospatial data and queries in the Semantic Web o Limitations of current spatial representation and querying techniques o Explanation of GeoSPARQL vocabulary and language constructs o Qualitative and quantitative spatial reasoning combined with GeoSPARQL o A large number of intuitive examples plus demonstrations based on real use cases o Overview of near-term implementations and future considerations <P>
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/abstract GeoSPARQL is a spatial extension to SPARQL near standardization in the Open Geospatial Consortium. This presentation will discuss language constructs and use cases and demonstrate the profound impact GeoSPARQL will have in Linked Data.
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http://data.semanticuniverse.com/resource/semtech-2011-3841 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dave-kolas
http://data.semanticuniverse.com/resource/semtech-2011-3841 http://www.w3.org/2000/01/rdf-schema#label GeoSPARQL: An OGC Standard for Spatial Query on the Web of Linked Data
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http://data.semanticuniverse.com/resource/semtech-2011-4154 http://purl.org/dc/elements/1.1/audience Business
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http://data.semanticuniverse.com/resource/semtech-2011-4154 http://purl.org/dc/elements/1.1/abstract Process Management and Information Retrieval are usually separated worlds, but automatic semantic technology combines both worlds for smart enterprise portals enabling dynamic information logistics for flexible and agile process management.
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http://data.semanticuniverse.com/resource/semtech-2011-4154 http://purl.org/dc/elements/1.1/title iQser AG Sponsored Session: Information Logistics for Smart Enterprise Portals
http://data.semanticuniverse.com/resource/semtech-2011-4154 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jörg-wurzer
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http://data.semanticuniverse.com/resource/semtech-2011-4154 http://www.w3.org/2000/01/rdf-schema#label iQser AG Sponsored Session: Information Logistics for Smart Enterprise Portals
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http://data.semanticuniverse.com/resource/semtech-2011-4154 http://purl.org/dc/elements/1.1/description The presentation respectively workshop shows in a real life example how to cope with the challenge of integrating, processing and accessing distributed data in organizations. The solution combines a pragmatic bottom-up integration approach with automatic and self optimizing semantic analysis to provide data dynamically in any personalized working and process context of the user. The active search and meta data maintenance is turned to a smart delivery of relevant, precise information. Distributed data is transferred to meaningful information by transparent relations. Partly unexpected relations and hidden information drives new business value beyond the increased efficiency of information access in an organization. The real live example is based on standard components and industry standards, mainly the Liferay Portal and the GIN Platform as a semantic integration and analysis engine. It enables an easy to adopt and setup portal and solution approach for any it infrastructure. The Audience will learn: <ul> <li>Concept of smart information logistics independently from any technology <li>Pragmatic approach for efficient data integration and analysis <li>Hands on guide to build a smart information logistic portal for their organization <li>Outlook to combine the technology stack with other solution components <li>Inspiration for own services and solutions to make business </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T13:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://purl.org/dc/elements/1.1/description Linked data offers a powerful approach to publishing and consuming data on the web. However, much data of interest comes as tables and multi-dimensional arrays of simple values: examples include official statistics, environmental sensor net data and raw financial data. Previously, Linked Data tools and vocabularies were not well-suited to such data. <P> In this talk we describe the Data Cube vocabulary, which provides a common framework for representing such information as RDF linked data. We will cover: <ul><li>The data cube vocabulary ("qb") and how to use it. <li>Our experiences publishing public sector data using qb,including UK local and central government spend information, and environmental monitoring data. <li>The benefits that the linked data approach brings in these cases. <li>Examples of tools and capabilities that use of qb makes possible, from APIs to UIs.</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://www.w3.org/2000/01/rdf-schema#label Linked Data Hypercubes
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://purl.org/dc/elements/1.1/title Linked Data Hypercubes
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http://data.semanticuniverse.com/resource/semtech-2011-3811 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dave-reynolds
http://data.semanticuniverse.com/resource/semtech-2011-3811 http://purl.org/dc/elements/1.1/abstract We describe how to publish multi-dimensional datasets as Linked Data using the new Data Cube vocabulary, based on our experiences with datasets ranging from government finance to environmental monitoring.
