Information about http://data.semanticuniverse.com/resource/semtech-2010

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http://data.semanticuniverse.com/resource/semtech-2010-3147 http://purl.org/dc/elements/1.1/description The first part of this tutorial will provide an introduction to Description Logics (DLs), explaining what they are, how/why they are used to underpin the OWL ontology language, and the cost/benefit of using ontology systems. The second part will consider how reasoning systems for different OWL profiles are actually implemented, and address the future of ontology systems by reviewing some recent research. Topics include: Motivating the need for formal languages and specifications (semantics) Understand DLs as fragments of first order logic (FOL) Syntax and semantics of DLs, in particular the semantics of (description) logical entailment Discover how DLs provide the underpinning for the OWL ontology language <P>
http://data.semanticuniverse.com/resource/semtech-2010-3193 http://purl.org/dc/elements/1.1/description Wordnik is trying to amass as much relevant lexical information as possible about as many words of English as possible, including: <P> - traditional and discursive definitions - prototypical collocations - near neighbors in -nymy - frequency information - orthographic and pronunciation information - and "word rank" - the wordiness of any particular word <P> We're building this API-accessible data set for use by people doing higher-order tasks, and we're interesting in talking to folks who may want to use what we have, or have other needs we can mine from our 8bn word corpus of high-quality English text. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3193 http://purl.org/dc/elements/1.1/title Wordnik: 8 Billion Words You Can Use
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http://data.semanticuniverse.com/resource/semtech-2010-2827 http://purl.org/dc/elements/1.1/abstract To introduce and publicize the Rules Interchange Format (RIF), a new W3C standard for the semantic web, to a wide audience.
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http://data.semanticuniverse.com/resource/semtech-2010-2827 http://purl.org/dc/elements/1.1/description The RIF rules standard is a formal W3C recommendation for rules on the semantic web and interchange between different rule systems, and various communities are beginning to implement tools that support it. In this talk we will introduce RIF, its design and goals, and discuss its potential uses on the semantic web and to support interoperability. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2827 http://www.w3.org/2000/01/rdf-schema#label RIF: Rules for the Semantic Web
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http://data.semanticuniverse.com/resource/semtech-2010-2873 http://purl.org/dc/elements/1.1/title A Semantic Search, Semantic Clustering and Semantic Knowledge Base Engine for Health Information
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http://data.semanticuniverse.com/resource/semtech-2010-2873 http://purl.org/dc/elements/1.1/abstract Trusted, up-to-date and comprehensive health information is vital for well being.
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http://data.semanticuniverse.com/resource/semtech-2010-2873 http://purl.org/dc/elements/1.1/description Using trusted health information sites, semantic resources and the Web as a database, our research has focused on the automatic generation of a comprehensive Health Knowledge Base to power a next generation semantic search engine for current and reliable health information. <P> The presentation will cover the following topics: <ul> <li>trusted health information sources</li> <li>biomedical semantic resources</li> <li>linguistic, statistical and heuristic techniques and tools for health data mining </li> <li>the HealthMash search engine for consumer health information</li> <li>the FirstStep semantic health search engine at the National Institutes of Health Library</li></ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3027 http://purl.org/dc/elements/1.1/abstract Application of semantic technologies for knowledge management in healthcare and biomedicine with focus towards a specific discipline.
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http://data.semanticuniverse.com/resource/semtech-2010-3027 http://purl.org/dc/elements/1.1/description Semantic technologies have been aggressively applied in biomedical and healthcare domains to address a number of problems related to the representation, interpretation, integration and access of knowledge. These technologies include the development of machine readable thesauri and vocabularies, taxonomies, formal ontologies as well as NLP tools and techniques. And of course, there are emerging applications that are being developed to deal with these underlying metamodels.   <P> This case study discusses a semantic platform that incorporates these technologies and metamodels towards the collaborative development of a knowledgebase in Orthopaedics. The platform enables users to easily enhance local content with publications from various sources, blogs, discussions, annotations, and automatically tag them with domain-specific terms, as well as make this information accessible across the enterprise to other tools and applications via a semantic repository. <P> We will also describe the current challenges in achieving coherency and integration across medical subdomains, and describe some the design decisions taken to overcome some of these challenges. <P> We will address the following points: <ul> <li>Overview of semantic technologies in healthcare</li> <li>Challenges in semantic information integration across resources and applications</li> <li>Objectives of the project</li> <li>Discussion of technologies implemented</li> <li>Review of strengths and weaknesses of the current state of technologies in addressing knowledge management issues in healthcare</li> <li>Demo</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3027 http://purl.org/dc/elements/1.1/title Orthopaedia - A Semantic Platform for Collaborative Knowledgebase Development in Orthopaedics
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http://data.semanticuniverse.com/resource/semtech-2010-3248 http://purl.org/dc/elements/1.1/description *Concept of Semantic Social Network Analysis *Semantic SNA Architecture *SSAMZIE ? Semantic SNA *Case Study - Semantic email social network service - Semantic mobile social network and personalized services - Semantic social network service in research/public sector <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2785 http://purl.org/dc/elements/1.1/abstract Open government is based on the ideals of making information more visible, accessible and useful. This session will discuss the role of linked open data applied to open government architectures.
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http://data.semanticuniverse.com/resource/semtech-2010-2785 http://purl.org/dc/elements/1.1/title Open Architectures for Open Government
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http://data.semanticuniverse.com/resource/semtech-2010-2785 http://purl.org/dc/elements/1.1/description <h4>PART I (30 minutes) | Linked Open Architectures for Open Government</h4> <P> Cory Casanave, CEO<br> Model Driven Solutions<br> <P> Open government is based on the ideals of making information more visible, accessible, and useful. This session will discuss the role of linked open data applied to open government architectures to make government more visible, collaborative and participatory. <P> The information to better understand government, how to work with it and to leverage government data is trapped in hard to access architectures. Applying linked open data (LOD) to architectural information provides a mechanism to support open government while improving inter- and intra-government collaboration and data sharing. Linked open architectures for government include the description of government processes, services, structures and information - both at the business and technology levels. Opening up this data and linking it together makes it more valuable and more accessible. This session will demonstrate the value proposition and technical approach for achieving open government with linked open architectures. <P> <hr width="10%" /> <P> <h4>PART II (30 minutes) | Put Your Desktop in the Cloud to Support the Open Government Directive</h4> <P> Brand Niemann<br> Semantic Cloud Computing Evangelist<br> Semanticommunity.net <P> A Semantic Cloud Computing Desktop/Mobile Apps with Linked Open Data that consists of the following: <ul> <li>A database of "things" referenced by URL's</li> <li>A free Wiki (Deki Express) that was a "fork" from MediaWiki that evolved to a platform (web-services with a wiki interface) that further evolved to a Cloud Computing Internet Operating System Desktop</li> <li>A semantic publishing environment that supports use on Mobile Apps (e.g., iPhone) and Linked Open Data through MindTouch Extensions (e.g., App Catalog and Deki Mobile), conversion of the MySQL database to an RDF triple-store (e.g., DBpedia), and use with spreadsheet tools (e.g., Cambridge Semantics).</li> </ul> Now that Google and other search engines are reorienting rankings to favor inclusion of semantics and RDFa, this becomes a very strong argument for Linked Open Data for the government. <br><br><em>Disclaimer: This does not reflect the views of the U.S. Environmental Protection Agency and does not constitute endorsement by the EPA of the standards or products mentioned.</em> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3216 http://purl.org/dc/elements/1.1/title The Challenge of Building DoD Business Enterprise Architectures with Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2010-3216 http://www.w3.org/2000/01/rdf-schema#label The Challenge of Building DoD Business Enterprise Architectures with Semantic Technologies
http://data.semanticuniverse.com/resource/semtech-2010-3216 http://purl.org/dc/elements/1.1/description The U.S. Department of Defense is perhaps the largest and most complex organization in the world. Our reach is truly galactic. With about 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 early Proof of Delivery (PoD) projects designed to test the limits of both semantic technologies and the ability of the organization to use them effectively. Is this the breakout year? What remains to be done to achieve the tipping point? Could potential massive deployment by DoD success achieve the semantic technologies ?Tipping Point"? <P>
http://data.semanticuniverse.com/resource/semtech-2010-3216 http://purl.org/dc/elements/1.1/abstract This session will explore semantic technologies in the context of business intelligence and business applications and present the DoD's early Proof of Delivery (PoD) projects designed to test the limits of both semantic technologies and the ability of the organization to use them effectively.
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http://data.semanticuniverse.com/resource/semtech-2010-2974 http://purl.org/dc/elements/1.1/description The semantic web has been pivotal in integrating relevant Electronic Health Record (EHR) data from eight local hospitals for real-time bio-surveillance to detect infectious disease outbreaks like Influenza and potential bio-terrorist acts. The recent H1N1 scare has highlighted how vulnerable our country is and how vital it is to act swiftly to squash any potential pandemics. There has been improvements in the algorithms to discover outbreaks that impact public health, but a fraction of effort on how to arrive at meaningfully integrated data where the surveillance algorithms can be applied reliably. <P> The current generation of disease surveillance systems face several informatics challenges: <ul> <li>Finding relevant information in a sea of data</li> <li>Non-existent or poor adoption of standards by vendors</li> <li>Frequent change in the systems supplied by vendors</li> <li>Change in priorities and requirements (e.g., Avian vs. Swine flu)</li> <li>Unprecedented events requiring immediate action without time for coordination</li> </ul> We explore a novel approach that empowers public health responders to rapidly leverage their expertise to integrate and interpret patient information from multiple hospitals into one unified knowledge-base. This knowledge-base can then be used to respond swiftly to public health incidents while also being re-purposed for multi-disciplinary research in a distributed network of collaborators. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2974 http://purl.org/dc/elements/1.1/title The Hospital Dilemma: Integrating Electronic Medical Records for Detection of H1N1 Outbreaks (Poster Session)
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http://data.semanticuniverse.com/resource/semtech-2010-2974 http://www.w3.org/2000/01/rdf-schema#label The Hospital Dilemma: Integrating Electronic Medical Records for Detection of H1N1 Outbreaks (Poster Session)
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http://data.semanticuniverse.com/resource/semtech-2010-2974 http://purl.org/dc/elements/1.1/abstract To demonstrate how the semantic web has enabled heterogeneous Electronic Health Records from different hospitals to detect infectious disease outbreaks.
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http://data.semanticuniverse.com/resource/semtech-2010-3174 http://purl.org/dc/elements/1.1/title PelletDb: Scalable, Expressive Semantic Reasoning for the Enterprise
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http://data.semanticuniverse.com/resource/semtech-2010-3174 http://purl.org/dc/elements/1.1/abstract Our objective is to present PelletDb in the enterprise semantics space to attendees who may be evaluating commercial offerings in that space.
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http://data.semanticuniverse.com/resource/semtech-2010-3174 http://purl.org/dc/elements/1.1/description In this presentation we will describe use cases and applications of PelletDb 1.0 and discuss our roadmap for the 2.0 version. PelletDb 1.0 is the first and only OWL 2 reasoner for Oracle Database 11g R2, providing scalable and correct OWL reasoning. Built on Pellet 2.0 and Oracle Database Semantic Technologies, PelletDb provides an integrated solution for OWL 2 reasoning in the enterprise. New features in PelletDb 2.0 include expressing integrity constraints in OWL which are then automatically translated to SPARQL queries for closed-world validation of RDF instance data. PelletDb 2.0 will also include a next-generation OWL 2 QL reasoning system that provides scalable query answering over frequently changing data. Finally, we will also detail plans for RDBMS semantic facade with OWL 2. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3142 http://purl.org/dc/elements/1.1/description Salesforce.com is investing in social and collaboration applications for the enterprise (Chatter). Semantics and collaborative filtering plays an important role in these applications. In this talk we will explore how Salesforce.com is developing semantically aware and filtering functionality that is expected to greatly enhance the experience and improve productivity for enterprise users. We will discuss why and how semantic technologies enable these features in the short term and what we envision using in the future. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2886 http://purl.org/dc/elements/1.1/title Overview of Entity Extraction
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http://data.semanticuniverse.com/resource/semtech-2010-2886 http://purl.org/dc/elements/1.1/description Entity Extraction has become one of the key tools of the semantic web. Entity Extraction is a process of identifying key entities such as people, organizations, products, places and events in unstructured text documents and annotating these entities with precise semantic markup for future use. <P> This presentation will review the entity extraction process, compare architectures and patterns, and compare how various open source and commercial tools have recently evolved to meet the needs of the semantic web. We will also include demonstrations of entity extraction. <ul> <li>What is entity extraction, and why is it so challenging?</li> <li>What are the benefits of using annotated documents? (search, re-purposing, time line views, geo-mashups etc.)</li> <li>Architecture and patterns: linguistic pipelines, annotations, enrichment, POS tagging/RDF encoding</li> <li>Standards: XML, RDFa, Microformats, TEI, DITA etc.</li> <li>Are entity extraction web services right for you?</li> <li>Linking to domain specific controlled vocabularies: products, terms, people, places</li> <li>Case studies</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2886 http://swrc.ontoware.org/ontology#keywords xml
http://data.semanticuniverse.com/resource/semtech-2010-2886 http://purl.org/dc/elements/1.1/abstract Entity Extraction is becoming one of the key tools for transforming free-form text into useful information. This presentation is a broad overview of Entity Extraction technology.
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http://data.semanticuniverse.com/resource/semtech-2010-3110 http://purl.org/dc/elements/1.1/description SemTech Chairman Dave McComb, along with the help of some friends, reviews the state of semantics today. This popular warm-up session kicks off an intense week of education, networking, business and fun. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3110 http://purl.org/dc/elements/1.1/title What Will We Be Saying About Semantics This Year?
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http://data.semanticuniverse.com/resource/semtech-2010-2854 http://www.w3.org/2000/01/rdf-schema#label Exploring Schema Spaces in Linked Open Data
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http://data.semanticuniverse.com/resource/semtech-2010-2854 http://purl.org/dc/elements/1.1/title Exploring Schema Spaces in Linked Open Data
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http://data.semanticuniverse.com/resource/semtech-2010-2854 http://purl.org/dc/elements/1.1/abstract The explosion of linked RDF datasets are rapidly moving the industry forward. However, in practice the exploration of these data sources is far from trivial. We will discuss approaches that help the user explore linked datasets.
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http://data.semanticuniverse.com/resource/semtech-2010-2854 http://purl.org/dc/elements/1.1/description There is an explosion of linked RDF datasets, particularly in the life sciences domain. A typical RDF dataset published on the web is about one particular domain and contains both an ontology of the data that it contains, a set of instances, and possibly some explicit owl:sameas relations to other instances in other datasets. Most interesting problems require one to combine a large number of these datasets and then create queries and analysis programs that touch multiple sources. <P> In practice, the exploration of these data sources is far from trivial. First the domain expert has to study each dataset to find out what classes it contains and the properties that each class has. Unfortunately not all datasets come with full ontologies that make this easy. One has to reverse engineer which property belongs to which class and what datatype a typical property has. Secondly, the user has to figure out the linkage between particular datasets where the linkage might be through instance names or through owl:sameas relationships. Again the user has to reverse engineer these links mostly manual. <P> We will discuss a number of tools that help the user to explore linked datasets. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3086 http://www.w3.org/2000/01/rdf-schema#label The Practical Use of Rules with Ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-3086 http://purl.org/dc/elements/1.1/abstract to show how OWL 2 RL ontologies can be employed with rules using forward-chaining inference engines
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http://data.semanticuniverse.com/resource/semtech-2010-3086 http://purl.org/dc/elements/1.1/description Formal ontologies developed using RDF/OWL provide an ideal means for establishing a ?vocabulary of discourse? for a given domain through the definition of relevant classes and relationships. It is common practice to use an ontology as the basis for a data model implemented in a language such as Java or C++, around which applications are then developed. While this approach can be effective, the real value in using an ontology comes from the ontology language?s formal semantics that enable the automatic deduction of information implicit in the data assertions made using the ontology. <P> An inference engine or reasoner is commonly used to invoke the semantics of the language defined in terms of explicit formal axioms. Some reasoners are solely dedicated to ontological reasoning while others are more generic and can be used for purposes in addition to ontological reasoning. In most real-world problems, ontology languages such as OWL are able to capture some but not all of the knowledge required for the domain. This talk will focus on the use of generic forward-chaining inference engines to solve real-world problems using OWL 2 RL axioms to perform ontological reasoning in conjunction with a knowledge base of rules to perform higher level reasoning over the ontologically represented data. <P> Topics to be covered include the following: <ul> <li>What is OWL 2 RL and how is it implemented on forward chaining inference engines?</li> <li>What types of automatic inferencing can be achieved using OWL 2 RL?</li> <li>What types must be implemented as user defined rules?</li> <li>How can this approach be applied to practical problems?</li> <li>What open source and commercial forward-chaining inference engines are available?</li> <li>What are some of their strengths and weaknesses?</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3086 http://purl.org/dc/elements/1.1/title The Practical Use of Rules with Ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-3008 http://purl.org/dc/elements/1.1/title How to Make Linked Data More Than Data
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http://data.semanticuniverse.com/resource/semtech-2010-3008 http://purl.org/dc/elements/1.1/abstract We will present a querying framework for LOD datasets which requires no knowledge of the LOD cloud from the user. We present a qualitative evaluation of our system with other LOD querying systems based on real-world queries.
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http://data.semanticuniverse.com/resource/semtech-2010-3008 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2010-3008 http://swrc.ontoware.org/ontology#keywords lod-cloud
http://data.semanticuniverse.com/resource/semtech-2010-3008 http://purl.org/dc/elements/1.1/description The recent emergence of the ?Linked Data? approach for publishing data represents a major step forward in realizing the original vision of ?Semantic Web?. This new approach has resulted in the Linked Open Data (LOD) cloud, which includes more than 70 large datasets contributed by experts belonging to diverse communities. The growing number of datasets available on the LOD cloud presents various challenges with regards to its usage. Datasets such as DBpedia and Freebase offer massive amounts of information from diverse domains. However, there is no formal description of these datasets or any other LOD cloud components or their interlinking. The LOD cloud has a potential for applicability in many AI-related tasks, such as open domain question answering, knowledge discovery, and the Semantic Web. <P> An important prerequisite before the LOD cloud can enable these goals is allowing its users (and applications) to effectively pose queries to and retrieve answers from it. However, this prerequisite is still an open problem for the LOD cloud and has restricted it to ?merely more data.? To transform the LOD cloud from "merely more data" to "semantically linked data? there are plenty of open issues which should be addressed. We believe this transformation of the LOD cloud can be performed by addressing the shortcomings identified by us: lack of conceptual description of datasets, lack of expressivity, and difficulties with respect to querying. <P> For example consider the following query available from Jamendo: ?Select artists within Jamendo who made at least one album tagged as ?punk? by a Jamendo user, sorted by the number of inhabitants of the places where they are based.? Due to the lack of conceptual description of datasets, there is no mechanism to describe that Jamendo captures music related information and Geonames captures geographical information. Similarly, the lack of expressivity prohibits expression of multiple population figures for the same place. <P> To ease querying from an infrastructural perspective, data contributors have provided public SPARQL endpoints to query the LOD cloud datasets. However, in order to answer the query, the user first has to be familiar with multiple datasets. Then the user has to express the precise relationships between concepts in the RDF triple pattern. This process, even in trivial scenarios, requires browsing multiple datasets. The talk will present our analysis conducted on LOD datasets which identified these issues and the possible solution. We will also present a querying framework for LOD datasets which requires no knowledge of the LOD cloud from the user. Our system automatically maps user queries written in terms of a conceptual upper ontology to different LOD datasets. Then it creates a query plan and sends sub-queries to the different datasets. Finally, it merges the results and presents them to the user. We present a qualitative evaluation of our system with other LOD querying systems based on real-world queries posed by other researchers and practitioners. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3054 http://purl.org/dc/elements/1.1/abstract To unlock the promise and value of semantic technologies, they need to be made useful & accessible to the non-technical user.
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http://data.semanticuniverse.com/resource/semtech-2010-3054 http://purl.org/dc/elements/1.1/description Sean Martin, President & CTO of Cambridge Semantics, will discuss the current difficulties facing businesses considering semantic technologies, as well as the problems for vendors attempting to introduce them. Now that the W3C has established a sufficient core of open data standards, enterprises can safely invest in developing semantics-based solutions that minimize the risk of their obsolescence and assures future interoperability. <P> What remains for the enterprise is how to get started when the technical complexities of semantic technology distracts from focusing on business value. For vendors, there remains considerable challenges over how to educate enterprise purchasers on both the technology advantages as well as the business potential. The answer lies in removing the complexity from the end user. Introducing tools integrated through a comprehensive semantic platform allows the business to talk about realizing their value through capabilities without ever talking about the technology. For the business the word semantics and all the tech in semtech isn?t even discussed. <P> This session will explore the following topics: <ul> <li>To move from the value of the promise to the value of the project</li> <li>To deliver quick, semantically-enabled project wins</li> <li>Demonstrate how successful project execution helps to educate both the business and technical enterprise components</li> <li>Increased confidence and understanding unleashes creativity, leading to increasingly sophisticated opportunities and risk taking</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3275 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/steve-bastasini
http://data.semanticuniverse.com/resource/semtech-2010-3275 http://purl.org/dc/elements/1.1/abstract Business strategy and market trends in the Semantic Technology and Semantic Web space.
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http://data.semanticuniverse.com/resource/semtech-2010-3275 http://purl.org/dc/elements/1.1/description More companies in the Semantic Technology/Semantic Web space are looking to mergers and acquisitions (M&A) as a top strategy for building their product lines and customer bases or to expand their international reach. Evidence of this is the substantial deal volume in the SemTech space during 2009 and 2010, when transactions rose to the highest levels. Whatever the scale and scope or the relative size of the two partners, before, during and after a deal moves forward, the management team must agree on how the two businesses complement each other. <P> In this panel session we will discuss and analyze: <ul> <li>Why these Mergers and/or Acquisitions were completed</li> <li>What were the key strategies and value drivers involved</li> <li>The plans for integrating the newly acquired or merged companies</li> </ul> We will also explore how these companies will work together to: <ul> <li>Expand in a specific market segment, nationally or internationally</li> <li>Facilitate their best cost producer strategy</li> <li>Consolidate their business and/or technology platforms to expand their served markets as a basis for increased top line growth</li> <li>Determine what synergies have been created and how they will be used to their best advantage to address the market as a whole</li> <P>
http://data.semanticuniverse.com/resource/semtech-2010-3275 http://purl.org/dc/elements/1.1/title Mergers&amp;Acquisitions in SemTech
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http://data.semanticuniverse.com/resource/semtech-2010-3275 http://swrc.ontoware.org/ontology#keywords semtech-business-strategy
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http://data.semanticuniverse.com/resource/semtech-2010-3022 http://purl.org/dc/elements/1.1/abstract We will briefly describe Java Persistence Architecture (JPA) and how Empire can be used as an implementation of JPA, similar to Hibernate or Toplink, in Semantic Web applications.
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http://data.semanticuniverse.com/resource/semtech-2010-3022 http://purl.org/dc/elements/1.1/description Many existing J2EE applications use JPA, often via Hibernate or Toplink, to provide an ORM (Object-Relational mapping) layer over the database. Mappings between business objects represented as ordinary Java beans are created to drive persistence into the database, thus providing a powerful,y et straightforward environment to build applications. As Semantic Web apps become more prevalent there is a need for an OTM Object Triple Mapping) layer between the application and a SPARQL database. <P> Empire fills this need by implementing the JPA core, but using SPARQL and RDF, instead of SQL and an RDBMS. This talk will cover: <P> A brief description of Empire How Empire can be used within existing JPA applications Using Empire to generate your business/domain model in Java from an OWL ontology or RDF schema Features and limitations of Empire <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3022 http://purl.org/dc/elements/1.1/title Empire: RDF&amp;SPARQL Meet Java&amp;JPA
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http://data.semanticuniverse.com/resource/semtech-2010-2987 http://purl.org/dc/elements/1.1/abstract Increase awareness of the Open Ontology Repository Initiative, to attract more users and developers.
http://data.semanticuniverse.com/resource/semtech-2010-2987 http://purl.org/dc/elements/1.1/title Finding a Good Ontology: The Open Ontology Repository Initiative
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http://data.semanticuniverse.com/resource/semtech-2010-2987 http://purl.org/dc/elements/1.1/description Can you find a good ontology to use or extend for your application? <P> Building on previous registry and repository efforts, the Open Ontology Repository Initiative is a community effort developing open source software for finding, using, and maintaining open source and other ontologies. <P> The initial implementation of OOR is based on BioPortal (http://bioportal.bioontology.org), which is used to access and share ontologies that are actively used in biomedical communities and currently supports OWL, OBO, and Protege ontologies, LexGrid and RRF vocabularies, and ontology mapping. BioPortal has been developed by the National Center for Biomedical Ontology with suppport from the NIH Roadmap, but its infrastructure is domain-independent and being extended in various directions. <P> This presentation will include the following: <ul> <li>A demonstration of the current public OOR instance</li> <li>OOR requirements and challenges</li> <li>On-going and planned development efforts (Common Logic support, federation, gatekeeping, provenance, governance, etc.)</li> <li>Details on how you can become involved</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2923 http://purl.org/dc/elements/1.1/description <h4>PART I (30 minutes) | Data.gov</h4> <P> Suzanne Acar, Co-chair<br> U.S. Federal Data Subcommitte<br> <P> This presentation will discuss Data.gov as the evolving centralized catalog for US Government raw datasets and information feeds. Data.gov is an example of sharing government data that was not always easy to find, access, and re-use. The objective is to provide Federal Executive Branch non-sensitive datasets for third party creative re-use that help give citizens visibility into the actions of their government and to participate in the development of innovative solutions to the problems of the nation. <P> <hr width="10%" /> <P> <h4>PART II (30 minutes) | Data.gov.uk</h4> <P> Ian Davis, CTO<br> Talis <P> The UK Government recently unveiled its open data portal, data.gov.uk, containing hundreds of datasets from across all areas of government. Several of these were selected for conversion to RDF using a combination of manual analysis and automated extraction. The UK government also now mandates that any government department issuing a consultation-an opportunity for the public to comment on proposed policy changes-must add RDFa to their web-site in order to describe the consultation. This then allows other services to crawl this information and make all current consultations available in one place?something that was not previously available to the public, making this an important contribution to ?open government? . <P> The resulting triples are published using Linked Data standards and are queryable using SPARQL services. This session will cover the following topics: <ul> <li>The range of data available</li> <li>Standards for URI creation</li> <li>Tools used for conversion</li> <li>Examples of the converted data</li> <li>Sample applications</li> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2923 http://purl.org/dc/elements/1.1/title Transparent, Open Government with Linked Data - Data.gov and Data.gov.uk
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http://data.semanticuniverse.com/resource/semtech-2010-2923 http://purl.org/dc/elements/1.1/abstract A discussion and showcase of some of the Linked Data being published through the US and UK Government's open data portals
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http://data.semanticuniverse.com/resource/semtech-2010-2899 http://purl.org/dc/elements/1.1/description Digital information available as un/semi-structured data is estimated to comprise 53 percent of all available information in enterprises, and little of it makes way into data warehouses. In addition, state-of-the-art search technologies for accessing information from online sources produce highly efficient query issues but are ineffective in delivering targeted results. They provide little support to articulate complex queries which results in poor delivery and indexing of harvested information. <P> We present a generic, service-oriented semantic technology infrastructure called Knowle platform that uses a combination of text mining, ontologies, and reasoning techniques, and enables visual query navigation and data mining of un/semi-structured and structured data indexed with OWL-DL ontologies. Knowle has been applied to a variety of domains including healthcare & life sciences, business intelligence, patent landscaping and campaign management. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2899 http://purl.org/dc/elements/1.1/title KnowleSuite: Bringing Deep Search to End-Users with Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2010-2899 http://purl.org/dc/elements/1.1/abstract The objective of the presentation is to educate the audience of the different domains we have applied semantic technologies in Asia, Singapore.
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http://data.semanticuniverse.com/resource/semtech-2010-3344 http://purl.org/dc/elements/1.1/title Consuming Linked Data
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http://data.semanticuniverse.com/resource/semtech-2010-3344 http://purl.org/dc/elements/1.1/description In the past two years, the amount of data published on the Web as RDF and following the Linked Data principles has increased dramatically. Every day people are publishing datasets as Linked Data. However, applications that consume Linked Data are not mainstream yet. This talk will give a brief introduction to Linked Data and present different techniques in which users can currently consume Linked Data. We will also present existing applications that consume Linked Data. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3067 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2010-3067 http://purl.org/dc/elements/1.1/title RDF Friday Part 1: The ABCs of RDF Vocabularies
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http://data.semanticuniverse.com/resource/semtech-2010-3067 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-25T09:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3067 http://purl.org/dc/elements/1.1/description Everyone enjoys using Dublin Core, FOAF, Creative Commons and other existing RDF vocabularies, but how do you go about writing your own? This talk will be an introduction to what goes into creating a domain-specific vocabulary that is usable by humans and machines alike. We will start from scratch to create a simple vocabulary that gets progressively more sophisticated and ready for use. We will also borrow terms from other vocabularies to show how you can extend concepts across domains where it makes sense. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3067 http://purl.org/dc/elements/1.1/abstract A walkthrough of RDF and RDFS vocabulary development
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http://data.semanticuniverse.com/resource/semtech-2010-3288 http://purl.org/dc/elements/1.1/title Investment Banking, Structured Products, Open Datas and Semantic Technologies: a encouraging Success Story
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http://data.semanticuniverse.com/resource/semtech-2010-3288 http://purl.org/dc/elements/1.1/description Structured products are designed for existing or coming market and are driven by the same factors as consumer products. The market becomes partly more and more retail culture ? a fast growing number of highly skilled, informed private investors generate rumors, information?s and expertise ? and use the numerous sources with a web access. We will present one of our semantic solutions we have developed with one of the leading swiss investmentbanks monitoring the relevant part of the german internet including financial forums, Twitter, Blogs, social networks, and online news. This semantic solutions helps us to answer the following type of questions: 1. What are the new trends the financial communities are discussing that have a potential for a new structured product class? 2. Who are the relevant influencer in this specific discussion? 3. Which structured products are validated positively/negatively and what are the reasons for? 4. What are the positive aspects in a product class? 5. Where is the discussion running? Which are the dominating stakeholders? This presentation will include a series of real examples that highlight each of the major questions and shows the benefits of semantic technologies. We will give an outlook to other applications in the field of semantic technologies in the financial industries relying partly on open data like M&A, Anti Money Laundering, Anti Counterfeiting, Market Intelligence, Hedge Fund Observations. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3288 http://swrc.ontoware.org/ontology#keywords market-trends
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http://data.semanticuniverse.com/resource/semtech-2010-3288 http://purl.org/dc/elements/1.1/abstract Investment Banks must use open data to design new structured products that fit to the market trends. The market response on a large number of products can be analysed quick and sharp. Opinion leader can be identified.
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http://data.semanticuniverse.com/resource/semtech-2010-3035 http://swrc.ontoware.org/ontology#keywords applied-ontology
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://purl.org/dc/elements/1.1/abstract Ontology-Driven EILM is an end-to-end approach for the collaborative development, management, governance and implementation of ontologies and controlled vocabularies across any large enterprise. T
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://swrc.ontoware.org/ontology#keywords controlled-vocabulary
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2010-3035 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-2010-3035 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://purl.org/dc/elements/1.1/description As Semantic Web technologies evolve from theory to practice, semantically enabling legacy digital resources is emerging as a key application area. Ontology-Driven Enterprise Information Lifecyle management provides a mechanism for filling gaps, resolving conflicts, and aligning commonalities across disparate information resources (e.g., schemas). <P> Ontology Driven EILM: <ul> <li>Implements semantically aligned controlled vocabulary terms consistently throughout the enterprise</li> <li>Disambiguates enterprise information at a conceptual level that does not depend on enterprise consensus of term definitions</li> <li>Makes the meaning of controlled vocabularies and enterprise standards machine interpretable</li> </ul> Implementing Ontology-Driven EILM enables integrators to build a semantically interoperable global network of digital assets that alleviates information overload, more effectively leverages mission critical information, improves knowledge worker productivity, and mitigates legal liability. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://www.w3.org/2000/01/rdf-schema#label Ontology-Driven Enterprise Information Lifecycle Management
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://swrc.ontoware.org/ontology#keywords semantic-interoperability
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http://data.semanticuniverse.com/resource/semtech-2010-3035 http://swrc.ontoware.org/ontology#keywords semantic-soa.
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http://data.semanticuniverse.com/resource/semtech-2010-3035 http://purl.org/dc/elements/1.1/title Ontology-Driven Enterprise Information Lifecycle Management
http://data.semanticuniverse.com/resource/semtech-2010-3035 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mary-catherine-parmelee
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http://data.semanticuniverse.com/resource/matthew-m-vagnoni http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/matthew-m-vagnoni http://www.w3.org/2000/01/rdf-schema#label Matthew M Vagnoni
http://data.semanticuniverse.com/resource/matthew-m-vagnoni http://xmlns.com/foaf/0.1/name Matthew M Vagnoni
http://data.semanticuniverse.com/resource/matthew-m-vagnoni http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/1890.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/matthew-m-vagnoni http://www.w3.org/2001/vcard-rdf/3.0#title Scientific Programmer II / Ph.D. Student
http://data.semanticuniverse.com/resource/matthew-m-vagnoni http://www.w3.org/2001/vcard-rdf/3.0#org University of Texas at Houston, Health Science Center
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http://data.semanticuniverse.com/resource/semtech-2010-3003 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-2010-3003 http://purl.org/dc/elements/1.1/title Constructing Domain Ontologies and Integrating with the 'Universal Core Semantic Layer' to Facilitate Data Sharing and Intelligence Analysis
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://swrc.ontoware.org/ontology#keywords ucore-sl
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://swrc.ontoware.org/ontology#keywords ontology-development
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-22T17:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://purl.org/dc/elements/1.1/abstract Creating ontologies which model data sources and analysis models, then tying them to each other and to the new UCore SL, for automated data conversion, storage, and analysis.
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http://data.semanticuniverse.com/resource/semtech-2010-3003 http://swrc.ontoware.org/ontology#keywords universal-core
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://www.w3.org/2000/01/rdf-schema#label Constructing Domain Ontologies and Integrating with the 'Universal Core Semantic Layer' to Facilitate Data Sharing and Intelligence Analysis
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://swrc.ontoware.org/ontology#keywords cross-ontology-concept-correlation
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://purl.org/dc/elements/1.1/description The creation of the Universal Core Semantic Layer (UCore SL) ontology, as a supplement to the Federal Government's Universal Core XML-schema-plus-taxonomy standard, offers a good framework upon which to build a data model for intelligence analysis. Using it, we have devised a set of ontologies: A master based on UCore SL to capture concepts of interest to our analysts A set to model numerous relevant data stores A set to model relevant standard analysis models In this talk, we briefly describe the ontology development and some modeling challenges addressed in the process. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/richard-lee
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://swrc.ontoware.org/ontology#keywords data-conversion
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3003 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-22T18:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-3003 http://swrc.ontoware.org/ontology#keywords data-store-modeling
http://data.semanticuniverse.com/resource/christopher-john-matheus http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/christopher-john-matheus http://www.w3.org/2000/01/rdf-schema#label Christopher John Matheus
http://data.semanticuniverse.com/resource/christopher-john-matheus http://xmlns.com/foaf/0.1/name Christopher John Matheus
http://data.semanticuniverse.com/resource/christopher-john-matheus http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/1191.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/christopher-john-matheus http://www.w3.org/2001/vcard-rdf/3.0#title CTO
http://data.semanticuniverse.com/resource/christopher-john-matheus http://www.w3.org/2001/vcard-rdf/3.0#org VIStology, Inc.
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords application-development
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords system-integration
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://purl.org/dc/elements/1.1/description Companies invest huge costs in system integration and maintenance for business applications or services and business intelligence, which deduces business critical information from the data. IT departments spend up to 30 percent in modeling of data, ontologies or processes. The increasing dynamic and amount of data and number of sources is corresponding to an increasing demand of flexibility and speed in market cycles, product life cycles, and changing supply chains. The challenge still remains with conventional semantic technologies. <P> This presentation explains a different approach for semantic data integration and automatic real-time analysis without the need of modeling and maintaining ontologies. It shows step by step how to develop custom applications and services rapidly and derive business value through a dynamic IT infrastructure adopting itself to new and changing data and information requirements. <P> This session will cover: <ul> <li>Pain points of system integration and maintenance</li> <li>Limits of conventional business intelligence</li> <li>Uniform Information Layer for application and service development</li> <li>Uniform Information Layer for semantic definition of business without system knowledge</li> <li>Using automatic semantic analysis for advanced BI and information logistics</li> <li>Saving high scalability and flexibility</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords event-handling
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://purl.org/dc/elements/1.1/abstract The audience will learn how to develop business applications by saving costs for development and maintenance and overcome the limits of conventional approaches. They will be able to define the architecture and elements of a solution for their needs and how to derive business value.