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http://data.semanticuniverse.com/resource/semtech-2011-3798 http://purl.org/dc/elements/1.1/title The IDEAS Group Ontology
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http://data.semanticuniverse.com/resource/semtech-2011-3798 http://purl.org/dc/elements/1.1/abstract An overview of the ongoing effort by the defense departments of Australia, Canada, Sweden, UK and USA to develop a common ontology for Enterprise Architecture
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http://data.semanticuniverse.com/resource/semtech-2011-3798 http://www.w3.org/2000/01/rdf-schema#label The IDEAS Group Ontology
http://data.semanticuniverse.com/resource/semtech-2011-3798 http://swrc.ontoware.org/ontology#keywords upper-ontology
http://data.semanticuniverse.com/resource/semtech-2011-3798 http://purl.org/dc/elements/1.1/description In 2005, it was recognized that the defense departments of various nations had each developed their own architecture frameworks. These frameworks specified standard ways to describe an enterprise - e.g. process models, org charts, system structures, network diagrams, state models, etc. <P> All the national frameworks served similar purposes but used different terminology and and metamodels. This was presenting a barrier to the nations sharing their architectures. The increase in the number of coalition operations (including various peacekeeping operations) combined with the increase in the complexity of the systems used by each of the nations meant that there was a real need to share enterprise and system information between coalition partners. The IDEAS Group was set up to tackle this problem and develop a common upper ontology that all the nations could adapt and specialize for their own purpose. The long term goal being that once all nations were using the same foundation it would be easier to eventually migrate to just one international framework. <P> The IDEAS Foundation (high level upper ontology) was published in 2008 and has since been adopted as the basis of the DOD's Architecture Framework Meta Model. The Swedish Armed Forces have also begun work to migrate the UK MOD's metamodel to the IDEAS Foundation. <P> This presentation outlines: <P> * The need for coalition interoperability of architectures - e.g. each nation understanding each others org structures, processes, communications laydowns, etc. * Current status of IDEAS, and the projects that have used it * A brief overview of the methodology used to re-engineer the national frameworks into an ontology * Use of modelling tools in a community which had little prior experience of ontology development * Lessons learned in collaborative, international ontology development * The benefits already realized and the future for IDEAS and the national frameworks <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4009 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/matthias-kaiser
http://data.semanticuniverse.com/resource/semtech-2011-4009 http://purl.org/dc/elements/1.1/abstract The presentation explains SAP?s strategic plan for adopting semantic technologies including goals, technical capabilities required to achieve the goals
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http://data.semanticuniverse.com/resource/semtech-2011-4009 http://purl.org/dc/elements/1.1/title SAP?s Strategy for Semantic Technology in Enterprise Applications
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http://data.semanticuniverse.com/resource/semtech-2011-4009 http://www.w3.org/2000/01/rdf-schema#label SAP?s Strategy for Semantic Technology in Enterprise Applications
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http://data.semanticuniverse.com/resource/semtech-2011-4009 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2011-4009 http://purl.org/dc/elements/1.1/description Pockets of adoption of semantic technologies in enterprise applications remain relatively uncoordinated and mostly tactically oriented. In this presentation we will explain SAP?s strategic plan for adopting semantic technologies. The plan poses bold yet achievable goals, defines the capabilities required to achieve the goals, and maps out a company-wide action plan to achieve success. The plan establishes the following strategic goals for using semantic technologies: <P> - Assist people in unstructured work - Align business applications with business intent - Promote transparency and consistency via end-to-end metadata - Clarify the meaning of structured business data - Unify diversely structured business data - Establish an ecosystem for semantics-based development <P> We will also discuss the capabilities that we have identified as necessary to achieve the strategic goals, including integrated metadata management, controlled vocabulary management, tagging, context management, linking, inference/reasoning, and harvesting existing metadata. <P> We will also explain the action plan to execute the strategy. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4009 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-crawford
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http://data.semanticuniverse.com/resource/semtech-2011-3979 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/robert-kost
http://data.semanticuniverse.com/resource/semtech-2011-3979 http://purl.org/dc/elements/1.1/title A Travel Strategy for Semantic Technology
http://data.semanticuniverse.com/resource/semtech-2011-3979 http://www.w3.org/2000/01/rdf-schema#label A Travel Strategy for Semantic Technology
http://data.semanticuniverse.com/resource/semtech-2011-3979 http://purl.org/dc/elements/1.1/abstract Overview of how semantic technologies are being deployed in the car rental industry
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http://data.semanticuniverse.com/resource/semtech-2011-3979 http://purl.org/dc/elements/1.1/description Avis Budget Group is at the forefront of semantic technology as it relates to: the adoption of standards within the travel industry; the use of semantics to enhance the customer experience; and the use of semantics for marketing its services. This presentation will provide a brief overview of how semantics is being adopted in the car rental business. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4070 http://swrc.ontoware.org/ontology#keywords multimedia-semantics
http://data.semanticuniverse.com/resource/semtech-2011-4070 http://purl.org/dc/elements/1.1/abstract We present an NLP-based approach towards the automatic generation of RDF video descriptions.
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http://data.semanticuniverse.com/resource/semtech-2011-4070 http://purl.org/dc/elements/1.1/description SemWebVid is a Web application that allows for the automatic on-the-fly generation of Resource Description Framework (RDF) video descriptions. These descriptions are based on two pillars: first, on a combination of user-generated metadata such as title, summary, and tags; and second, on closed captions which can be user-generated, or be auto-generated via audio transcription services. The plaintext contents of both pillars are analyzed using multiple Natural Language Processing (NLP) Web services in parallel whose results are then merged and where possible detected entites matched back to concepts represented by URIs in the sense of Linked Open Data (LOD). The final result is a downloadable RDF description of the video. As a first exemplary use case the application provides a special view where detected entites are depicted as the video plays along. <ul> <li>Fully automatable approach (audiotranscription-based, NLP-based) <li>Working prototype available at http://tomayac.com/semwebvid/ <li>Interesting details in the approaches to entity matching and mapping</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4070 http://www.w3.org/2000/01/rdf-schema#label SemWebVid - An Automatable Approach Towards RDF Video Description Generation
http://data.semanticuniverse.com/resource/semtech-2011-4070 http://purl.org/dc/elements/1.1/title SemWebVid - An Automatable Approach Towards RDF Video Description Generation
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http://data.semanticuniverse.com/resource/semtech-2011-3823 http://swrc.ontoware.org/ontology#keywords text-parsing
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http://data.semanticuniverse.com/resource/semtech-2011-3823 http://purl.org/dc/elements/1.1/abstract The Luminary System integrates a content extraction framework, entity extraction, ontologies, and semantic wikis into a cohesive design for identifying relevant content and presenting the derived information to users.
http://data.semanticuniverse.com/resource/semtech-2011-3823 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3823 http://swrc.ontoware.org/ontology#keywords lexical-parsing
http://data.semanticuniverse.com/resource/semtech-2011-3823 http://www.w3.org/2000/01/rdf-schema#label The Luminary System
http://data.semanticuniverse.com/resource/semtech-2011-3823 http://swrc.ontoware.org/ontology#keywords reasoning
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http://data.semanticuniverse.com/resource/semtech-2011-3823 http://purl.org/dc/elements/1.1/description We present the Luminary System, a prototype designed to identify and extract relevant content from unstructured text and present it in a summarized form to users. Guided by an OWL ontology, the system extracts relevant entities and concepts using semantic lexical parsing. The Luminary system can parse news articles, word documents, and other unstructured text, looking for relevant information. When it identifies a relevant nugget of information, it expands the information into an OWL object composed of RDF triples. The system automatically creates or updates the relevant information in a semantic wiki, incorporates information known from other sources, and derives new information. The semantic wiki maintains templates, forms and categories for each class of objects within the OWL ontology, ensuring a consistent data model. <P> Innovations within the Luminary System include: <ul><li>Entity extraction using multiple tools in parallel within an extensible framework <li>Entity verification processes to enhance accuracy of extracted entities <li>Concept extraction through lexical parsing and ontological reasoning <li>Automated updates to the semantic wiki using OWL objects <li>Automated process to generate or update templates, forms, and categories when ontology changes</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3823 http://purl.org/dc/elements/1.1/title The Luminary System
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http://data.semanticuniverse.com/resource/semtech-2011-4010 http://purl.org/dc/elements/1.1/description This half-day tutorial is an overview of Entity Extraction for the non-programmer. Entity extraction is rapidly becoming one of the most cost-effective ways to extract knowledge from documents. The first session is a general introduction including introduction to terminology with short demonstrations of entity extraction using real-world software on real documents. We cover the key processes Entity Extraction and then link them to concepts in the Semantic Web stack including XML encoding, URIs, RDF and RDFa. <P> In part two we begin to uncover some of the real challenges involved in high-quality entity extraction and the tools. We cover part-of-speech analysis, noun phrases and entity extraction pipelines, validation of entities and a short jump into some of the complex mathematics used in machine learning of large corpus. <P> In Part three we cover ROI, quality metrics, data formats, mashups and strategies. We also show how Business Intelligence systems can integrate text analytics. <P> After this presentation users will: <P> <ul><li>Understand the key issues in Entity Extraction of text documents <li>Understand the concept of linguistic pipelines, annotators and text enrichment <li>Appreciate the complexities of natural language understanding and how both rule based systems and machine learning can be used to tackle these challenges <li>Understand how Entity Extraction quality can be measured and how quality metrics can be used to tune the Entity Extraction process <li>Find resources to start and Entity Extraction pilot project</ul> <P>
http://data.semanticuniverse.com/resource/semtech-2011-4010 http://purl.org/dc/elements/1.1/abstract This presentation covers the core process of finding key objects within text documents such as people, geo-locations, organizations, terms and dates. This presentation is a non-technical overview for business users.