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http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords semantic-analysis
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords soa
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords middleware
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jörg-h-wurzer
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords enterprise-architecture
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http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords business-intelligence
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords service-implementation
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http://data.semanticuniverse.com/resource/semtech-2010-2747 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-business-applications
http://data.semanticuniverse.com/resource/semtech-2010-2747 http://purl.org/dc/elements/1.1/title Solving the Pain Points of System Integration and Business Intelligence
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http://data.semanticuniverse.com/resource/semtech-2010-2747 http://swrc.ontoware.org/ontology#keywords real-time
http://data.semanticuniverse.com/resource/forward-look-inc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/forward-look-inc http://xmlns.com/foaf/0.1/name forward look, inc.
http://data.semanticuniverse.com/resource/forward-look-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/chito-jovellanos
http://data.semanticuniverse.com/resource/forward-look-inc http://www.w3.org/2000/01/rdf-schema#label forward look, inc.
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/semtech-2010-3224 http://purl.org/dc/elements/1.1/description Handling critical query loads in an efficient and resilient manner is not a trivial job even in architectures based on mature database management systems. We present a real-world scenario, where BigOWLIM is used to handle millions of requests per day, serving as a back-end, which seamlessly brings the power of the Semantic Web to the website of one of the largest and most popular television production companies in the World. The solution is based on BigOWLIM's Replication Cluster configuration, which allows load balancing, dynamic online re-configuration, and failover in order to guarantee a high performance "always on" service. To make the task even more challenging, the cluster performs non-trivial reasoning (through forward-chaining and materialization) on top of data which is being constantly updated. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/yosemite-b
http://data.semanticuniverse.com/resource/semtech-2010-3224 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-2010-3224 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-industry:-publishing
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://swrc.ontoware.org/ontology#keywords distributed-semantic-repository
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http://data.semanticuniverse.com/resource/semtech-2010-3224 http://purl.org/dc/elements/1.1/title OWLIM Cluster Allows Resilient Handling of Millions of Queries per Day
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://www.w3.org/2000/01/rdf-schema#label OWLIM Cluster Allows Resilient Handling of Millions of Queries per Day
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://swrc.ontoware.org/ontology#keywords television
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/atanas-kostadinov-kiryakov
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://swrc.ontoware.org/ontology#keywords reasoning
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://swrc.ontoware.org/ontology#keywords 24x7
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http://data.semanticuniverse.com/resource/semtech-2010-3224 http://purl.org/dc/elements/1.1/abstract BigOWLIM is used to handle millions of requests per day, serving as a back-end for the website of one of the most popular television production companies in the world
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http://data.semanticuniverse.com/resource/semtech-2010-3224 http://swrc.ontoware.org/ontology#keywords high-performance
http://data.semanticuniverse.com/resource/semtech-2010-3224 http://swrc.ontoware.org/ontology#keywords resilience
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http://data.semanticuniverse.com/resource/semtech-2010-3224 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/fransciscan-d
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://purl.org/dc/elements/1.1/description Much current financial regulators attention is focused on benefits of XBRL and development of standardized taxonomies for creating XBRL documents. This presentation focuses on the use of XBRL data, starting with Search capability. We show why text-based search engines like Google are insufficient for XBRL documents and Semantic Web technologies of SPARQL and RDF meet the objectives. <P> Highlights include: <ul> <li>XBRL files are a collection of semantically inter-related XML documents that are not easily searchable</li> <li>RDF-based linked-data supports SPARQL as the standard, distributed search technology</li> <li>Extracting XBRL data in RDF format SPARQL endpoints enables fast and cost-effective searches</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-23T17:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-2936 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-23T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ashu-bhatnagar
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://purl.org/dc/elements/1.1/title Semantic XBRL Data Search Using SPARQL
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-semantic-search
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://swrc.ontoware.org/ontology#keywords xbrl
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://www.w3.org/2000/01/rdf-schema#label Semantic XBRL Data Search Using SPARQL
http://data.semanticuniverse.com/resource/semtech-2010-2936 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-2010-2936 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://swrc.ontoware.org/ontology#keywords semantic-tagging
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http://data.semanticuniverse.com/resource/semtech-2010-2936 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2010-2936 http://swrc.ontoware.org/ontology#keywords semantic-search
http://data.semanticuniverse.com/resource/semtech-2010-2936 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-2010-2936 http://purl.org/dc/elements/1.1/abstract SPARQL makes Semantic XBRL searches possible on-demand across a distributed web space while simplifying front-end design, and keeping the complexity of technology hidden and out of sight from end users.
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http://data.semanticuniverse.com/resource/sandia-national-laboratories http://xmlns.com/foaf/0.1/name Sandia National Laboratories
http://data.semanticuniverse.com/resource/sandia-national-laboratories http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/bettina-k-schimanski
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http://data.semanticuniverse.com/resource/sandia-national-laboratories http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/jennifer-miller
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http://data.semanticuniverse.com/resource/semtech-2010-3168 http://purl.org/dc/elements/1.1/description Sentiment analysis, listening platforms, actionable intelligence ? the semantic web is enabling new ways of measuring, engaging and responding to your audience. How should you communicate during times of crisis, how can you use listening platforms to guide pricing policies, and what features of your new product are REALLY going to help it sell? This panel will discuss the challenges and opportunities in measuring market sentiment, and how the results can be used to drive your marketing strategies and actions. <P> How do you track the sources of negative (or positive) sentiment? How do you know which sources to monitor? How do you filter the huge volumes of potentially valuable data, and focus on the portion that really matters to your success? What are the technical limitations? The language constraints? And how do these systems handle contemporary colloquialism, abbreviations and idioms? Context plays a major part in understanding - the language in a major newspaper differs from a discussion forum, which in turn differs from Twitter. Furthermore, different content domains have different slang ? what signifies a positive sentiment for a financial company may be neutral or even negative when applied to a celebrity. <P> It is important not only to assess the sentiment, but to understand what drives it. Semantic analysis can identify key topics raised in public discussions, and appropriate software can create maps of issues on-the-fly. But what do you do with this information? Making the metrics actionable is critical, and ultimately where the payoff lies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3168 http://purl.org/dc/elements/1.1/abstract How to understand and measure the sentiment of your audience and turn that into appropriate actions.
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http://data.semanticuniverse.com/resource/semtech-2010-3182 http://purl.org/dc/elements/1.1/abstract Semantic web technology offers sophisticated ways to manage metadata. Publishers feel financial pressure to improve their metadata management. How can semantics be an agent of change for a culture steeped in tradition.
http://data.semanticuniverse.com/resource/semtech-2010-3182 http://purl.org/dc/elements/1.1/description <h4>PART I | Semantic Web Technology and the Publishing World: What Can They Offer Each Other?</h4> <P> Bob DuCharme, Solutions Architect, TopQuadrant <P> As publishers watch print revenue decline, they're drawn to various aspects of semantic technologies. "Semantic search" vendors have convinced some that it may be a magic wand that connects more content to more customers, but often with greater dependencies on proprietary technology than on standards-based approaches. <P> Other publishers see better metadata management as a key to their future. In addition to helping customers and production staff find the right content more quickly, better metadata reduces the time and costs of determining what rights a publisher has to use which content in which media?a growing problem in the industry. <P> The semantic world has the standards, techniques, and tools (in that order) to provide this, but talk of blank nodes and open world assumptions frightens off many publishers. Examining aspects of how both sides look at the same issues from different angles can help both address those issues better. For example: <ul> <li>Publishers see overlapping, confusing metadata standards; ontology standards can help to sort and find the right connections between these standards.</li> <li>Academics develop ontologies paying more attention to development techniques than to the actual use of the ontologies; publishers' content is real data that can contribute more to their business with better ontologies.</li> <li>The relational and XML worlds tell publishers that data management starts with fixed schemas; the semantic web world offers them the schema flexibility that they need to accommodate different sets of metadata from different sources.</li> <li>Publishers' long experience with XML and SGML has taught them how to think about data structures that don't fit into relational tables.</li> <li>Newer, higher-level semantic web standards such as SKOS and RDFa help connect semantic web theory to publishing practice.</li> <hr width="10%" /> </ul> <P> <h4>PART II | Added Value Services of Financial Newspapers with Semantic Technology</h4> <P> Luca Scagliarini, VP Strategy & Business Development, Expert System<br> <P> Il Sole 24 Ore is one of the leading daily newspaper publishers in Italy, providing news and information services about politics, the economy, legislation and Italian and international financial markets. <P> Semantic technologies are used to support Il Sole 24 Ore in three important aims: <ol> <li>To increase the monetization of content by both enhancing the relevance of information presented to our customers, and improving the effectiveness of our SEO and SEM activities.</li> <li>To improve the user experience on our portal http://www.sole24ore.com/, through the implementation of innovative solutions.</li> <li>To introduce new efficiencies in our publishing activities through automation in the analysis and classification of content.</li> </ol> Sole 24 Ore efforts in these three areas brought value on both sides of the business case equation through both revenue enhancement and cost efficiencies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3104 http://purl.org/dc/elements/1.1/description Social networks are a natural fit for semantics. The opportunities for connecting people and analyzing social content are enormous. This panel will present some approaches and tools that combine semantics with social network data, visualization of relationships, measurement and interactions, and user-generated content analysis. <P> This session will explore the following topics: <ul> <li>How can we use the Social Web to detect and observe signals from real time social data?</li> <li>How to study diversity and change, identify patterns of interactions, and extract insights</li> <li>What can we learn about social perceptions of real time events?</li> <li>Tools for visualization and analysis in space, time and theme</li> <li>Can social network analysis be trusted?</li> <li>Capturing social network content to track and analyze buyer preferences, shopping experience, demographics, and other characteristics that influence purchasing behavior</li> <li>How to factor in quality control, Internet jargon, keyboard symbols, extreme word-shortenings, non-standard vocabulary, grammatical and spelling errors</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2848 http://purl.org/dc/elements/1.1/abstract Summary of the findings and outcome of the semantic research project conducted in partnership with Semantic Universe.
http://data.semanticuniverse.com/resource/semtech-2010-2848 http://www.w3.org/2000/01/rdf-schema#label Semantics in Publishing and Media: Recent Research Results
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http://data.semanticuniverse.com/resource/semtech-2010-2848 http://purl.org/dc/elements/1.1/description In January 2010, the Razorfish Media & Entertainment practice, along with research partner Semantic Universe, set out to chart how media and publishing companies are adapting to the demands of the digital content landscape. Who is pushing the envelope and how? What technologies can be applied in new and interesting ways? What lessons can be put to use in your own organization? <P> To explore these ideas we went straight to the experts, in over 20 interviews with people on the ground at The New York Times, the BBC, the Wall Street Journal, TalkingPointsMemo, CBS Interactive, and Next Issue Media, as well as with semantic technology experts who have been exploring ways that linked data can change content experiences (Many of whom will be speaking at this conference). <P> The result was a report called Nimble. This presentation will provide an overview of the report, discuss the implications, and talk about what?s next. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2848 http://swrc.ontoware.org/ontology#keywords prototype
http://data.semanticuniverse.com/resource/semtech-2010-2848 http://purl.org/dc/elements/1.1/title Semantics in Publishing and Media: Recent Research Results
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http://data.semanticuniverse.com/resource/semtech-2010-2894 http://purl.org/dc/elements/1.1/abstract This tutorial introduces common, easy to use techniques in the designer's toolkit, as well as exploring approaches needed to achieve good design given the unique attributes of semantic technologies.
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http://data.semanticuniverse.com/resource/semtech-2010-2894 http://purl.org/dc/elements/1.1/title Semantic Web Interface Design: Opportunities and Techniques
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http://data.semanticuniverse.com/resource/semtech-2010-2894 http://purl.org/dc/elements/1.1/description Designing for the web?and increasingly the semantic web?is a blend of art and science. The science is taught through exercises that expose simple, applicable techniques. The art is encouraged by providing examples of well-designed sites, along with a framework for how to examine sites for adoptable attributes. <P> Participants will: Gain an overview into determining good user-experience design Practice some simple techniques that help open up design ideas and options Apply a framework for how to review site designs, looking at user goal accomplishment and the overall experience to assess what works Identify where and how to effectively involve actual users in the analysis > design > evaluation process <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3048 http://purl.org/dc/elements/1.1/title A Jena-based Framework for Semantic Enterprise Information Integration (SEII)
http://data.semanticuniverse.com/resource/semtech-2010-3048 http://purl.org/dc/elements/1.1/abstract A framework is proposed for integrating collaboration, applications data and processes within an enterprise to achieve semantic information integration. Such a framework can be a powerful complement to EII or MDM strategies in large enterprises.
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http://data.semanticuniverse.com/resource/semtech-2010-3048 http://www.w3.org/2000/01/rdf-schema#label A Jena-based Framework for Semantic Enterprise Information Integration (SEII)
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http://data.semanticuniverse.com/resource/semtech-2010-3048 http://purl.org/dc/elements/1.1/description EII (Enterprise Information Integration) and MDM (Master Data Management) have been the leading strategies in large enterprises for data integration across business functions. Initiatives driven by these strategies have been deployed successfully and proven effective in providing data consistency to business units as well as reducing costs of data maintenance. They also provide powerful analytics and business intelligence capabilities. <P> Semantic web technologies can offer a powerful complement to EII. Through the implementation of application-specific, collaboration and process ontologies, integration transcends from application data to the semantics of that data. Repositories may be central or federated across the enterprise - but they still provide a unified view of information. This level of semantic information integration may be tool or application-agnostic, domain-specific and easy to implement via a supporting framework. <P> This presentation discusses a Jena-based architecture for semantic enterprise information integration. This architecture has been implemented to integrate collaboration and tools within software engineering. It is also equally applicable in other areas. The resulting semantic information network can provide unique dashboards to decision makers. <P> In this session, we will address the following: <ul> <li>EII versus Semantic EII (SEII)</li> <li>Role of ontologies and metamodels in SEII</li> <li>A framework for SEII based upon Jena</li> <li>Proposed connector architecture for integrating applications and tools</li> <li>Demo</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3094 http://purl.org/dc/elements/1.1/description The Semantic Web standards of the W3C were designed with global scale in mind, addressing the issue of how information can be shared on the World Wide Web. Enterprise applications of Semantic Web technology have traditionally downplayed the global nature of the Semantic Web, using the technology as a way to respond to increasing need for flexibility in their data management. We see increasing uptake in a wide variety of industries, including energy, health care, publishing and security, as well as some of the early adopters, government and life sciences. <P> But enterprises are finding that they are more like the Web than meets the eye. More and more, enterprises internally look like the Web, made up of multiple components with varied histories who have to share information in order to survive. Semantic Web solutions aren't just a better way to solve certain information management problems: a Semantic Web approach is an essential part of a successful enterprise data strategy. <P> The drive pushes outside the enterprise. More industries are recognizing the value of 'pre-competitive' collaboration, efforts in which competing companies sit down at the same table, working together, to increase the common level of knowledge in an industry. This isn't a pipe-dream of a future world-it is a reality happening today. And the Semantic Web is an integral part of it, smoothly connecting intranet with internet in a global knowledge economy. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3283 http://purl.org/dc/elements/1.1/abstract Part I will show how Semantic Technologies can enhance the Intelligence Cycle employed by homeland-security, law-enforcement and Competitive Intelligence agencies. Part II will provide an ontology development case study focusing on the creation of an ontology designed to model aspects of the IT security domain with a goal of providing a higher level of data interoperability between heterogeneous viewpoints within the domain.
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http://data.semanticuniverse.com/resource/semtech-2010-3283 http://purl.org/dc/elements/1.1/description <h4>PART I | Harnessing Semantic Technologies for Intelligence</h4> <P> <i>Oren Yosifon, Chief Technology Officer, MindCite</i> <P> Semantic Technologies allow unprecedented capacity for information analysis and fusion. Knowledge harvested from unstructured-data and from structured-data can be easily combined, reasoned upon, and shared. This is important for law enforcement and government agencies, as well as for competitive intelligence bodies in the private sector. <P> This presentation will demonstrate how Semantic Technologies can help each step in the Intelligence Cycle, most notably: <ul> <li>Streamline and simplify PIR (Priority Intelligence Requirements)-driven collection</li> <li>Help fuse information from diverse sources</li> <li>Reduce noise and improve accuracy of information-retreival</li> <li>Enhance knowledge sharing among analysts</li> <li>Help uncover activity-patterns (modus operandi), and implicit relationships between entities</li> </ul> <P> <hr width="10%" /> <P> <h4>PART II | Semantic Interoperability in IT Security: Ontology for IT Product Representation</h4> <P> <i>Paul Cichonski, Software Engineer, Booz Allen Hamilton / NIST</i> <P> This session will begin with a short introduction to the concepts and goals of the National Institute of Standards and Technology (NIST)Security Automation Program, as well as a brief description of the problems faced by the National Vulnerability Database (NVD), which is the primary repository of security automation content within the federal government. <P> We will show how interoperable data solutions are required in the IT security domain to allow for successful communication of critical security alerts between organizational stovepipes and disparate security products. The most important part of any solution is the ability to represent IT product data in a standardized way that will allow disparate organizations to communicate about unique IT products. <P> The majority of the session will focus on an ontology being developed by NIST to model IT product information. This ontology facilitates unique product enumeration as well as the creation of complex relationships required to relate groupings of products to other IT security concepts, such as IT vulnerabilities and configuration checklists. <P> This session will also address the following points: <ul> <li>What can semantic technologies offer for IT Security?</li> <li>How semantic technologies can allow disparate organizational domains to describe IT products in an interoperable fashion</li> <li>How a common language for speaking about IT products and IT security will improve multi-vendor interoperability while lowering the operational cost of security and compliance</li> <li>An overview of ontology modeling IT products and their relation to other IT security concepts</li> <li>An overview of ontology modeling constructs used to describe complex groupings of products</li> <li>An overview of ontology modeling constructs designed to support useful inferencing</li> <li>Future uses of semantic technologies within the IT security domain</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3205 http://purl.org/dc/elements/1.1/title Using Semantics to Leverage Information Hidden in Excel: 2 Case Studies
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http://data.semanticuniverse.com/resource/semtech-2010-3205 http://purl.org/dc/elements/1.1/abstract This session presents two case studies showcasing the power of semantic technology in leveraging corporate data found in Excel spreadsheets to drive savings and revenue growth in two global corporations.
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http://data.semanticuniverse.com/resource/semtech-2010-3205 http://purl.org/dc/elements/1.1/description Knowledge workers use Microsoft Excel in nearly every aspect of running a business, from departmental budgeting, to project and program management, to ad hoc reporting and analysis, to risk analysis, and beyond. It has become a truism that half of a corporation's data exists in spreadsheets. Unfortunately, however valuable the information represented in a spreadsheet might be, it is effectively a silo managed by a single expert user and as such cannot easily be reused, reported on, integrated with other information, tracked, or audited. IT has been trying to solve this Excel problem for decades, with CIO Magazine even going so far as to call Excel the "cockroach of IT" while simultaneously awarding it the distinction of being the Enterprise Application of the Decade. <P> Semantics now makes it possible to integrate information and processes represented in Excel spreadsheets with the standard corporate information infrastructure for reporting, auditing, analysis, and compliance. In this session, Rob Gonzalez, Cambridge Semantics's Senior Product Manager, will present two real-world case studies where semantic technologies were used to integrate so-called "Shadow IT" data found in spreadsheets. Thousands of man-hours of development effort and millions of dollars of investment were saved. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2949 http://purl.org/dc/elements/1.1/description Web Ontology Language (OWL) is a powerful knowledge representation language that can be used to express data semantics in a formal language that is amenable to automated reasoning and validation. However, in many real-life applications, developers face problems with OWL because it does not allow Closed World reasoning. If certain information cannot be inferred from what is already known, it cannot be assumed false in OWL. Without Closed World assumption, what would trigger a constraint violation in a traditional RDBMS causes an OWL reasoner to compute new inferences. This behavior causes problems in cases where knowledge about the domain is known to be complete. One way to overcome this problem is to treat some parts of an OWL ontology (designated by the ontology engineer) as integrity constraints rather than inference rules. This talk describes such an approach along with other methods that enable combining open world reasoning with closed world validation in a principled way. <P> This talk will cover the following points: <ul> <li>Differences between open world and closed world reasoning</li> <li>Common problems developers face regarding open world reasoning building OWL-based applications</li> <li>Integrity Constraints semantics for OWL via SPARQL</li> <li>Incorporating other forms of closed world reasoning into OWL</li> <li>Using the Pellet OWL 2 reasoner with closed world assumption</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2949 http://www.w3.org/2000/01/rdf-schema#label Using OWL in Closed World Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2949 http://purl.org/dc/elements/1.1/abstract Describe the differences between open world and closed world reasoning, discuss common problems developers face building OWL-based applications, and explain solutions to these problems such as integrity constraints semantics for OWL.
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http://data.semanticuniverse.com/resource/semtech-2010-3251 http://purl.org/dc/elements/1.1/description This workshop will demonstrate how vision, concise engineering and 10 years of experience can deliver successful applications of semantic technology. We will present how RDF databases and light-weight semantics guarantee unmatched efficiency in data integration for the publishing industry in two scenarios: as a back-end for the web site of a top-5 television company and as part of Profium?s content delivery platform. Further, we will show how RDF-based data management can be combined with tailor-made text analytics and web mining to produce business intelligence and professional search applications within short timeframes and limited budgets. The agenda will include presentation of the latest progress in our product range: the most scalable semantic repository OWLIM, the semantic annotation and search platform KIM and the life science knowledge management platform LifeSKIM. We will present the reason-able views paradigm for linked data management, which enables the usage of Linking Open Data (LOD) datasets in enterprise applications. The FactForge view includes the central LOD datasets (e.g. DBPedia, Geonames and Freebase) in a repository containing 1.2B explicit statements. The LinkedLifeData view includes 20+ biomedical datasets with a total size of over 4B statements. In summary, the workshop attendants will learn: What the key principles are behind an efficient semantic technology application What the key steps in building text-mining solution are What is the role of different tools and components in specific scenarios and workflows How linked data prove that Nietzsche is the most famous German entertainer How to locate Modigliani paintings based on linked data queries <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2875 http://purl.org/dc/elements/1.1/abstract The presentation will describe how certain tasks in semantic content creation require human contribution and how the human user can be motivated in various scenarios to get involved.
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http://data.semanticuniverse.com/resource/semtech-2010-2875 http://purl.org/dc/elements/1.1/title Reputation, community, Web 2.0, and games: incentives for semantics ? about getting people involved
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http://data.semanticuniverse.com/resource/semtech-2010-2875 http://purl.org/dc/elements/1.1/description The European project INSEMTIVES (www.insemtives.eu) is seeking to bridge the gap between technology and the creation of semantic content by applying different incentive models to tools and applications, lowering the entrance barriers to implementation. This presentation will describe these tools, as well as outline two case studies. <P> Topics include: The role of human contribution in semantics Incentive models for semantic content creation (Games, Challenges, Reputation, etc.) Case study: Multimedia annotation in virtual worlds (game) Case study: incentives for annotation in corporate knowledge management <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3200 http://purl.org/dc/elements/1.1/abstract Oracle Database Semantic Technologies provide a scalable persistent RDF/OWL store that takes advantage of the inherent reliability and transactional support provided by the Oracle Database.
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http://data.semanticuniverse.com/resource/semtech-2010-3200 http://purl.org/dc/elements/1.1/description As semantic repositories grow to tens of billions of triples, databases and storage technologies must seamlessly scale and perform. Oracle Database Semantic Technologies provide a scalable persistent RDF/OWL store that takes advantage of the inherent reliability and transactional support provided by the Oracle Database. <P> To cater to the needs of enterprises and government organizations, security in the RDF/OWL store is provided at the granularity of a resource. To allow transactions involving concurrent changes by multiple developers over long durations, the notion of private workspaces provide a hierarchy of logical versions of the RDF store. <P> SQL-based SEM_MATCH queries offer the capabilities of SPARQL while simultaneously allowing queries to span both relational and RDF data. Additionally, relational and textual content can be explored with greater efficiency through the notion of semantic indexes and ontology-assisted relational queries. <P> The Oracle RDF store can be accessed using Java APIs including the popular open-source Jena and Sesame. SPARQL service endpoints, with sophisticated query execution management capabilities, are enabled using either Jena Adapter with Joseki or Sesame Adapter with Sesame Server. W3C Standards for RDF, RDFS, OWL, SPARQL and SKOS are supported, including OWL expressiveness to store and manage complex ontologies such as SNOMED. User defined rules are allowed to further extend the semantics supported. Interfaces are also available to supplement the native parallel and incremental inferencing algorithms with external inference engines such as Pellet. External entity extraction and language understanding tools can feed RDF data for semantic indexing of documents. <P> Participants will gain an understanding of the above capabilities and learn about the performance characteristics and best practices of the Oracle database implementation of semantic technologies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3200 http://purl.org/dc/elements/1.1/title Semantic Technologies in Oracle Database 11gR2: Capabilities, Interfaces, Performance
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http://data.semanticuniverse.com/resource/semtech-2010-2944 http://purl.org/dc/elements/1.1/title Building User Interfaces for Semantic Web Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2944 http://purl.org/dc/elements/1.1/description While the size of the Linked Data cloud is growing rapidly, most user interface frameworks are still rather simple. Often, RDF data is displayed in tabular form with name/value pairs. Frameworks such as Fresnel and LESS are emerging to allow ontology designers and users to annotate classes with metadata so that user interface engines can select more attractive views on the underlying data instances. <P> This face-to-face meeting aims at bringing together practitioners to explore which user interface generation frameworks are working well in the real world, and which limitations have been hit. A possible outcome might be to come up with a list of requirements that could lead to a W3C standard for RDF-based user interface descriptions. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2944 http://purl.org/dc/elements/1.1/abstract A face-to-face meeting for developers interested in ontology-based frameworks for generating user interfaces. Topics include linked data browsers and user interface metadata frameworks such as Fresnel.
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http://data.semanticuniverse.com/resource/semtech-2010-3176 http://purl.org/dc/elements/1.1/title Using Knoodl.com to Facilitate the Human Resource Enterprise Information Web (HR-EIW) for the U.S. Dept. of Defense
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http://data.semanticuniverse.com/resource/semtech-2010-3176 http://purl.org/dc/elements/1.1/description The Enterprise Information Web project (EIW) is radically changing the information management paradigm at the U.S. Department of Defense (DOD). EIW is implementing a "federated" information management architecture using semantic web standards RDF, OWL and SPARQL, building on top of the existing Net Centric infrastructure (HTTP, URL, XML, web services). In a federated architecture, the various services and agencies that are part of DOD each manage their own systems, but they are described with OWL models and ontologies, so that the total collection of information is a queryable web of data. <P> The core of the approach is the creation of domain vocabularies by each service using a community-based OWL modeling tool knoodl.com. We will show the methodology and best practices to enable this architecture. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2888 http://swrc.ontoware.org/ontology#keywords taxonomies
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http://data.semanticuniverse.com/resource/semtech-2010-2888 http://purl.org/dc/elements/1.1/description Knowledge-based applications offer solutions for a variety of problems related to searching, finding, and acquiring new knowledge. To encourage the wide industrial uptake of knowledge-based technologies, instruments to assess potential economic benefits of these technologies and to predict the total costs of their development and deployment are a must. The aim of this presentation is to introduce methods that produce quantitative estimates of the costs and benefits of knowledge-based applications. In order to ensure validity of these models, we rely on a predicative framework that outlines a detailed track on how such models should be derived. Following this framework, we identify functionalities and consider relevant factors with respect to costs and benefits. Based on these factors, we propose an initial set of cost/benefit methods. Most notably, these methods are applicable to a wide range of knowledge structures, such as ontologies, taxonomies and folksonomies, but also to the software applications using them. They leverage experience in engineering knowledge-based applications and a survey of over 150 projects in academia and industry. <P> In this presentation, we'll address the following topics: <ul> <li>Explain how to estimate and manage the efforts related to developing and maintaining ontologies, taxonomies and folksonomies</li> <li>Introduce methods to quantify the benefits of knowledge-driven technologies in a number of key information management scenarios</li> <li>Describe a case study at a globally acting telecommunications operator, in which different types of knowledge structures have been used to create intelligent information management solutions that maximize the productivity of knowledge workers</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2888 http://purl.org/dc/elements/1.1/abstract The aim of the presentation is to introduce a suite of methods for estimating and managing the costs of developing and maintaining ontologies and other related knowledge structures, as well as the benefits associated with their usage in typical technological use cases in information management.
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http://data.semanticuniverse.com/resource/semtech-2010-2888 http://purl.org/dc/elements/1.1/title Estimating and Managing the Costs and Benefits of Knowledge Structures
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http://data.semanticuniverse.com/resource/semtech-2010-3190 http://purl.org/dc/elements/1.1/title RDF Friday Part 2: Intermediate Technical Issues - Extending and Querying RDF
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http://data.semanticuniverse.com/resource/semtech-2010-3190 http://purl.org/dc/elements/1.1/description <h4>PART I | Resource Identity and Semantic Extensions: Making Sense of Ambiguity</h4> <P> David Booth, Software Architect, Cleveland Clinic <P> What does a URI denote? How should its referent be determined, even in the presence of semantic extensions that affect the interpretation of an RDF graph? How should ambiguity be viewed? <P> One view is that a given URI has no fixed referent, but may denote different things in different contexts. Another is that each URI should have a URI declaration that precisely delimits its interpretation. Some suggest reusing existing URIs in new contexts, while others prefer to mint new URIs and then allow owl:sameAs assertions to indicate that two URIs denote the same thing. <P> This presentation sheds light on these issues by explaining how ambiguity of a URI's referent fits within standard RDF semantics, how this ambiguity applies to the use of owl:sameAs, and proposes a standard operational sequence for determining the intended referent of a URI, even in the the presence of semantic extensions. <hr width="10%" /> <P> <h4>PART II | RDF as a Query Language</h4> <P> James Leigh, Senior Software Consultant, Zepheira, LLC David Wood, Partner, Zepheira, LLC <P> RDFa makes creating and publishing RDF as easy as writing HTML, but RDFa can also make querying RDF just as easy. <P> This session explores how to use RDFa to query by example. Learn how to construct complicated SPARQL queries using the familiar syntax of HTML and RDFa. Using the Callimachus framework (http://callimachusproject.org), HTML documents with RDFa markup are used as templates to automatically construct SPARQL queries, query an RDF datastore and construct the resulting Web page. <P> The Callimachus framework's architecture, syntax and usage will be presented with a focus on the use of RDFa as a query language. By the end of the session, experienced Web authors should be ready to create their own Semantic Web applications. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3088 http://purl.org/dc/elements/1.1/description Rule standards not only increase the interoperability and openness of rule applications, they also increase the usefulness and the usability of many semantic technologies and improve development productivity and quality. In this session, we will introduce the various standards related to semantic rules, describing the problems they solve and where they fit in the process of developing and maintaining rule applications. <P> We will cover the OMG's SBVR (Semantics of Business Vocabulary and Rules) and PRR (Production Rule Representation), W3C's RIF (Rule Interchange Format), and the JCP's JSR 94 (Java API for Rule Engines) with a short introduction to the technical content of each specification. <P> We will explain how they relate to each other and to other standards such as W3C OWL, and we will discuss how they can be used separately and in conjunction. We will also cover implementation, from both the implementer and the user point of view. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3088 http://purl.org/dc/elements/1.1/abstract Introducing the various standards related to semantic rules, describing the problems they solve and where they fit in the process of developing and maintaining semantic rule applications
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http://data.semanticuniverse.com/resource/semtech-2010-3291 http://purl.org/dc/elements/1.1/description Paper is still used to deliver a great deal of information but its value could be significantly augmented if it could be linked to other data in the same way online information is. Barcodes and scannable marks can be used to provide the missing connection between paper and data. This session will describe some approaches and possible applications of semantifying print on paper. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3291 http://purl.org/dc/elements/1.1/abstract This session will describe some approaches and possible applications of semantifying print on paper.
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http://data.semanticuniverse.com/resource/semtech-2010-2957 http://purl.org/dc/elements/1.1/abstract A closer look at the state-of-the art of predicate-oriented programming for business applications.
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http://data.semanticuniverse.com/resource/semtech-2010-2957 http://purl.org/dc/elements/1.1/title Is the Age of Predicate-Oriented Programming upon Us?
http://data.semanticuniverse.com/resource/semtech-2010-2957 http://purl.org/dc/elements/1.1/description As it stands today, object-oriented programming is the dominant paradigm for the development of business applications. While the object as a primitive for the modeling of the business domain has clearly served its purpose, more and more evidence has and still is being gathered through experiences from the field, specifically that vanilla OOP has reached a ceiling in terms of its ability to address the challenges of highly dynamical market conditions. <P> When compared to object systems, which are consistently demonstrating a large turnaround when modifications need to be made to respond to changes in the market, predicate systems seem to exhibit magical properties which allow the system to change its behavior with only marginal modifications and few additions. <P> In this presentation, we provide a state-of-the-art overview of existing approaches that allow business application developers to tap into this magic, and what their state and availability is. <P> This session will also include the following topics: <ul> <li>Understanding non-monotonic logic</li> <li>Pitching OOP vs. POP</li> <li>A use case taken from the world of insurance</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2925 http://www.w3.org/2000/01/rdf-schema#label Supporting Networking at Conferences with Social Semantics and Sensors
http://data.semanticuniverse.com/resource/semtech-2010-2925 http://purl.org/dc/elements/1.1/description Most conference attendees would agree that networking is a crucial component of their conference activities. It is vital for researchers to network and to form collaborations with other researchers, and such ties usually stem from casual meetings and conversations at conferences and similar scientific and social events. However, there are currently no viable applications and technologies to help researchers to initiate, capture, and preserve their social interactions with other researchers. <P> We have developed a novel application; Live Social Semantics, that brings together the semantic web, web2.0, and active sensors to encourage, ignite, and support researchers to network during conferences, and to retrace their social interactions with other researchers whenever required. The application will also show and suggest contacts based on the overlap of researchers? work, communities of practice, friends, and general interests. <P> In this talk, we will described the following parts of Live Social Semantics: <P> - The semantic architecture that integrates data from heterogeneous and distributed sources - The active RFID technology used to track face-to-face contacts - Collection and processing of semantic communities of practice and online social relationships - Processing of users? tag clouds to produce semantic profiles of interest - Results and user feedback on deploying the application at two major conferences in 2009 where it was used by 300 attendees - Evaluation and future development and deployments <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2925 http://purl.org/dc/elements/1.1/title Supporting Networking at Conferences with Social Semantics and Sensors
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http://data.semanticuniverse.com/resource/semtech-2010-2925 http://purl.org/dc/elements/1.1/abstract We will describe our novel application for supporting and logging networking activities of conference attendees by integrating active RFID, semantic web, and social networking technologies.