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http://data.semanticuniverse.com/resource/semtech-2011-4010 http://purl.org/dc/elements/1.1/title Entity Extraction
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http://data.semanticuniverse.com/resource/semtech-2011-4136 http://purl.org/dc/elements/1.1/description The Library of Congress is utilizing linked data and semantic technologies in several current projects including Project Recollection and it's Digital Preservation Initiative. Laura Campbell, CIO of the LoC, will describe these efforts and the reasons for choosing to enable them with semantics. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4136 http://www.w3.org/2000/01/rdf-schema#label Semantic Technology at the Library of Congress
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http://data.semanticuniverse.com/resource/semtech-2011-4136 http://purl.org/dc/elements/1.1/title Semantic Technology at the Library of Congress
http://data.semanticuniverse.com/resource/semtech-2011-3919 http://purl.org/dc/elements/1.1/description Globo.com is the web portal from the leading media group in Brazil, Organizações Globo, a conglomerate that includes TV and radio stations, newspapers and magazines. The company started to use semantic technologies to improve the way it organizes and presents multimedia content ranging from hard news to sports coverage to celebrity gossip. Working in two parallel initiatives, Globo.com is building a set of ontologies to annotate content in different knowledge domains and developing a common software framework that allows each web site to work with semantic annotations to classify and present content in attractive ways. This session will present the key achievements from this work, including: <ul><li>Building a top-level ontology that permeates all domains handled by the portal. <li>Enabling product teams to build and work with domain ontologies. <li>Building a set of reusable software tools that incorporate semantic annotation to different web sites. <li>Finding new ways to present annotated content on the web, mixing and matching text, image and video.</ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3919 http://swrc.ontoware.org/ontology#keywords interfaces
http://data.semanticuniverse.com/resource/semtech-2011-3919 http://purl.org/dc/elements/1.1/title Improving Web Content Management with Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2011-3919 http://purl.org/dc/elements/1.1/abstract This case study shows how Globo.com, a Brazilian web portal, uses semantic technologies to improve content management and let users explore its multimedia content in new and interesting ways.
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http://data.semanticuniverse.com/resource/semtech-2011-3980 http://purl.org/dc/elements/1.1/abstract Semantic Social Networks are a new product category that combine online social networking and Semantic Web technologies to maximize data fidelity and reusability across heterogeneous online products.
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http://data.semanticuniverse.com/resource/semtech-2011-3980 http://purl.org/dc/elements/1.1/audience Business
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http://data.semanticuniverse.com/resource/semtech-2011-3980 http://purl.org/dc/elements/1.1/description A Semantic Social Network (SSN) is a new product category that combines features of online social networking sites with Semantic Web technologies to maximize data fidelity and data reusability across heterogeneous social networking products. With the increase in online networking sites and social media content offerings propriety data formats become a road block for efficient data management and transfer across community boundaries. Centralized services and API based data exchange are a temporary fix to tackle this issue but do not address the challenge of data mobility that we already face with the growing data deluge on the world wide web. In a Semantic Social Network the business logic of social practice become first class objects, uniquely identifiable on the web and maybe most importantly relationships between objects become first class objects as well, and thereby are now negotiable amongst users and will allow for entirely new services on the web. In this presentation we will take a look at Lotico a Semantic Social Network with more than 15000 members worldwide that share a common interest in the Semantic Web. Lotico?s core platform is powered with semantic technologies, that now enable Lotico to publish its content in form of Linked Open Data to the public web. In addition to the core platform Lotico augments existing social networking and community sites such as meetup, mediawiki and facebook to allow members to utilize Lotico resources across heterogeneous community platforms, to find content and to connect people across sites. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3980 http://purl.org/dc/elements/1.1/title Distributed Semantic Social Networks
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http://data.semanticuniverse.com/resource/semtech-2011-3920 http://purl.org/dc/elements/1.1/title Fighting Fires Using Semantic Web Technology
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http://data.semanticuniverse.com/resource/semtech-2011-3920 http://www.w3.org/2000/01/rdf-schema#label Fighting Fires Using Semantic Web Technology
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http://data.semanticuniverse.com/resource/semtech-2011-3920 http://purl.org/dc/elements/1.1/abstract As no single incident is the same, static interfaces and predefined questions will not work. A new way of structuring information and a new interface design are needed.