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http://data.semanticuniverse.com/resource/semtech-2010-3189 http://purl.org/dc/elements/1.1/title RDF Friday Part 3: Practical RDF - POWDER&amp;Object Design Patterns
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http://data.semanticuniverse.com/resource/semtech-2010-3189 http://purl.org/dc/elements/1.1/description <h4>PART I | The Power of POWDER</h4> <P> Matthew Fisher, Principal Systems Engineer, Progeny Systems John Hebeler, Division Scientist, Raytheon BBN Technologies <P> In September 2009, the W3C elevated the Protocol for Web Description Resources (POWDER) artifacts to a Recommendation. POWDER is a great bonus to the Semantic Web, and to the larger Internet in general. POWDER assists with: <ul> <li>Automated RDF creation from web data</li> <li>Content Personalization</li> <li>Content Discovery</li> <li>Trustmarks</li> </ul> This talk will detail what POWDER is, how it can be used, and why semantic web developers should care. In addition, POWDER's development and use of resource grouping will be covered. Grouping is a potent tool that, in the words of the POWDER primer, "offers semantically rich information about entire groups of online resources with both flexibility and precision." <hr width="10%" /> <P> <h4>PART II | Practical RDF: Object Design Patterns</h4> <P> Martyn Cutcher, Software Engineer, SYSTAP, LLC Bryan Thompson, Chief Scientist, SYSTAP, LLC <P> RDF's schema-flexibility has demonstrable benefits: enabling on-demand federation and semantic alignment of disparate data sets. Unfortunately, application programmers need access to the data in a form that makes sense to the domain in which they are working, described in some architectures as the Business Layer. <P> RDF amplifies the potential of the so called ?Impedance Mismatch? of relational representations. Right now, software designers have complex problems to solve using relational databases (access, representation and performance) and these will become even harder with RDF if conventional approaches are used. Is the aim to simplify the creation and use of RDF or to simplify the building of flexible applications? Our experience is that developers find object-centric approaches most productive. The problem is then reduced to identifying design and implementation patterns to support RDF representation of Object models and to efficiently support their modes of use. We present solutions to this problem using the Bigdata® RDF Datalayer. <P> Object Design Patterns can provide and support: <ul> <li>RDF's Schema Flexibility</li> <li>A Domain Specific Object Model</li> <li>Efficient exchange between object and RDF representations</li> <li>A methodology to develop new applications</li> <li>Straightforward access to the underlying RDF data</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2971 http://purl.org/dc/elements/1.1/abstract Introduce concepts, various technologies, and methods for automatic categorization of textual content.
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http://data.semanticuniverse.com/resource/semtech-2010-2971 http://purl.org/dc/elements/1.1/description The ability to automatically categorize textual content is very powerful and highly scalable. But auto-categorization needs to be done right to work well. This workshop helps you determine if auto-categorization suits your needs and how to select the correct type of auto-categorizer. It discusses how to automatically organize content to a taxonomy, and tools and methods you need for different auto-categorizers and application areas. <P> Attendees will gain an understanding of: Application areas in which auto-categorization works (or doesn't) Which auto-categorization technology to use for your application What can be automated and what must be done by humans What you can and cannot do with metadata How to use lexicons and vocabularies <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2869 http://purl.org/dc/elements/1.1/title Ontology-driven SOA Governance
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http://data.semanticuniverse.com/resource/semtech-2010-2869 http://purl.org/dc/elements/1.1/abstract Tutorial covering how to develop enterprise SOA messages from an Enterprise Ontology, based on a recent case study.
http://data.semanticuniverse.com/resource/semtech-2010-2869 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dave-mccomb
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http://data.semanticuniverse.com/resource/semtech-2010-2869 http://purl.org/dc/elements/1.1/description In this tutorial we will present a methodology and case report on developing and managing the messages in a Service Oriented Architecture. Participants will: <P> Be able to describe the business case for basing a Service Oriented Architecture on an enterprise ontology Be able to outline the steps needed to build an enterprise ontology of sufficient scope to support the message building process Be able to outline the steps needed to define and shape services and messages based on a combination of business event analysis and the ontology Be aware of tools that can be used to aid in various stages in the process <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3171 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/lars-hard
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http://data.semanticuniverse.com/resource/semtech-2010-3171 http://purl.org/dc/elements/1.1/description Mobile devices are the perfect home for semantic technology, from natural language interfaces, to smart inter-connections between device data, internet data and social media. By applying semantic technology, a new level of search functionality can be achieved for question-answer systems, social media disintermediation, customer self-help and more. This panel will describe how to use context, precision, relevance, discovery and interaction to go beyond traditional keyword index search to improve mobile search. <P> How can you deliver a rich mobile search experience? How is mobile search different from traditional web search? How can you use semantic technology to achieve a new level of search functionality? Real world experiences and key success factors in large-scale applications will be examined. Find out where semantic technology is likely to play next on mobile devices, and how you can put the "smart" in smart phones. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3171 http://purl.org/dc/elements/1.1/title Mobile Semantics
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http://data.semanticuniverse.com/resource/semtech-2010-2805 http://purl.org/dc/elements/1.1/title Ontology-centric knowledge discovery in a Contact Centre for Technical Product Support
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http://data.semanticuniverse.com/resource/semtech-2010-2805 http://purl.org/dc/elements/1.1/abstract Custom solution for telecommunications OEM technical contact center. New search paradigm for contact center workers navigating OWL-DL knowledgebases instantiated with text segments. Review the contribution to contact center performance metrics
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http://data.semanticuniverse.com/resource/semtech-2010-2805 http://www.w3.org/2000/01/rdf-schema#label Ontology-centric knowledge discovery in a Contact Centre for Technical Product Support
http://data.semanticuniverse.com/resource/semtech-2010-2805 http://swrc.ontoware.org/ontology#keywords knowledge-discovery
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http://data.semanticuniverse.com/resource/semtech-2010-2805 http://swrc.ontoware.org/ontology#keywords contact-centre
http://data.semanticuniverse.com/resource/semtech-2010-2805 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-marketing-and-advertising
http://data.semanticuniverse.com/resource/semtech-2010-2805 http://purl.org/dc/elements/1.1/description To respond to customer information requests in a timely manner contact center workers need to search through many types of knowledge resources including user manuals, training, marketing, engineering, and case resolution databases. Companies face increasing contact center costs as their products and information support services evolve. We report on a custom solution for a telecommunications OEM technical contact center involving development of product-specific OWL-DL ontologies. Ontologies were populated from a wide variety of document formats with sentence-triples generated by a telecom-specific text mining pipeline that leverages document segmentation techniques to instantiate with state of the art precision and recall. We evaluate the paradigm where contact center workers perform ad-hoc query-answer and navigate over instantiated OWL-DL knowledgebases using a combination of reasoning, faceted browsing and graphical query. Moreover we review the contribution to contact center performance metrics namely; utilization, first call resolution, case closed timeframe, efficiency, filtration rate, and revenue model. <P> <a href="http://innovatia.net/" target="_blank">http://innovatia.net/</a> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2805 http://swrc.ontoware.org/ontology#keywords ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-3258 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3258 http://purl.org/dc/elements/1.1/abstract In this session we will demonstrate the installation and use of Intellidimension?s Semantics.Platform for .NET
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http://data.semanticuniverse.com/resource/semtech-2010-3258 http://purl.org/dc/elements/1.1/title Getting Started with Intellidimension Products
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http://data.semanticuniverse.com/resource/semtech-2010-3258 http://www.w3.org/2000/01/rdf-schema#label Getting Started with Intellidimension Products
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http://data.semanticuniverse.com/resource/semtech-2010-3258 http://purl.org/dc/elements/1.1/description In this session we will demonstrate the installation and use of Intellidimension?s Semantics.Platform for .NET. We will provide an overview of the individual components of the platform, Semantics.Framework, Semantics.Server, and Semantics.DataCenter, and then demonstrate common tasks such as loading data, querying, and performing inference using those components. This is an ideal session for .NET developers looking to get started with semantic technologies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3005 http://purl.org/dc/elements/1.1/abstract The presentation aims to give an overview of the area of semantic service annotation: techniques, usage, examples, challenges, and future research directions.
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http://data.semanticuniverse.com/resource/semtech-2010-3005 http://swrc.ontoware.org/ontology#keywords decision-support-systems
http://data.semanticuniverse.com/resource/semtech-2010-3005 http://swrc.ontoware.org/ontology#keywords discovery
http://data.semanticuniverse.com/resource/semtech-2010-3005 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/arne-jørgen-berre
http://data.semanticuniverse.com/resource/semtech-2010-3005 http://purl.org/dc/elements/1.1/title Lightweight Semantic Annotations for Web Services
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http://data.semanticuniverse.com/resource/semtech-2010-3005 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-3005 http://purl.org/dc/elements/1.1/description Semantic annotations of services play a key role in automating service related tasks such as service discovery, selection, composition, or mediation. This presentation will give an overview of existing top-down and bottom-up approaches to semantic annotation for Web services with a particular focus on the newly developed WSMO-Lite semantic service annotation technique. We will highlight the use of semantic annotation in the ?Semantic Web Services Interoperability for Geospatial Decision Making (SWING)? research project (http://swing-project.org/), and present two challenging scenarios in the area of environmental decision support systems that require the use of semantic annotations for enabling better accessibility to environmental modeling tools using the Web, and providing greater flexibility through improved connections to distributed sources of information. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3005 http://www.w3.org/2000/01/rdf-schema#label Lightweight Semantic Annotations for Web Services
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http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/description Linked Data offers the ability to rapidly recombine data in varied ways at almost zero cost. As linked open data (LOD) gains a wider footprint, the opportunity is growing for use of linked data as a marketing vehicle. We will discuss how marketers can use linked data to increase online traffic and visibility, boost e-commerce, and engage in "data branding" -- positioning their organizations through the strategic publishing of structured and linked data. <P> Topics include: <P> - Can you generate profits from linked data? - Offensive opportunities and defensive strategies - Justifying linked data marketing with business relationships <P>
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-22T18:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-2749 http://www.w3.org/2000/01/rdf-schema#label New Business and Marketing Models with Semantics and Linked Data
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/title New Business and Marketing Models with Semantics and Linked Data
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http://data.semanticuniverse.com/resource/semtech-2010-2749 http://swrc.ontoware.org/ontology#keywords business-models
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ian-davis
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://swrc.ontoware.org/ontology#keywords advertising
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/scott-brinker
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http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/abstract Examine how linked data and semantic web technologies can be leveraged to create new business models that marketers can use to drive the adoption of "data web" strategies.
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-f-uschold
http://data.semanticuniverse.com/resource/semtech-2010-2749 http://swrc.ontoware.org/ontology#keywords branding
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://swrc.ontoware.org/ontology#keywords ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://swrc.ontoware.org/ontology#keywords motion-picture-industry
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://purl.org/dc/elements/1.1/abstract This talk describes: 1. novel problems/solutions in creating flexible knowledge representations and tools for the motion picture and video industry, 2. developing hybrid ontology frameworks using rules-based and statistical machine learning, and 3. strategies for ontology mapping and evolution challenges.
http://data.semanticuniverse.com/resource/semtech-2010-3051 http://swrc.ontoware.org/ontology#keywords metadata
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://purl.org/dc/elements/1.1/title Adobe® Story and Creative Suite 5 Semantic Technologies for the Motion Picture and Video Industry
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/marci-meingast
http://data.semanticuniverse.com/resource/semtech-2010-3051 http://www.w3.org/2000/01/rdf-schema#label Adobe® Story and Creative Suite 5 Semantic Technologies for the Motion Picture and Video Industry
http://data.semanticuniverse.com/resource/semtech-2010-3051 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T11:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3051 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/walter-w-chang
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://purl.org/dc/elements/1.1/description Adobe® Story is a collaborative movie script development system designed for creative movie/video professionals such as producers, directors, and writers working on or with scripts and screenplays. The Story system plays a key role during planning-to-playback workflows and leverages several Adobe semantic technologies to provide tight metadata integration within the entire Creative Suite platform during the pre-production, production, and post-production process. <P> This talk will focus on specific semantic technologies developed for CS5. By using natural language processing techniques and novel ontology creation and mapping mechanisms, raw script information is automatically transformed and structured into tagged metadata enabling the automatic creation of shooting scripts, shot lists, and the time synchronization of video content to script text. <P> Topics covered in this talk include: <ul> <li>An overview of key metadata workflows in the Creative Suite 5 platform</li> <li>The evolution of taxonomies and ontologies for the movie industry within Adobe</li> <li>Overcoming domain knowledge capture and ontology engineering challenges</li> <li>Developing hybrid rules-based and statistical methods to evolve and extend ontologies</li> </ul> <P> In addition to the speakers, Swapnil Gupta is a co-author on this presentation. Swapnil is a Software Quality Engineer in the Adobe Story Team Dynamic Media Organization, with Adobe Systems India. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3051 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-3051 http://swrc.ontoware.org/ontology#keywords natural-language
http://data.semanticuniverse.com/resource/semtech-2010-3226 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-enterprise-semantics
http://data.semanticuniverse.com/resource/semtech-2010-3226 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2010-3226 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3226 http://purl.org/dc/elements/1.1/description We have spent ten years learning how to save time and money when it comes to management of text and data from multiple sources. This talk will present our experience in implementing Semantic Enterprise solutions and reusing common software components and best practices. We will investigate different usage scenarios like data integration or text mining from the health care and life sciences domain. A typical workflow will be applied to the scenarios and demonstrate how to manage in 10 weeks to integrate 10 different databases, mine 10 million documents, and let customers explore this interlinked knowledge in 10 different ways. This presentation will cover the full path in adopting semantic technology in the enterprise and demonstrate a fully operational infrastructure which allows one to: Integrate structured data from a variety of sources Uncover implicit facts, interpreting the semantics of the data Collect information from proprietary sources and the web Interlink text and data to tag and index the text Extract new facts from text to enrich the data Provide multi-modal search and navigation <P>
http://data.semanticuniverse.com/resource/semtech-2010-3226 http://purl.org/dc/elements/1.1/abstract Summarizing 10 years of experience: process maturity is the key for the efficiency of semantic technology-based solutions, illustrated with data integration and content management projects in the life sciences.
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http://data.semanticuniverse.com/resource/semtech-2010-3226 http://purl.org/dc/elements/1.1/title How to integrate 10 databases and interlink them with 10 million documents in 10 weeks
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http://data.semanticuniverse.com/resource/semtech-2010-3240 http://purl.org/dc/elements/1.1/description Millions of community built Search Apps (focused search engines customized to content) will power future search -- not 2 or 3 general purpose search engines. What's missing until now is a platform where the community can build Search Apps. Semantifi is such a community driven search platform for structured data. <P> In this session, learn how to 1. Publish a Search App 2. Search different types of data including CSV, EXCEL, RDBMS 3. Search Linked Datasets (a case study on Freebase Linked data) 4. Profit by building Paid Search Apps <P>
http://data.semanticuniverse.com/resource/semtech-2010-3240 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T10:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3240 http://purl.org/dc/elements/1.1/abstract Encourage community to publish datasets as search apps using semantifi search platform for structured data.
http://data.semanticuniverse.com/resource/semtech-2010-3240 http://swrc.ontoware.org/ontology#keywords public-data
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http://data.semanticuniverse.com/resource/semtech-2010-3240 http://swrc.ontoware.org/ontology#keywords search-apps
http://data.semanticuniverse.com/resource/semtech-2010-3240 http://purl.org/dc/elements/1.1/title Future of Search is Millions of Community built Search Apps
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http://data.semanticuniverse.com/resource/semtech-2010-3240 http://www.w3.org/2000/01/rdf-schema#label Future of Search is Millions of Community built Search Apps
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http://data.semanticuniverse.com/resource/semtech-2010-2984 http://purl.org/dc/elements/1.1/description In the public sector various agencies are given different areas of responsibility. Despite this, a clear division between agencies - when it comes to functions they provide or the information they use - is rarely the case. The result is that citizens and organizations are required to report the same information or partly overlapping information to several agencies. Sometimes agencies then copy data received from another agency, falsely assuming a shared meaning. <P> In 1999, the Norwegian government established The Register of the Reporting Obligations of Enterprises as a central registry to monitor, reduce, and coordinate reporting obligations of enterprises. The register contains meta-information about reporting groups (i.e., organization types), their reporting obligations, and legal grounds for reporting. Since its start, the reporting obligations have been reduced by 23%. <P> In 2003, three national agencies established a national portal, Altinn, to simplify the interaction between government and businesses by providing a single electronic channel for written communications with the public sector, enabling businesses to communicate with multiple government agencies through a single point of submission. With the success of Altinn, the Register of the Reporting Obligations of Enterprises was challenged by the increase of electronic reporting and needed a better solution for metadata management. <P> The SERES intitative allows governmental agencies to model all their interactions at semantic, structural, and syntactical levels. The semantic descriptions are published and anchored in law and reporting obligations, supporting the Register of the Reporting Obligations and allowing coordination and harmonization between various agency vocabularies, and ultimately decreasing overlapping reporting of businesses. It also supports the definition of services in the Altinn portal. SERES is based on a MOF metamodel, and models and concepts can be exported in various formats including RDF/OWL. <P> In 2010, the SERES initiative got funding over the National Budget to support the increasing number of agencies wish for a common approach for metadata modeling, a long way on the road to become a national metadata registry across agencies. In addition several agencies have shown interest in using SERES to model their internal vocabularies. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2984 http://purl.org/dc/elements/1.1/abstract SERES is a semantic registry in Norway allowing individual agencies to model their internal vocabulary and interaction with other agencies. The registry is created to simplify
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http://data.semanticuniverse.com/resource/semtech-2010-2984 http://purl.org/dc/elements/1.1/title Semantic Registry for eGov Interoperability
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http://data.semanticuniverse.com/resource/semtech-2010-2906 http://purl.org/dc/elements/1.1/description Semantic Web/Linked Data technologies offer enterprises advanced data integration capabilities; the stack of technologies allows for bringing together both internal data and external web data based on open standards. This presentation will introduce various use case scenarios for data publishing and integration based on Semantic Web technologies, and present VisiNav, a fully-implemented application for searching and navigating RDF datasets collected from the open web. VisiNav has been deployed in several pilots over both open web and domain-specific datasets. We present VisiNav from an end-user perspective: what do prospective users have to know in order to explore and query web datasets in ways that go beyond the capabilities of current systems. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2906 http://purl.org/dc/elements/1.1/abstract The objective of the presentation is to demonstrate how to search, browse, navigate, and visualize enterprise and web data published and integrated using Semantic Web/Linked Data standards.
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http://data.semanticuniverse.com/resource/semtech-2010-2952 http://purl.org/dc/elements/1.1/abstract Engage the Community in a dialog about what the next steps are in pushing semantic technology into the mainstream software application development
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http://data.semanticuniverse.com/resource/semtech-2010-2952 http://purl.org/dc/elements/1.1/description In this presentation we will share some of the insights that we have gained about the reasons for the high cost of ?semantic programming model? in developing business applications. In semantic programming model the semantic content of an application is decoupled from the runtime machinery. This maximizes the reuse of the semantic content across different applications. It also makes it easier to upgrade an application to work in new situations. <P> Despite clear benefits, adoption of the semantic programming model has not been widespread in the business applications industry mainly because of the following reasons: <ul> <li>The upfront cost for capturing and validating semantic content in a business domain is high.</li> <li>Extraction of semantic content from existing legacy systems is prohibitively expensive.</li> <li>The gap between the capabilities of OWL DL inference engines and a full-fledged runtime environment for business applications is still wide.</li> <li>There are still not enough standard (or widely accepted) business ontologies in OWL DL to create a critical mass.</li> </ul> <P> We will provide an example of how we have used OWL DL for capturing the semantic content of a business application and the challenges we have encountered. At the end, we will propose a few recommendations for where the semantic technology community should put its focus in order to lower the cost of semantic programming model. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2952 http://purl.org/dc/elements/1.1/title Lowering the Cost of Semantic Programming Model in Developing Business Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2920 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/domingo-valhondo-solano
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http://data.semanticuniverse.com/resource/semtech-2010-2920 http://purl.org/dc/elements/1.1/abstract Repsol, a global oil company, has deployed semantic technologies for knowledge, collaboration and innovation management at corporate level. We describe the followed roadmap and exploitation results of this experience.
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http://data.semanticuniverse.com/resource/semtech-2010-2920 http://purl.org/dc/elements/1.1/description In 2007, Repsol, the major Spanish oil company, started deploying semantic technologies for knowledge, collaboration, and innovation management at the corporate level. Repsol has more than 35,000 employees with a presence in more than 30 countries in several business units for oil and gas operations. <P> The first task for the corporate knowledge management unit has been the definition of goals for better preservation and exploitation of knowledge, aligned with the overall strategic plan for management excellence achievement. <P> The roadmap is based on semantic technology adoption covering two basic objectives: <ol> <li>Serve as a unified corporate representation for information and knowledge</li> <li>Offer advanced applications beyond the current state-of-the-art of traditional knowledge management tools</li> </ol> We will explain all the steps of the roadmap we have undertaken: <ol> <li>Ontology deployment: Currently there are four businesses or administrative units that have already defined their operative ontology for knowledge representation.</li> <li>Application deployment: Currently several semantically-enhanced applications are deployed. <ul> <li>Semantic Collaborative Environment for open innovation paradigm support</li> <li>Intranet semantic search engine</li> <li>Knowledge management system to define, manage, and locate experts, processes, and resources</li> </ul> <P> The report includes an evaluation methodology and results of the impact of the adoption of semantic technology in the organization. For instance, early statistical evaluation of semantic functionality has shown that content relation and similarity are about 90% better than traditional solutions impacting the overall performance of a knowledge worker. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2920 http://purl.org/dc/elements/1.1/title Corporate Knowledge Management Using Semantic Technology: A Practical Experience in Repsol, a Major Oil Company in Spain
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http://data.semanticuniverse.com/resource/semtech-2010-3327 http://www.w3.org/2000/01/rdf-schema#label From Concepts to Production: Semantic Technology Solves Real Life Sciences and Healthcare Challenges
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http://data.semanticuniverse.com/resource/semtech-2010-3327 http://purl.org/dc/elements/1.1/description While semantic technologies have been around for quite some time, real proof of being able to deliver on its promise has been lacking and therefore life science companies and clinical centers of excellence have been reluctant to implement it. With the advent of translational research and science spanning multiple information domains, a dynamic, flexible, and extensible solution has become more necessary than ever to cope with the demand for knowledge management and data sharing across disciplines. As data from countless disperse sources (new instruments, files, images, database, and web content) are generated in ever-changing formats, new approaches were needed. This poster outlines how the transition to a semantic data integration, where data are in context with other data, has changed the playing field. <P> Using real-life challenging scenarios (a. Discovery of genomic & proteomic biomarkers for toxicity classification in a NIST/CLDA setting; b. Development of species-independent disease markers for FDA VET to minimize animal experiments; c. Compound purity and excipient influence on drug stability at Pfizer; d. Comparative treatment effectiveness assessment for prostate cancer at the Prostate Cancer Centre at UBC; and, e. Predictive decision support for organ failure in transplant patients at the PROOF Centre for the Prevention of Organ Failures) we will demonstrate, that semantic technology not only provides the toolset required for the new information age in life sciences and clinics as it harmonizes synonyms and nomenclature, but also allows for relationship mining, inference, and reasoning in a systems approach ? leading to informed decision-making with high confidence. The presented solutions using dynamic, flexible and scalable RDF triples stores, SPARQL endpoints, and "linked open data" initiatives are key in research demanding global collaborations. Graph representations of merged data correlation networks and mechanistic reference networks allow identifying classifiers in biomarker discovery and focusing on relevant dimension-reduced subnetworks. Knowledge from powerful systems biology-based models fosters understanding of complex biological processes (e.g., diseases & disease states, pre-disposition to certain biological responses, patient stratification for trials and treatment, predictive risk assessment for tumor growth, organ rejection, and severity of drug side effects). <P> These successfully demonstrated implementations are testimonials for capabilities, power and effectiveness of semantic technologies to cope with "imprecise connections? across multiple sources effectively, in less time, and at lower costs as compared to alternative approaches. Real peoples? real problems have been solved with real technology. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3327 http://purl.org/dc/elements/1.1/title From Concepts to Production: Semantic Technology Solves Real Life Sciences and Healthcare Challenges
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http://data.semanticuniverse.com/resource/semtech-2010-2896 http://purl.org/dc/elements/1.1/title Collaborative Authoring and Sharing of Semantic Web-based Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2896 http://purl.org/dc/elements/1.1/abstract We present Rexpolorator, an environment allowing users to explore possibly unknown RDF repositories, find answers to questions, generalize the solution and share it with other potential users interested in the same information.
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http://data.semanticuniverse.com/resource/semtech-2010-2896 http://purl.org/dc/elements/1.1/description There is an increasing amount of data being made available as RDF data, as evidenced by the accelerated growth of the Linked Data cloud. DBPedia, BBC Music, US SEC EDGAR database, the Best Buy product catalog, and the US Government data in Data.gov are good examples of what can already be used today. <P> A recurring problem being faced is finding information in such repositories, especially because often their structure is unknown beforehand. Thus, users typically have to explore the data until they understand its structure, then they are able to formulate queries to extract the desired information, and finally they have to combine the results and make them available to other users. <P> We provide an environment which allows non-technically savvy users, but who understand the problem domain, to accomplish these tasks. They employ a combination of search, query and faceted navigation in a direct manipulation, query-by-example style interface. In this process, users can reuse previously found solutions by other users, which may accomplish sub-tasks of the problem at hand. Once a solution has been found, it can be generalized and made available for reuse by other users, effectively building a social network around these repositories. <P> This presentation will cover the following issues: <ul> <li>Explore RDF datasets in domains of interest</li> <li>Build solutions to information-seeking problems</li> <li>Generalize solutions found</li> <li>Share and reuse solutions with other users</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2818 http://purl.org/dc/elements/1.1/abstract This tutorial will teach all elements of the latest version of the SPARQL Query Language from the ground up via real, runnable examples.
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http://data.semanticuniverse.com/resource/semtech-2010-2818 http://purl.org/dc/elements/1.1/description As the query language of the Semantic Web, SPARQL is a key foundational technology to finding answers and building software based on the Semantic Web. This hands-on tutorial will teach you everything you need to know to be proficient in SPARQL. No previous knowledge of SPARQL is assumed. Attendees are encouraged to come with their laptops so that they can experiment with SPARQL queries as the tutorial goes along. <P> Demonstrations will use real queries that can be run against real data on the Web to learn about the structure and features of SPARQL; how to create, evolve, and debug queries; and how to run queries against SPARQL endpoints around the Web. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2818 http://purl.org/dc/elements/1.1/title SPARQL 1.1 by Example
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http://data.semanticuniverse.com/resource/semtech-2010-3018 http://purl.org/dc/elements/1.1/title The Implications of Semantic Technologies for Market Research
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http://data.semanticuniverse.com/resource/semtech-2010-3018 http://purl.org/dc/elements/1.1/abstract A look at some of the outcomes of semantic technologies on the market research industry and the marketing function generally
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http://data.semanticuniverse.com/resource/semtech-2010-3018 http://www.w3.org/2000/01/rdf-schema#label The Implications of Semantic Technologies for Market Research
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http://data.semanticuniverse.com/resource/semtech-2010-3018 http://purl.org/dc/elements/1.1/description Extrapolation of some of the applications that could revolutionize the field of market research. How do insight professionals respond when the data itself starts becoming smarter, self organizing, and more meaningful? This presentation looks at some of the opportunities and threats to the MR industry as semantic technology starts to interact and synergize with other trends such as mass collaboration, consumer generated content, the Long Tail and RFID technology, and how this throws up unprecedented mash ups of data with unexpected results. <P> This presentation will mention semantic advertising and data branding, but will also focus on five other areas: <ol> <li>Semantic search, pinpoint granularity, the Long Tail and micro-segmentation</li> <li>Semantic identification, RFID and Customer Relationship Marketing</li> <li>Semantic challengers: reasoning engines and news wire services</li> <li>Semantic specification, Friend of a Friend and improved recruitment</li> <li>Semantic monitoring: intelligent agents and snitch bots</li> </ol> <P> The presentation will also include further speculations. <P>
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http://data.semanticuniverse.com/resource/evren-sirin http://www.w3.org/2001/vcard-rdf/3.0#org Clark & Parsia, LLC
http://data.semanticuniverse.com/resource/semtech-2010-3064 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/karthik-gomadam
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http://data.semanticuniverse.com/resource/semtech-2010-3064 http://purl.org/dc/elements/1.1/title Social Space: A Novel Approach to Analyzing Social Networks by Bringing Data and Graphs Together
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http://data.semanticuniverse.com/resource/semtech-2010-3064 http://www.w3.org/2000/01/rdf-schema#label Social Space: A Novel Approach to Analyzing Social Networks by Bringing Data and Graphs Together
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http://data.semanticuniverse.com/resource/semtech-2010-3064 http://purl.org/dc/elements/1.1/abstract In this presentation we will outline the shortcomings in the current state of analysis in social networks. Specifically, we address the problem of "friends" and "friends-of-friends" based analysis and propose a multi-dimensional approach for developing a more richer model.
http://data.semanticuniverse.com/resource/semtech-2010-3064 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/charalampos-chelmis
http://data.semanticuniverse.com/resource/semtech-2010-3064 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2010-3064 http://swrc.ontoware.org/ontology#keywords targeted-content-delivery
http://data.semanticuniverse.com/resource/semtech-2010-3064 http://swrc.ontoware.org/ontology#keywords linked-data-cloud
http://data.semanticuniverse.com/resource/semtech-2010-3064 http://purl.org/dc/elements/1.1/description We present a formal Semantic Model, called social space, for Social Networks based on Vector Spaces. Our approach takes into account both the social data (captured in the profile, user posts, and user activity) and the network aspect (captured by the connections). Rather than saying that Alice is a friend of Bob, our model will allow quantification of the strength of connection across different dimensions. For example, one can answer the question, "How close are Alice and Bob in the domain of sci-fi movies?" We will also present new operators that use our model, for computing distance and creating neighborhoods. We will present the theoretical foundations of our model and outline its usability by demonstrating a targeted content delivery application on top of the Facebook platform. In this demonstration we will use existing semantic models from the Linked Data Cloud, for semantic analysis of social networking data. <P>
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http://data.semanticuniverse.com/resource/daiichi-sankyo-pharma-development http://xmlns.com/foaf/0.1/name Daiichi Sankyo Pharma Development
http://data.semanticuniverse.com/resource/daiichi-sankyo-pharma-development http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/james-mcgurk
http://data.semanticuniverse.com/resource/daiichi-sankyo-pharma-development http://www.w3.org/2000/01/rdf-schema#label Daiichi Sankyo Pharma Development
http://data.semanticuniverse.com/resource/semtech-2010-3239 http://purl.org/dc/elements/1.1/title Using a Visual Ontology Modeler to create a financial product selection ontology
http://data.semanticuniverse.com/resource/semtech-2010-3239 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2010-3239 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/semtech-2010-3239 http://purl.org/dc/elements/1.1/description Financial services firms have many products on offer. Product change occurs frequently as a result of changing market conditions and competition. To win customer business, it is imperative to be able to respond with a selection of financial products that closely match the customer's request. It is difficult and time consuming to train customer service personnel to intelligently select from a large number of products. It is even more challenging to keep online systems up to date with the frequent product changes, and a simple text search exhibits low precision. Financial product ontologies can potentially assist in product selection, whether online or via staff. We show some examples of financial product selection ontologies, and demonstrate how to create them with a visual ontology modeling tool. The tool helps the ontologist understand complex relationships between the various components of financial products. A DL reasoner is used to determine which products in the ontology are compatible with a customer request. The results can be used to drive conventional product presentation systems. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3239 http://swrc.ontoware.org/ontology#keywords selection
http://data.semanticuniverse.com/resource/semtech-2010-3239 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/james-rhyne
http://data.semanticuniverse.com/resource/semtech-2010-3239 http://swrc.ontoware.org/ontology#keywords product
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http://data.semanticuniverse.com/resource/semtech-2010-3239 http://purl.org/dc/elements/1.1/abstract Product selection ontologies are complex networks of classes, object properties and data properties. Modeling them is easier when these entities and relationships can be seen and manipulated as diagrams using a diagram editor.
http://data.semanticuniverse.com/resource/semtech-2010-3239 http://purl.org/dc/elements/1.1/audience Intermediate
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http://data.semanticuniverse.com/resource/semtech-2010-3239 http://www.w3.org/2000/01/rdf-schema#label Using a Visual Ontology Modeler to create a financial product selection ontology
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http://data.semanticuniverse.com/resource/semtech-2010-3032 http://swrc.ontoware.org/ontology#keywords semantic-technology
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://purl.org/dc/elements/1.1/description There are over 10 million scientific researchers covering twenty-one subject disciplines across the world. Scientific publishing growth is at 3?4% per year representing millions of new articles distributed via thousands of publishers and over twenty thousand plus journals. Researchers are under great pressure to publish more high quality content while reaching into new areas with new collaborators. Today?s tools are not effective to allow a researcher to find new and innovative collaborators in an efficient manner. <P> This presentation will show how semantic technology coupled with a subject-based taxonomy, thesaurus, or ontology solves this problem. Attendees will see how the Collexis Fingerprinting technology achieves the following attributes: <ul> <li>Disambiguates the author?s names effectively and accurately</li> <li>Creates weighted profiles of each author</li> <li>Shows the co-author connections (the 6 degrees of separation is true in scientific research as well)</li> <li>Disambiguates the city, states, and countries representing the origin of the author?s publications.</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3032 http://purl.org/dc/elements/1.1/title How Semantic Technology Enhances the Productivity of Scientific Researchers
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://www.w3.org/2000/01/rdf-schema#label How Semantic Technology Enhances the Productivity of Scientific Researchers
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-social-networks-and-collaboration
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-semantic-search
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://swrc.ontoware.org/ontology#keywords co-authors-author-name-disambiguation
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2010
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/darrell-w-gunter
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://purl.org/dc/elements/1.1/abstract To show and demonstrate the specific semantic technology used to profile, identify and connect research experts and how it allows them to be more effective and efficient in their research.
http://data.semanticuniverse.com/resource/semtech-2010-3032 http://purl.org/dc/elements/1.1/audience Non-Technical
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http://data.semanticuniverse.com/resource/semtech-2010-3032 http://swrc.ontoware.org/ontology#keywords scientific-researchers
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http://data.semanticuniverse.com/resource/marie-wallace http://www.w3.org/2000/01/rdf-schema#label Marie Wallace
http://data.semanticuniverse.com/resource/marie-wallace http://xmlns.com/foaf/0.1/name Marie Wallace
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http://data.semanticuniverse.com/resource/marie-wallace http://www.w3.org/2001/vcard-rdf/3.0#title IBM Social Analytics Strategy
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http://data.semanticuniverse.com/resource/modus-operandi-inc http://xmlns.com/foaf/0.1/name Modus Operandi, Inc.
http://data.semanticuniverse.com/resource/modus-operandi-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/dr-kent-d-bimson
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http://data.semanticuniverse.com/resource/modus-operandi-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/randy-caldwell
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http://data.semanticuniverse.com/resource/semtech-2010-social-networks-and-collaboration http://www.w3.org/2000/01/rdf-schema#label Social Networks and Collaboration
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http://data.semanticuniverse.com/resource/semtech-2010-3253 http://swrc.ontoware.org/ontology#keywords named-entity-recognition
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http://data.semanticuniverse.com/resource/semtech-2010-3253 http://swrc.ontoware.org/ontology#keywords enterprise-search
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http://data.semanticuniverse.com/resource/semtech-2010-3253 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/terry-patten
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://purl.org/dc/elements/1.1/abstract Part I: A useful search technique is to infer whether entities are instances of query classes based on their properties rather than having to maintain explicit detailed ontologies. An Air Force application is described. Part II: An accessible, empirical discussion of the different challenges two document types (mainstream news articles and blogs) present in extracting named entities. A linguistic perspective is emphasized.