http://data.semanticuniverse.com/resource/semtech-2011-3920 http://swrc.ontoware.org/ontology#keywords fire-department
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http://data.semanticuniverse.com/resource/semtech-2011-3920 http://purl.org/dc/elements/1.1/description The Fire Department Amsterdam-Amstelland has started an innovation project to change the way it deals with information about incidents to which the fire fighters are called. It pulls incident-relevant information, and processes it, from various institutions, such as organizations that are involved in emergency response and partners in the municipality. As already shown on various occasions, the department uses a navigation assistant which utilizes Semantic Web Technologies / Open Data and is based on some of the innovative concepts created by netlabs.org. As the project is moving ahead, we are currently creating more interfaces on the same data, enriching the data, collecting more data from local government departments and putting data around previous incidents in the Linked Open Data (LOD) cloud. This session is intended to give a real-life use case to illustrate the process of using Semantic Web Technologies and to show the dynamics of data-driven interfaces based on Semantic Web data. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4022 http://purl.org/dc/elements/1.1/abstract Mayo Consumer Vocabularies (MCV) bridges the communication gap between patients and healthcare professionals. This presentation demonstrates an innovative semantic-based and model driven approach for implementing MCV.
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http://data.semanticuniverse.com/resource/semtech-2011-4022 http://www.w3.org/2000/01/rdf-schema#label Mayo Consumer Vocabularies (MCV): Semantic-Based&amp;Model Driven Solution to Support the Delivery of Healthcare Information
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http://data.semanticuniverse.com/resource/semtech-2011-4022 http://purl.org/dc/elements/1.1/description As one of the country?s leading healthcare organizations, Mayo Clinic not only treats patients from all over the world, but also provides essential healthcare knowledge for the public via its website, mayoclinic.com. The majority of visitors to the Mayo Clinic web site are not versed in technical medical terms. Therefore, consumer vocabularies come to the rescue by providing everyday words and phrases about health in place of technical professional terms. <P> The new MCV environment, to be released in late 2011, transforms the current implementation, which is taxonomy-based, into a model driven and semantic-based one, using semantic technology and best practices of software engineering. <P> The new MCV release will play a central role in providing accurate and consistent knowledge to different systems in Mayo. MCV is based on a robust and well-designed semantic framework that utilizes different aspects of semantic technology, including ontology, SPARQL, and off-shelf reasoners. <P> MCV maps consumer vocabularies to standard medical vocabularies, such as SNOMED, LOINC, ICD-9, RxNorm, etc. Consequently, the semantic environment will also support delivery of personalized healthcare information and services. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4022 http://purl.org/dc/elements/1.1/title Mayo Consumer Vocabularies (MCV): Semantic-Based&amp;Model Driven Solution to Support the Delivery of Healthcare Information
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http://data.semanticuniverse.com/resource/semtech-2011-3932 http://swrc.ontoware.org/ontology#keywords google-gadgets
http://data.semanticuniverse.com/resource/semtech-2011-3932 http://purl.org/dc/elements/1.1/description In a federated information environment, the need for visibility into disparate systems to provide real-time, plug-and-play dashboards displaying decision-grade information has become a significant requirement for any enterprise. <P> Combining Google Gadgets with the SPARQL query language creates a flexible, semantics-based environment which enables agile development of federated enterprise dashboards. Google gadgets, implementing the OpenSocial API and populated with federated SPARQL queries, accomplishes the following: <P> * Allows for the development of gadgets by multiple parties while ensuring interoperability and scalability * Provides the flexibility for users to rapidly develop customized dashboards * Ensures top-to-bottom visibility across the enterprise. <P> In December 2010, the HR EIW transitioned its user interface platform away from custom HTML and JavaScript to support Google Gadgets. This transition allows for more rapidly developed and flexible user defined front-end visualization capabilities. In addition, the semantic description of these gadgets provides the foundation of a operationally governed, collaborative gadget registry. This community approach to gadget development and description enables users to precisely align their information requirements with current analytic capabilities, and collaboratively address any capability gaps with the reuse or development of analytic capabilities. <P> This session will highlight the real world application of semantic technologies and Google Gadgets in one of the world?s largest, most complicated enterprise data environments through a case study of the Department of Defense Human Resource Enterprise Information Web (HR EIW), overseen by the Office of Secretary of Defense Deputy Chief Management Office. The HR EIW implements freely available products developing cutting edge, agile business intelligence capabilities. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3932 http://swrc.ontoware.org/ontology#keywords dashboards
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http://data.semanticuniverse.com/resource/semtech-2011-3932 http://purl.org/dc/elements/1.1/title Agile Development of Federated, Interoperable Dashboards with Google Gadgets and SPARQL
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http://data.semanticuniverse.com/resource/semtech-2011-3932 http://purl.org/dc/elements/1.1/abstract Combining Google Gadgets and SPARQL creates a flexible, semantics-based environment which enables agile development of federated enterprise dashboards, as implemented in the Department of Defense Human Resources Enterprise Information Web.
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http://data.semanticuniverse.com/resource/semtech-2011-3847 http://purl.org/dc/elements/1.1/abstract Contextual intelligence technologies identify relationships among information, people, and places, and use the resulting context to construct knowledge and provide new services.
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http://data.semanticuniverse.com/resource/semtech-2011-3847 http://purl.org/dc/elements/1.1/description With the increasing scale of pervasive systems, more and more information is constantly collected and stored. The amount of information that is accumulated for each user becomes enormous. Contextual intelligence technologies identify relationships among information, people, and places, and use the resulting context to construct knowledge and provide services. Increasingly powerful content analysis and contextual inferencing technologies make it possible to extract and construct a personal semantic network (PSN) of the contextual relationships across one?s digital and physical interactions. Entities representing locations, people, topics, activities etc. serve as pivotal elements empowering the user to navigate their PSN. This presentation will discuss and detail the construction of PSNs and the integration of physical and digital content using connection points rich enough to serve as a "second brain" to augment the user?s cognition on a constant basis. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3847 http://purl.org/dc/elements/1.1/title Contextual Intelligence: Semantics in the Physical World
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http://data.semanticuniverse.com/resource/semtech-2011-3902 http://purl.org/dc/elements/1.1/abstract Why and how the EU Publications Office is using automated thesaurus matching to improve retrieval of multilingual government content through smarter annotation, federation, and semantic (re-)indexing.
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http://data.semanticuniverse.com/resource/semtech-2011-3902 http://purl.org/dc/elements/1.1/description The Publications Office of the European Union has launched several initiatives that will leverage the Office?s controlled vocabularies and indexing tools to facilitate metadata interoperability and access to multilingual government content. This subject was at the center of the Eurovoc Conference held in Luxembourg in November 2010. <P> One of such initiatives is thesaurus matching, which aims to improve automatic indexing and re-indexing of existing content, support automatic query expansion, and ultimately, help the Publication Office to join the ?Linked Data? community. <P> The EU?s thesaurus matching initiative uses advanced semantic technologies, and is specifically powered by AROMA, INRIA Exmo?s thesaurus matcher. <P> This talk will explain why and how the EU relies on thesaurus matching technologies to achieve their objectives. The presentation will cover the following: The technology behind semantic thesaurus matching; Examples of thesaurus matching between EuroVoc (4.3), GEMET, ETT (Cedefop), Directory of the legislation in force (in EUR-Lex) and EuroVoc 4.2; Manual quality control and validation of thesaurus matching relations based on scores. <P> Mondeca is a provider of thesaurus matching software to the Publications Office of the EU. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3902 http://www.w3.org/2000/01/rdf-schema#label Thesaurus Matching: EU Publications Office Improves Access to Government Content
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http://data.semanticuniverse.com/resource/semtech-2011-3902 http://purl.org/dc/elements/1.1/title Thesaurus Matching: EU Publications Office Improves Access to Government Content
http://data.semanticuniverse.com/resource/semtech-2011-3902 http://swrc.ontoware.org/ontology#keywords metadata-alignment
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http://data.semanticuniverse.com/resource/semtech-2011-3817 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-08T11:40:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3817 http://www.w3.org/2000/01/rdf-schema#label Semantic Web for the Bottom Line: Case Studies in Pharma
http://data.semanticuniverse.com/resource/semtech-2011-3817 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/rob-gonzalez
http://data.semanticuniverse.com/resource/semtech-2011-3817 http://purl.org/dc/elements/1.1/title Semantic Web for the Bottom Line: Case Studies in Pharma
http://data.semanticuniverse.com/resource/semtech-2011-3817 http://purl.org/dc/elements/1.1/description Pharma has a serious data management problem. Our understanding of biological systems is evolving rapidly, becoming more complicated by the day. New methods of compound discovery, testing, and validation continue to be developed, and the regulatory environment changes almost as quickly in an attempt to keep up. Meanwhile, companies are outsourcing core activities, including compound testing, validation, manufacturing, and even aspects of clinical trials and clinical trial management abroad. <P> In this tumultuous environment, traditional technologies have been unable to provide scientists, scouts, marketers, and brand managers with access to the right views of data in this rapidly changing environment. Rob Gonzalez, Senior Product Manager at Cambridge Semantics, will discuss how the flexibility and focus on subject matter experts--as opposed to technological experts--provides pharmaceutical companies with new capabilities to drive down costs of drug research and marketing. He will present two case studies, and draw parallels in other industries. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3817 http://purl.org/dc/elements/1.1/abstract Semantic Web technologies are being used in production applications in top pharmaceutical companies to drive down costs and boost top line revenue. Rob will describe a couple specific use cases in detail.