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-23T16:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://swrc.ontoware.org/ontology#keywords linguistic-semantics
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://swrc.ontoware.org/ontology#keywords semantic-search
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://purl.org/dc/elements/1.1/description <h4>PART I | Semantic Search Using Inferred Classes</h4> <P> <i>Terry Patten, Principal Scientist, Charles River Analytics</i><br> <i>Stephen Hookway, Software Engineer, Charles River Analytics</i> <P> Air Force analysts help prepare for air operations by searching imagery metadata for potential threats to the mission such as enemy aircraft or surface-to-air missile launchers. Semantic technology can improve these searches in several ways: Ontologies allow searching for entire classes of threats (such as surface-to-air missile launchers) without having to list the specific weapons in that class and all their synonyms. Another useful technique is to infer whether entities are instances of threat classes based on their properties rather than having to maintain explicit knowledge of which specific weapons are members of threat classes. For instance, if anti-aircraft ammunition becomes available for a weapon that was previously not a threat, that weapon automatically becomes a member of the threat class and will match a threat query. We demonstrate how a sound and complete OWL-DL reasoner can perform this inference in a scalable manner. <P> <hr width="10%" /> <P> <h4>PART II | Updating Named Entity Recognition and Classification for Real-Time Search</h4> <P> <i>John Lowe, Co-founder, Qewz, Inc.</i> <P> "Named Entity Recognition and Classification" (NERC) is a crucial component of any deep semantic analysis and is especially important to the development of the Semantic Web. NERC, however, is still something of a black art: <ul> <li>Good system performance depends on the interaction of many variables ? corpora, entity types used, evaluation metrics; and so far, there is no one-size-fits-all solution.</li> <li>NERC for real-time search applications requires the ability to recognize existing entities and their types and relations, as well as new, unseen, and unknown entities.</li> </ul> We present the results of an NERC experiment performed using three corpora (two well-known corpora, and one of our own devise): <ul> <li>The newly-released NYT Annotated Corpus</li> <li>The Blog Authorship Corpus</li> <li>The International News Corpus, combining news and blogs in English from several international sources</li> </ul> We generated a gold standard using a "tag-and-correct" approach: NEs were identified using a state-of-the-art NERC system, and the results were then "crowdsourced" for verification and correction via a novel labor-as-a-service (LAAS) component. <P> We compute and compare the distribution of entities and their types between and within the corpora, providing a linguistic account of the challenges each of these corpora present for robust NER. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-enterprise-semantics
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http://data.semanticuniverse.com/resource/semtech-2010-3253 http://purl.org/dc/elements/1.1/title Innovations in Semantic Enterprise Search
http://data.semanticuniverse.com/resource/semtech-2010-3253 http://www.w3.org/2000/01/rdf-schema#label Innovations in Semantic Enterprise Search
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http://data.semanticuniverse.com/resource/semtech-2010-3253 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/john-b-lowe
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http://data.semanticuniverse.com/resource/semtech-2010-3253 http://swrc.ontoware.org/ontology#keywords entity-classification
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http://data.semanticuniverse.com/resource/semtech-2010-2997 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-25T08:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-2997 http://swrc.ontoware.org/ontology#keywords simple-knowledge-organization-system- skos unified-medical-language-system umls umls-sk knowledge-representation
http://data.semanticuniverse.com/resource/semtech-2010-2997 http://purl.org/dc/elements/1.1/audience Advanced
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http://data.semanticuniverse.com/resource/semtech-2010-2997 http://purl.org/dc/elements/1.1/description According to the National Library of Medicine, the UMLS Knowledge Source (UMLS-KS) integrates and distributes key terminology, classification and coding standards, and associated resources to promote creation of more effective and interoperable biomedical information systems and services "that behave as if they 'understand' the meaning of the language of biomedicine and health". However the current information representation model utilized by UMLS-KS itself is not conducive to computer programs effectively retrieving and automatically and unambiguously interpreting the 'meaning' of the biomedical terms and concepts and their relationships. We will introduce a transformation algorithm to produce an SKOS representation of the UMLS-KS that integrates UMLS-Semantic Network, and the UMLS-Metathesaurus complete with all its 143 source vocabularies as a unified body of knowledge, along with appropriate metadata to trace provenance and governance information. <P> Our proposal is based on the idea that formal and explicit representation of the UMLS-KS enables: 1) automatic consistency and integrity checking of local mash-up thesauri, 2) automated information interpretation, integration, and discovery, and 3) novel and creative repurposing, and extensions of the knowledgebase within a distributed and collaborative network of researchers. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2997 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-industry:-pharmaceutical-health-care
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http://data.semanticuniverse.com/resource/semtech-2010-2997 http://www.w3.org/2000/01/rdf-schema#label UMLS-SKOS: A Semantic Web Framework for Representation of Biomedical Terminologies Using Simple Knowledge Organization System (SKOS)
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http://data.semanticuniverse.com/resource/semtech-2010-2997 http://purl.org/dc/elements/1.1/abstract We will propose using Simple Knowledge Organization System (SKOS) as an alternative to represent the body of knowledge incorporated within the Unified Medical Language System (UMLS) within the framework of the Semantic Web technologies.
http://data.semanticuniverse.com/resource/semtech-2010-2997 http://purl.org/dc/elements/1.1/title UMLS-SKOS: A Semantic Web Framework for Representation of Biomedical Terminologies Using Simple Knowledge Organization System (SKOS)
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http://data.semanticuniverse.com/resource/semtech-2010-3197 http://purl.org/dc/elements/1.1/description <h4>PART I (30 minutes) | Publishing (Linked) Data at the Library of Congress</h4> <P> Kevin Ford, Digital Project Coordinator, Network Development and Marc Standards Office Library of Congress <P> Although part of the legislative branch of government, and therefore not obligated to comply with the Open Government Directive, the Library of Congress has historically made its cataloging, authorities, and vocabularies data available for use and reuse. ID.LOC.GOV, one of the Library's most recent offerings, makes many of the authorities and vocabularies under the Library's management freely available for browsing and bulk download. The web service also marks the Library's entry into the Linked Data movement by providing a means for machines to semantically access, use, and harvest authority and vocabulary data that adheres to W3C recommendations, such as SKOS. Kevin Ford, current project manager for the ID.LOC.GOV web service, will provide an overview of ID.LOC.GOV, including how the data are used within and without the library and information science community. Special focus will be given to the mechanics behind initially offering the service and making the data available, such as security and privacy measures, new IT infrastructure, licensing language developed by Library counsel, cost recovery issues and federally mandated cost recovery, and data conversion. <P> <hr width="10%" /> <P> <h4>PART II (30 minutes) | Mash-up of Linked Government Data from http://data.gov</h4> <P> Li Ding, Research Scientist Deborah McGuinness, Professor James Hendler, Professor Rensselaer Polytechnic Institute <P> We discuss our use of Semantic Web technologies (RDF, RDFS, SPARQL and RDFa) to facilitate the development of open government applications. We present techniques for mashing up data from government sources and then review ongoing approaches from both the US and the UK. We also show RPI's "Data-gov Wiki" project, which creates linked government datasets; technical demos (open source with implementation details) on mashing up and visualizing the data; and a semantic wiki that supports government "subject matter experts" in helping Web developers, and eventually the public, better understand the meaning of the data. Finally, we end with a brief discussion of bringing together Web 2.0 and Linked Data to create "social data networks" in which communities of citizens will be able to interact to jointly solve societal problems. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2901 http://purl.org/dc/elements/1.1/abstract We want to demonstrate semantic mediawiki+ (SMW+) can be used to facilitate agile software development, from inception to user stories, to issue handling to user support, with two case studies.
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http://data.semanticuniverse.com/resource/semtech-2010-2901 http://purl.org/dc/elements/1.1/description In software project development, people always find different tools are used to fit various models and heterogeneous environment. From product owners/managers, program managers / scrum masters, developers, testers, document writers to users, all use a different set of tools, we want to show how to use semantic wiki plus related extensions to facilitate project management, by linking all the semi-structured data from heterogeneous sources into a single semantic storage, in semantic wikis. We will show how semantic technology can boost: * Capturing requirements * Managing milestones, sprints, stories and tasks * Relating detailed specs, issues (bugs), status reports and deliverables * Semantic notifications and RSS feeds, in real-time * Visualizations and reports * and Connecting people across the whole development cycle from inception, development, testing, to user support. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3165 http://purl.org/dc/elements/1.1/description Data is no longer just a back-office asset. Sharing data?and collaborating on its creation and enhancement?with your prospects, customers, and partners is quickly becoming the new way to build and strengthen relationships in the front-office too. Savvy marketers should be asking themselves: what data could I share far and wide to help grow my market and boost my brand? Companies such as Factual, InfoChimps, and MetaWeb are leading the charge with this vision, and in this session we'll explore the business and marketing opportunities that they enable. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3165 http://purl.org/dc/elements/1.1/title Data as the New Marketing Channel
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http://data.semanticuniverse.com/resource/semtech-2010-3165 http://purl.org/dc/elements/1.1/abstract Data is no longer just a back-office asset. Sharing data is quickly becoming the new way to build and strengthen relationships with customers.
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http://data.semanticuniverse.com/resource/semtech-2010-3133 http://purl.org/dc/elements/1.1/description <p>This session will be update attendees on recent developments in semantic wikis, an exciting hybrid of web 2.0 and semantic web technology. In the session, we will introduce semantic wikis, review some of the main developments in semantic wikis over the past year, and describe in detail two new emerging application areas. It will be organized into the following parts:</p> <ul> <li><em>Introduction</em>: A quick overview presentation on the background and main application areas of semantic wikis.</li> <li><em>A Year in Semantic Wikis</em>: A set of rapid-fire presentations devoted to developments in semantic wikis over the past year. </li> <li><em>Semantic Wiki Applications</em>: Two 30-minute detailed presentations of applications of semantic wikis in support of agile software development and in enterprise communities of practice.</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2789 http://purl.org/dc/elements/1.1/description The first version of SPARQL provided a standard way to access data on the Semantic Web, and as such was a key enabling technology for the growing Linked Data Web. But the first version of SPARQL lacked some key features for building powerful Semantic Web applications. <P> SPARQL 1.1, in development since March, 2009, seeks to rectify many of these omissions. SPARQL 1.1 adds an update language, clarifies the relationship between queries and reasoning, specifies a RESTful way to work with RDF data, provides a vocabulary for describing SPARQL endpoints, and, of course, adds several new features to the SPARQL query language, including: <ul> <li>Aggregates</li> <li>Subqueries</li> <li>Projected Expressions</li> <li>Negation</li> <li>Property Paths</li> </ul> In this panel session, members of the W3C SPARQL Working Group will give an overview of the new features in SPARQL 1.1, along with their motivation, uses, and when you can expect to start using them. (For many, the answer is now!) Following this overview, the Working Group will engage the community in a Q&A session and a discussion of both SPARQL 1.1 and the future of SPARQL beyond 1.1. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2757 http://purl.org/dc/elements/1.1/title Semantic Applications for Financial Services
http://data.semanticuniverse.com/resource/semtech-2010-2757 http://purl.org/dc/elements/1.1/description The effort to homogenize data gathered from disparate sources across an organization for a collective purpose--a complete customer profile, or a uniform financial statement--characterizes the underlying thrust of many technologies utilized by financial institutions, ranging from application integration technologies that attempt to integrate data-in-motion, to ETL and business intelligence tools that attempt to integrate data-at-rest. However, there are problems, limitations, and costs associated with these conventional technologies. This session addresses how Semantic Technology attempts to redress some of these constraints and how it may potentially provide benefit, particularly to financial institutions. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2757 http://purl.org/dc/elements/1.1/abstract Describe advantages of Semtech over conventional database and integration technologies; describe how Semtech can be applied to multiple use cases in financial services industry to reap its many advantages.
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http://data.semanticuniverse.com/resource/semtech-2010-3202 http://purl.org/dc/elements/1.1/description The presentation shows how a semantic web approach to text analytics can deliver deep insights from text and allow these insights to be integrated into the business in new and interesting ways. Through combining text analytics and ontologies we can transform content into a semantic network, and use inferencing and semantic reasoning to discover and derive new business insights. This approach increases the interoperability of the resulting knowledge, such as leveraging open linked data. This improves access to information and gives rise to smarter business decisions that are based on enhanced information consolidated from disparate sources. <P>
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http://data.semanticuniverse.com/resource/andy-denmark http://www.w3.org/2001/vcard-rdf/3.0#title VP of Engineering
http://data.semanticuniverse.com/resource/andy-denmark http://www.w3.org/2001/vcard-rdf/3.0#org TripIt
http://data.semanticuniverse.com/resource/leigh-dodds http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/leigh-dodds http://www.w3.org/2000/01/rdf-schema#label Leigh Dodds
http://data.semanticuniverse.com/resource/leigh-dodds http://xmlns.com/foaf/0.1/name Leigh Dodds
http://data.semanticuniverse.com/resource/leigh-dodds http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/1836.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/leigh-dodds http://www.w3.org/2001/vcard-rdf/3.0#title Platform Programme Manager
http://data.semanticuniverse.com/resource/leigh-dodds http://www.w3.org/2001/vcard-rdf/3.0#org Talis
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http://data.semanticuniverse.com/resource/semtech-2010-2960 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://swrc.ontoware.org/ontology#keywords ontologies
http://data.semanticuniverse.com/resource/semtech-2010-2960 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-2010-2960 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-k-bergman
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://swrc.ontoware.org/ontology#keywords semantic-technologies
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://purl.org/dc/elements/1.1/description A nagging gap in the semantic technology stack is acceptable ? still better, compelling ? user experiences. Whether because of direct exposure to triples and URIs (good for machines, not humans) or because of clunky widgets and apps, most agree that semantic user interfaces are awful. <P> This gap is perplexing given the innate structure and connectedness of semantic data and the wide availability of compelling rich Internet applications (RIAs). Further, these RIA frameworks are also well suited to ontology-driven applications, wherein generic and semantic "containers" can be "driven" by ontologies using straightforward best practices. <P> This session will explain this framework and demo publicly for the first time a new, open-source semantic RIA. It is Flex-based, highly interactive, and attractive. It adds sizzle to the semantic steak. <P> Component demos include the following: <ul> <li>Structure "slicing-and-dicing" of the information space</li> <li>Faceted browsing and discovery</li> <li>Data visualization (charts, graphs, mapping)</li> <li>Network and relationship graph browsing</li> <li>Ontology building and management</li> </ul> <P> The demos are based on deployments from both a prominent city and a well known knowledge base. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://swrc.ontoware.org/ontology#keywords rich-internet-applications
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-23T15:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://swrc.ontoware.org/ontology#keywords user-interfaces
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://purl.org/dc/elements/1.1/abstract A nagging gap in the semantic technology stack are rich, visual interfaces mere mortals can use. This session is split 80/20 between demo and slides, geared for maximum ?wow? factor.
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://www.w3.org/2000/01/rdf-schema#label Sizzle for the Steak: Rich, Visual Interfaces for Ontology-driven Apps
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://purl.org/dc/elements/1.1/title Sizzle for the Steak: Rich, Visual Interfaces for Ontology-driven Apps
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://swrc.ontoware.org/ontology#keywords flex
http://data.semanticuniverse.com/resource/semtech-2010-2960 http://swrc.ontoware.org/ontology#keywords ria
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http://data.semanticuniverse.com/resource/dan-g-mccreary http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/dan-g-mccreary http://www.w3.org/2000/01/rdf-schema#label Dan G McCreary
http://data.semanticuniverse.com/resource/dan-g-mccreary http://xmlns.com/foaf/0.1/name Dan G McCreary
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http://data.semanticuniverse.com/resource/dan-g-mccreary http://xmlns.com/foaf/0.1/onlineAccount http://www.linkedin.com/in/danmccreary
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-2010-2858 http://purl.org/dc/elements/1.1/title Maintaining Temporal Perspective
http://data.semanticuniverse.com/resource/semtech-2010-2858 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/yosemite-b
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http://data.semanticuniverse.com/resource/semtech-2010-2858 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/douglas-reid
http://data.semanticuniverse.com/resource/semtech-2010-2858 http://purl.org/dc/elements/1.1/description In an evolving knowledge environment, what was true yesterday may have been superseded by fresher information today, but remembering what we knew yesterday is still important. In these situations, the time interval for the validity of any given fact must also be recorded. This presentation explores one such system, focusing on two key aspects: The RDF knowledge representation that associates facts with time intervals of validity The query mechanism, which transforms a naive SPARQL query and a point in time into a new, time-sensitive query. The transformed query yields the subset of the results of the naive query that were valid at the indicated time. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2858 http://purl.org/dc/elements/1.1/abstract A methodology for recording and retrieving temporally valid data in an evolving knowledge environment.
http://data.semanticuniverse.com/resource/semtech-2010-2858 http://swrc.ontoware.org/ontology#keywords temporal-query
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http://data.semanticuniverse.com/resource/semtech-2010-2858 http://www.w3.org/2000/01/rdf-schema#label Maintaining Temporal Perspective
http://data.semanticuniverse.com/resource/semtech-2010-2858 http://swrc.ontoware.org/ontology#keywords temporal-knowledge-representation
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http://data.semanticuniverse.com/resource/martyn-cutcher http://www.w3.org/2001/vcard-rdf/3.0#org SYSTAP, LLC
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http://data.semanticuniverse.com/resource/the-knowledge-dynasty http://xmlns.com/foaf/0.1/name The Knowledge Dynasty
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http://data.semanticuniverse.com/resource/jeff-jonas http://xmlns.com/foaf/0.1/name Jeff Jonas
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http://data.semanticuniverse.com/resource/jeff-jonas http://www.w3.org/2001/vcard-rdf/3.0#title Distinguished Engineer & Chief Scientist of Entity Analytic Solutions
http://data.semanticuniverse.com/resource/jeff-jonas http://www.w3.org/2001/vcard-rdf/3.0#org IBM
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2010
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://purl.org/dc/elements/1.1/title Capturing Tweet Semantics to Foster Responsive and Transparent Governance
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T15:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-3335 http://www.w3.org/2000/01/rdf-schema#label Capturing Tweet Semantics to Foster Responsive and Transparent Governance
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/abir-qasem
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://purl.org/dc/elements/1.1/description This talk will be on how governance related ontologies can be induced from social media stream like Twitter, how governments can use these ontologies to sift through the information streams and look for key indicators/trends that need to be addressed and react to them in a timely manner. We argue that this form of responsive actions from the government will provide positive feedback to the citizens and they will feel more empowered and prone to participating in the governance process. We will describe a concrete method for domain specific ontology induction from a Tweet stream and use examples of how it can be used to provide timely governance decisions. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3335 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-24T16:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-3335 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/mark-windholtz http://www.w3.org/2000/01/rdf-schema#label Mark Windholtz
http://data.semanticuniverse.com/resource/mark-windholtz http://xmlns.com/foaf/0.1/name Mark Windholtz
http://data.semanticuniverse.com/resource/mark-windholtz http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/2643.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/mark-windholtz http://xmlns.com/foaf/0.1/onlineAccount http://twitter.com/agiledna/
http://data.semanticuniverse.com/resource/mark-windholtz http://www.w3.org/2001/vcard-rdf/3.0#title President
http://data.semanticuniverse.com/resource/mark-windholtz http://www.w3.org/2001/vcard-rdf/3.0#org AgileDNA
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-industry:-publishing
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/roger-roberts
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-23T12:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://purl.org/dc/elements/1.1/description The Belgian public broadcaster is currently conducting a large digitization project in the production environment called ?NumProd?. The project received the ?Innovation Award? at the last IBC. One of its aspects relates to the enrichment of its archives for opening their valorizations through various channels (Web, DVD, VOD ?). The enrichment has been made in a two-step process creating a network of Semantic Information Objects. Another aspect concerns the new productions creating ?native semantic? objects. The experiments have been conducted in various domains: interviews, news, history, etc... For each of the domains a specific profile (including its ontology files) has been created on the top of the AXIS-Core profile. This session will introduce the processes involved, the difficulties encountered, and the potentialities. The modeling of a semantic domain appears to be a major challenge. A methodology has been experimented for converging in that modeling. Concrete examples and explanation of the AXIS Open-Conceptual-Model will illustrate the session. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2826 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-2010-2826 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2010
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://purl.org/dc/elements/1.1/abstract The RTBF (French Speaking Belgian Public Broadcaster) has contributed to research projects for semantic modelling of enriched archives and new productions. The examples were chosen in the interviews and the news domains.