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http://data.semanticuniverse.com/resource/semtech-2011-3974 http://purl.org/dc/elements/1.1/abstract This hands-on tutorial will give participants practical experience using Semantic Web tools and technologies to develop dynamic web and mobile mashups based on the Linked Open Data cloud.
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http://data.semanticuniverse.com/resource/semtech-2011-3974 http://purl.org/dc/elements/1.1/title Building Mashups for the Linked Data Cloud
http://data.semanticuniverse.com/resource/semtech-2011-3974 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2011-06-06T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-3974 http://purl.org/dc/elements/1.1/description Mashups are a popular form of lightweight web application that combine rich heterogeneous datasets together to create compelling visualizations and enable users to interact with data to uncover new patterns and correlations. Building Mashups for the Linked Data Cloud will be a hands-on tutorial that will give participants practical experience using Semantic Web tools and technologies to quickly create mashups using data from the Linked Open Data cloud. Participants will learn how to: <P> * Identify and query semantic datasets across the Linked Open Data ?cloud? (e.g. DBpedia) using SPARQL * Choose the best visualization approaches for various kinds of data * Transform query results into visualizations and mashups (e.g. Google Visualization API, Simile Exhibit) * Extend and evolve the scope of existing mashups by adding related datasets to queries * Present information to users on a variety of mobile platforms (iOS, Android) through the application of web technologies such as CSS <P> The tutorial will include live demos, code analysis, live coding and audience participation. By the end of the session participants will have a working knowledge of how to find relevant linked data in the cloud and how to construct compelling mashups and visualizations to get their message across. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-3974 http://swrc.ontoware.org/ontology#keywords mobile-web
http://data.semanticuniverse.com/resource/semtech-2011-3974 http://swrc.ontoware.org/ontology#keywords visualization
http://data.semanticuniverse.com/resource/semtech-2011-3974 http://swrc.ontoware.org/ontology#keywords semantic-web
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http://data.semanticuniverse.com/resource/semtech-2011-3763 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2011-3763 http://purl.org/dc/elements/1.1/title Introduction to RDFa 1.1
http://data.semanticuniverse.com/resource/semtech-2011-3763 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ivan-herman
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http://data.semanticuniverse.com/resource/semtech-2011-3763 http://purl.org/dc/elements/1.1/abstract RDFa has gained a significant traction the past few years; this presentation gives an overview of what this technology is, how it works, and shows some applications.
http://data.semanticuniverse.com/resource/semtech-2011-3763 http://swrc.ontoware.org/ontology#keywords web-developers
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http://data.semanticuniverse.com/resource/semtech-2011-3763 http://purl.org/dc/elements/1.1/description RDFa has gained a significant traction the past few years; sites from BestBuy to the Library of Congress, from Tesco to O'Reilly use it to convey Semantic information on their Web site. Google, Facebook, or Yahoo all use and understand RDFa information, too. W3C has published a first version of RDFa in 2008. Since then a number of new issues in using RDFa has surfaced, new requirements came to the fore; as a result, a new version of RDFa, referred to as RDFa 1.1, is planned to be published in 2011. <P> This presentation aims at a short tutorial on RDFa, including the features added as part of RDFa 1.1. The goal is that the audience would have a good understanding on how RDFa is used in an (X)HTML page, ie, how structured information could be added to traditional Web pages for further processing on the Semantic Web. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4076 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2011-4076 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-08T14:20:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2011-4076 http://purl.org/dc/elements/1.1/abstract The world population is estimated to be 9 billion by 2050. Global food security is dependant upon the discovery of new and novel ways to use small molecules to provide crop protection and help farmers guarantee yields.
http://data.semanticuniverse.com/resource/semtech-2011-4076 http://purl.org/dc/elements/1.1/description In order to maximize the chances of finding new and novel crop protection molecules it is necessary to harness information both inside and outside of an organization. The European Bioinformatics Institute (EBI) provides highly curated small molecule data sets which when combined with an organization corporate collection can give insights into activity. This presentation will show how Syngenta went about integrating these highly curated datasets with their own internal corporate small molecule data sets, to help the invention process: <P> - Candidate data, Chembl, CHEBI, Corporate Catalog - IDs and integration Strategy - ontologies developed to meet the needs - new user capabilities <P> This is a great example of small applications of semantic web technology that has a great impact on life science research. <P>
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http://data.semanticuniverse.com/resource/semtech-2011-4076 http://purl.org/dc/elements/1.1/title Integrating Public Chemical Activity Data to Help Farmers Feed the World
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http://data.semanticuniverse.com/resource/semtech-2011-4076 http://swrc.ontoware.org/ontology#keywords chembl-chebi-semantic_web-bioinformatics-chemistry-biology
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http://data.semanticuniverse.com/resource/semtech-2011-4076 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/derek-scuffell
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http://data.semanticuniverse.com/resource/semtech-2011-4076 http://www.w3.org/2000/01/rdf-schema#label Integrating Public Chemical Activity Data to Help Farmers Feed the World
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://swrc.ontoware.org/ontology#keywords entity-relationship-model
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2011-3859 http://purl.org/dc/elements/1.1/description "What is the difference between an ontology and a database schema"? Since the early days of the now maturing ontology field, this has been a persistent question that has never been adequately answered. We define each concept for a high level comparison and then ask the following questions about each concept: 1) What is it for? 2) What does it look like? 3) How do you build one? 4) How is it implemented and used? and 5) Where are the semantics? <P> This gives rise to many other questions. For example: What is the role of constraints? of instances? Is there an analogy in ontology development for the process or database schema normalization? How is change management handled? <P> The differences between database schema and ontologies are many, varied and illuminating. Most arise from their different purposes and historical origins. There are also striking similarities. We wondered whether database schema and ontologies were more alike than different. We reached a surprising conclusion! <P>
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#SessionEvent
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://purl.org/dc/elements/1.1/abstract The goal of this talk is to once and for all settle the often asked but never adequately answered question: ?What is the difference between an ontology and a database schema??
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http://data.semanticuniverse.com/resource/semtech-2011-3859 http://purl.org/dc/elements/1.1/title Ontologies and Database Schema: What?s the Difference?
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-f-uschold
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://swrc.ontoware.org/ontology#keywords database-schema
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http://data.semanticuniverse.com/resource/semtech-2011-3859 http://www.w3.org/2000/01/rdf-schema#label Ontologies and Database Schema: What?s the Difference?
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2011-3859 http://swrc.ontoware.org/ontology#keywords object-oriented-modeling
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http://data.semanticuniverse.com/resource/semtech-2011-4046 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-06T13:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-4046 http://purl.org/dc/elements/1.1/title Introduction to Semantic Search
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/2002/12/cal/icaltzd/Vevent
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://purl.org/dc/elements/1.1/abstract The objective of the tutorial is to give an overview to conference attendees of the rapidly growing field of Semantic Search, including theory (Information Retrieval, Semantic Web data management) and applications from the Web and the enterprise context.
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://swrc.ontoware.org/ontology#keywords large-scale-processing
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http://data.semanticuniverse.com/resource/semtech-2011-4046 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://purl.org/dc/elements/1.1/description This presentation highlights the role semantic technologies in offering new search capabilities in Web search, vertical search and enterprise search. The tutorial offers an overview of theory, engineering issues and practical applications. In particular, we discuss: <P> -- Background from Semantic Web, Information Retrieval and Database literature <li><ul>Semantic Search tasks, including RDF retrieval and hybrid retrieval of data and documents</ul> -- Crawling and indexing -- Query processing and Ranking -- Evaluation of Semantic Search -- Demonstration of existing Semantic Search systems. <P> A basic familiarity with Semantic Web terminology is recommended for attending this tutorial. <P>
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/thanh-tran
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http://data.semanticuniverse.com/resource/semtech-2011-4046 http://www.w3.org/2000/01/rdf-schema#label Introduction to Semantic Search
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/peter-mika
http://data.semanticuniverse.com/resource/semtech-2011-4046 http://swrc.ontoware.org/ontology#keywords data-management
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://swrc.ontoware.org/ontology#keywords configure
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://swrc.ontoware.org/ontology#keywords manage
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://swrc.ontoware.org/ontology#keywords rules
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2011-06-07T11:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2011-3829 http://purl.org/dc/elements/1.1/description The software industry has long strived for an environment where a business user can easily define the business concepts, relationships and policies. Recently a team of developers using semantic technology and an expressive business language made a significant breakthrough. <P> Through demonstration and discussion of the technologies, the presenters explore how business users create, extend and alter high level business concepts, view concept dependencies, create natural language rules and instantly reveal the code behind the rules. <P> You will see the technologies including the ontology patterns, language and user interface breakthroughs that make this vision a reality. <P>
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://purl.org/dc/elements/1.1/title A Software Industry Breakthrough - Enabling Business Users to Define Rules and Configure the Semantic Enterprise
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://swrc.ontoware.org/ontology#keywords usability
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://purl.org/dc/elements/1.1/abstract See how a business user can easily define the business concepts, relationships and policies. Examine how semantic technology and an expressive business language power this significant breakthrough.
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/craig-d-hanson
http://data.semanticuniverse.com/resource/semtech-2011-3829 http://www.w3.org/2000/01/rdf-schema#label A Software Industry Breakthrough - Enabling Business Users to Define Rules and Configure the Semantic Enterprise
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