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://www.w3.org/2000/01/rdf-schema#label Introducing Semantics Concepts in a Television Broadcasting Organization
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/imperial-b
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://swrc.ontoware.org/ontology#keywords broadcast---medadata---semantic---modelling---serendipity-search---demonstration
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http://data.semanticuniverse.com/resource/semtech-2010-2826 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/guy-nl-marechal
http://data.semanticuniverse.com/resource/semtech-2010-2826 http://purl.org/dc/elements/1.1/title Introducing Semantics Concepts in a Television Broadcasting Organization
http://data.semanticuniverse.com/resource/semtech-2010-knowledge-engineering-and-management http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://data.semanticweb.org/ns/swc/ontology#TrackEvent
http://data.semanticuniverse.com/resource/semtech-2010-knowledge-engineering-and-management http://www.w3.org/2000/01/rdf-schema#label Knowledge Engineering and Management
http://data.semanticuniverse.com/resource/innovatia-inc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/innovatia-inc http://xmlns.com/foaf/0.1/name Innovatia Inc.
http://data.semanticuniverse.com/resource/innovatia-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/christopher-j-o-baker
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http://data.semanticuniverse.com/resource/swingly http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/swingly http://xmlns.com/foaf/0.1/name Swingly
http://data.semanticuniverse.com/resource/swingly http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/andy-hickl
http://data.semanticuniverse.com/resource/swingly http://www.w3.org/2000/01/rdf-schema#label Swingly
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://swrc.ontoware.org/ontology#keywords meetup
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/franciscan-a
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://swrc.ontoware.org/ontology#keywords social-media
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://purl.org/dc/elements/1.1/abstract An increasing number of communities use the web as a platform to manage content and interactions such as events. For efficiently management an ontology is introduced that defines the business logic.
http://data.semanticuniverse.com/resource/semtech-2010-2872 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/marco-neumann
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http://data.semanticuniverse.com/resource/semtech-2010-2872 http://purl.org/dc/elements/1.1/description This is a community of interest meeting that will discuss the development on the meetup ontology to enable a standard for Semantic Social Networks. <P> The Semantic Web meetup community comprises more than 5000 active participants around the globe. To better enable communication between meetup locations an ontology is defined to describe common features of available business logic processes such as meetings, membership and payments to provide an integration layer across heterogeneous and local applications. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2872 http://swrc.ontoware.org/ontology#keywords semantic-social-networks
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http://data.semanticuniverse.com/resource/semtech-2010-2872 http://purl.org/dc/elements/1.1/title Semantic Social Networks ? Ontology
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http://data.semanticuniverse.com/resource/semtech-2010-3058 http://www.w3.org/2000/01/rdf-schema#label Ontology 101: An Introduction to Knowledge Representation and Ontology Development
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http://data.semanticuniverse.com/resource/semtech-2010-3058 http://purl.org/dc/elements/1.1/description 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. This tutorial, which has been given for several years, 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: <P> Domain analysis methodology from software engineering IDEF methods developed for the US Department of Defense Best practices from the Semantic Web and Deployment working group <P> Examples from several business domains will be provided, with a focus on the Web Ontology Language (OWL). <P>
http://data.semanticuniverse.com/resource/semtech-2010-3058 http://swrc.ontoware.org/ontology#keywords owl
http://data.semanticuniverse.com/resource/semtech-2010-3058 http://purl.org/dc/elements/1.1/title Ontology 101: An Introduction to Knowledge Representation and Ontology Development
http://data.semanticuniverse.com/resource/semtech-2010-3058 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/elisa-kendall
http://data.semanticuniverse.com/resource/semtech-2010-3058 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2010-3058 http://purl.org/dc/elements/1.1/abstract This tutorial is a comprehensive and fast-moving introduction to ontology development, fully updated for OWL 2, new use cases and examples, and recent research.
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http://data.semanticuniverse.com/resource/semtech-2010-3058 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-2840 http://purl.org/dc/elements/1.1/abstract We adopt Semantic Wiki to build online Community of Practice in enterprise to facilitate the knowledge sharing, problem solving and innovation in Community of Practice.
http://data.semanticuniverse.com/resource/semtech-2010-2840 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/qinghai-wu
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http://data.semanticuniverse.com/resource/semtech-2010-2840 http://purl.org/dc/elements/1.1/description Communities of Practices (CoPs) are groups of professionals who share their knowledge, ideas and practices in a common domain or topic. An important aspect and function of communities of practice is increasing organization performance in several areas, such as spawning new ideas for products and services, responding more rapidly to customer needs and inquiries, and reducing rework and preventing "reinvention of the wheel". More and more companies and public institutions turn to the implementation and ?cultivation? of CoPs, expecting to improve the experience and knowledge of their employees. <P> Currently, various tools, such as discussion board, mailing list, Wiki, blog, are used to support online CoPs. People communicate at large to share ideas and information, address problems, and launch discussion on specific themes. But they have to spend a lot of time to gather enough information about a topic to be able to answer a question or complete a task as the acquired knowledge is often scattered, disordered, and not effectively integrated. Besides, people in the community are poor-linked and they often feel difficult to find right experts or solutions to address their practical problems. <P> By combining properties of Wiki (like ease of use, collaboration, linking) with Semantic technology (like structured content, knowledge models in form of ontologies, reasoning), Semantic Wikis structure data in a smart (up-to-date, consistent, inferable) and accessible way to better support flexible resource utilization and external applications. We adopt Semantic Wiki to build online CoPs in enterprise to facilitate the knowledge sharing, problem solving and innovation in CoPs. In this session, we will present our Semantic Wiki-based solution for online CoPs with the following key features: * Allowing dynamic concept modeling based on ontology. * Linking all kinds of data (e.g. people, content, event, time and place) via semantic annotation. * Enabling dynamic and structured presentation of up-to-date knowledge by means of inline query on linked data. * Providing relational navigation and semantic search to retrieve and discover relevant knowledge. * Supporting expert discovery based on linked data and interaction activities. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2840 http://purl.org/dc/elements/1.1/title Building Community of Practice in Enterprise based upon Semantic Wiki
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http://data.semanticuniverse.com/resource/semtech-2010-3247 http://purl.org/dc/elements/1.1/description <b>OWL: Experiences and Directions</b></p> <P> <p><b>13:00 - 13:10</b> Introduction</p> <p><b>13:10 - 15:00</b> Scientific Applications of OWL</p> <p>Relational patterns in OWL and their application to OBO (0:35)<br> <i>Robert Hoehndorf, Anika Oellrich, Michel Dumontier, Heinrich Herre and Dietrich Rebholz-Schuhmann</i></p> <p>Representing chemicals using OWL, Description Graphs and Rules (0:35)<br> <i>Janna Hastings, Duncan Hull, Matthew Horridge, Christoph Steinbeck, Robert Stevens, Ulrike Sattler, Tertia Horne and Katarina Britz</i></p> <p>Computed Knowledge Base for Description of Information Resources of Water Spectroscopy (0:20)<br> <i>Alexey Privezentsev, Alexander Fazliev, Dmitry Tsarkov and Jonathan Tennyson</i></p> <p>An OWL ontology for quantum mechanics (0:20)<br> <i>Marcin Skulimowski</i></p> <p><b>15:00 - 15:30</b> Break</p> <p><b>15:30 - 16:50</b> Services and Protocols</p> <p>SHARE & The Semantic Web - This Time it?s Personal! (0:20)<br> <i>Benjamin Vandervalk, Luke McCarthy, and Mark Wilkinson</i></p> <p>An Open Source Database Backend for the OWL API and Protege 4 (0:20)<br> <i>Timothy Redmond</i></p> <p>The OWLlink API: Teaching OWL Components a Common Protocol (0:20)<br> <i>Olaf Noppens, Marko Luther and Thorsten Liebig</i></p> <p>PelletServer: HTTP & OWL2 Reasoning (0:20)<br> <i>Blazej Bulka and Evren Sirin</i></p> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2941 http://purl.org/dc/elements/1.1/description This talk is about a simple way of feeding many ontologies with changes arising from routine update of source data bases in various formats at different locations. We will show how this can be done with the A-tree, a new API for storage and distribution of data. With this API, any data base updates can be wrapped-up as a stream of freestanding assertions in an RDF compatible format. These are stored locally with selective distribution into similar stores across the web. Subscription contracts ensure that there is one of these A-tree stores tailored to the needs of each affected ontology. <P> This talk will explain how the unique 'assertion' format adopted for all data in the A-tree allows both application and meta data to be distributed at will across the web without any loss of integrity and without any form of central management. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2941 http://swrc.ontoware.org/ontology#keywords ontology
http://data.semanticuniverse.com/resource/semtech-2010-2941 http://www.w3.org/2000/01/rdf-schema#label Using A-tree Technology to Keep Ontologies Up-to-date
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http://data.semanticuniverse.com/resource/semtech-2010-2941 http://purl.org/dc/elements/1.1/abstract To show that the A-tree concept has become a useable API with real value in the role of feeding ontologies with updates from data bases across the web.
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http://data.semanticuniverse.com/resource/semtech-2010-2941 http://purl.org/dc/elements/1.1/title Using A-tree Technology to Keep Ontologies Up-to-date
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http://data.semanticuniverse.com/resource/semtech-2010-2821 http://purl.org/dc/elements/1.1/description The landscape of the ontology tools today is largely fragmented between the tools for ontology editing and publishing and peer review: users develop an ontology in an environment such as Protege (http://protege.stanford.edu) and publish it an ontology repository, such as BioPortal (http://bioportal.bioontology.org) to share it with the community and to collect feedback from users. Our group is bringing these two worlds together, by developing an integrated platform for the entire ontology lifecycle, enabling users to switch seamlessly from the process of browsing feedback from users on their ontology, to making changes based on the feedback, to integrating elements from other published ontologies, to publishing the new ontology version. <P> We will demonstrate WebProtege, a Web-based collaborative ontology-editing environment and BioPortal, a community-based ontology repository, and will discuss how to use both tools in the ontology life cycle. We will show how users can search BioPortal ontologies from Protege and include concepts from those ontologies into their own ontology. We will then show how developers can open the ontology-editing to a wider community of their users, enabling them to provide suggestions and request changes in the published version of the ontology. These requests and suggestions are then accessed in the Protege editing environment, enabling the editors to act on the users' suggestions if they choose to. The two tools together, integrated in this way, provide a new open social process for developing ontologies. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2821 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/natasha-noy
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http://data.semanticuniverse.com/resource/semtech-2010-2821 http://purl.org/dc/elements/1.1/abstract We will describe the ontology life cycle that uses Protege for ontology editing and BioPortal for ontology publishing, peer review and service-based access to ontologies. The two tools are integrated and provide a single platform.
http://data.semanticuniverse.com/resource/semtech-2010-2821 http://www.w3.org/2000/01/rdf-schema#label The Ontology Life Cycle: Integrated Tools for Editing, Publishing, Peer Review, and Evolution of Ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-2821 http://purl.org/dc/elements/1.1/title The Ontology Life Cycle: Integrated Tools for Editing, Publishing, Peer Review, and Evolution of Ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-3053 http://purl.org/dc/elements/1.1/title Integrating Semantic Systems
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http://data.semanticuniverse.com/resource/semtech-2010-3053 http://purl.org/dc/elements/1.1/abstract Explain the semantic issues that create problems and difficulties for interoperating systems. Illustrate them with examples and case studies. Demonstrate techniques and methodologies that would enable developers to anticipate the problems and design systems that solve them or avoid them.
http://data.semanticuniverse.com/resource/semtech-2010-3053 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-22T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3053 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-knowledge-engineering-and-management
http://data.semanticuniverse.com/resource/semtech-2010-3053 http://purl.org/dc/elements/1.1/description Tight integration across computer systems, even of local systems, is hard to achieve because all components must interpret the same data in the same way. Further complications are created by different notations and conventions in databases, knowledge bases, the Semantic Web, folksonomies, and legacy systems that have no explicit semantic notations. <P> This tutorial will use examples and case studies to illustrate these problems, ways of addressing them, and future challenges. Topics include: Methods of communication and control among loosely coupled systems and more tightly integrated systems Diagrams and controlled natural languages for expressing formal ontologies in humanly readable forms Supporting interoperability among heterogeneous systems with different semantic representations, including legacy systems with no explicit semantics <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3274 http://www.w3.org/2000/01/rdf-schema#label The Personal Data Locker
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http://data.semanticuniverse.com/resource/semtech-2010-3274 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/chris-messina
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http://data.semanticuniverse.com/resource/semtech-2010-3274 http://purl.org/dc/elements/1.1/description Personal data lockers, linked data, semantic understanding, and intelligent agents will form an ecosystem where applications, leveraging a rich understanding of the relationships between different themes and concepts, will know how to access, manage, and act on the items in your data locker to present relevant content and services. <P> You will be able to configure who gets access to your locker and in what context, depending on your role, intent, and location. This ecosystem will enable businesses to offer customers more relevant, convenient, and useful content and experiences. Your personal data locker will hold your dynamic persona, including preferences, affinities, purchases, travel destinations, social graphs, and much more. <P> However, there are many questions to ask: What will it mean for your life in terms of better services, greater productivity, and cheaper goods? Who is going to give you the data locker - a bank, a mobile operator, Facebook, a new start-up? Will you have one locker for everything or a series of linked lockers containing different data for different uses? <P> This session will explore the current opportunities and issues surrounding the advent of the personal data locker including: consumer privacy and control, semantic understanding, and a holistic view of the consumer for enterprises. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3274 http://purl.org/dc/elements/1.1/title The Personal Data Locker
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http://data.semanticuniverse.com/resource/semtech-2010-3242 http://purl.org/dc/elements/1.1/abstract With ai-one you can develop intelligent applications that provide better sense-making capabilities for semantic discovery, knowledge collaboration sentiment analysis, business intelligence, data mining and more. Provide complex AI with reasoning and learning capabilities. Get smarter with each use.
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http://data.semanticuniverse.com/resource/semtech-2010-3242 http://purl.org/dc/elements/1.1/description ai-one inc. has developed an adaptive semantic neural net with semiotic data handling capabilities ( holosemantic SDK/API with libraries) that allows users to quickly analyze and discover meaningful patterns of interleaved text, data, and images. <P> A range of partner projects are based on ai-one? technology: <P> CENDOO Butler is autonomic intelligence to facilitate both creative and logical semiotic data processes In simple terms it's an automated information service that interprets your needs to retrieve specific information that can be tailored for better sense-making. With CENDOO Butler you have learning capabilities that gets smarter with use. And the user - you - have total control over the Butler. <P> Brainup uses ai-one? TopicMapper API to mine and understand legacy, archived and current content on your PC, intranet, enterprise data bases or document management systems into your personal knowledge base. For pixel/image data, ASTIS? Automatic Shoe Track Information System matches and analyzes shoe tracks for crime laboratories. ASTIS has the ability to learn individual forms but also groupings of forms relevant for matching images. It can learn from experience, deal with ambiguity and unknown situations, know when to ask for help, and recover from errors. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2986 http://purl.org/dc/elements/1.1/abstract Learn how Merck used semantic web technologies to create an agile, comprehensive "Scouting Knowledgebase" that links together many sources of information and provides living, real-time, role-specific views into Merck's early-stage licensing pipeline.
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http://data.semanticuniverse.com/resource/semtech-2010-2986 http://purl.org/dc/elements/1.1/description In order to continue our mission of delivering innovative health solutions, Merck relies on a rich ecosystem of organizations and data sources to capture, curate and leverage knowledge of early-stage licensing opportunities. Traditionally, these stakeholders and systems are disconnected silos, linked only by email, telephone calls and manually integrated spreadsheets. We initiated a Proof-Of-Concept (POC) that used Semantic Web technologies to create an agile and comprehensive "Scouting Knowledgebase" that links together many sources of information and provides living, real-time, role-specific views into Merck's early-stage licensing pipeline. Merck chose Cambridge Semantics to provide a comprehensive environment for our development. In the POC we were able to enhance Merck's discovery and pre-clinical knowledge gathering and scouting processes. It also enabled us to integrate a diverse set of existing systems, including relational databases and Excel spreadsheets, and to do so while maintaining a consistent view of early-stage licensing opportunities. This presentation will cover: <P> The challenge Merck faced in dealing with the wealth of stakeholders and systems that are crucial to pursuing early-stage licensing opportunities The process of creating our semantic pilot program and applying Semantic Web technologies How Semantic Web technologies provided immediate tactical and strategic benefits in coordinating knowledge discovery and management How Semantic Web technologies lay the foundation for future improvements and automation of the competitive intelligence/scouting landscape. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2908 http://purl.org/dc/elements/1.1/abstract Explore how the architecture, design, and concepts behind an innovative new site for collecting and publishing community sourced annotations of Linked Data can be extended to other areas.
http://data.semanticuniverse.com/resource/semtech-2010-2908 http://purl.org/dc/elements/1.1/description FanHu.bz is a web application that both consumes and produces Linked Data. Built on the data published by the BBC the application surfaces existing communities that surround broadcast media. FanHu.bz combines these features with the means for the community to annotate that data with additional metadata, providing pointers to other resources. The presentation will: Review the basic concepts and approach that underpin the design of the site Illustrate how the FanHu.bz concept could be extended to other media and news outlets Introduce the architecture of the site and how this could be generalised for other uses Present an alternate approach for growing and inter-linking the Linked Data cloud <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2908 http://purl.org/dc/elements/1.1/title FanHu.bz ? Community Annotations of Linked Data Using Twitter
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http://data.semanticuniverse.com/resource/semtech-2010-2908 http://www.w3.org/2000/01/rdf-schema#label FanHu.bz ? Community Annotations of Linked Data Using Twitter
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http://data.semanticuniverse.com/resource/semtech-2010-3186 http://swrc.ontoware.org/ontology#keywords web-data
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http://data.semanticuniverse.com/resource/semtech-2010-3186 http://purl.org/dc/elements/1.1/description <h4>PART I | Text Analytics Changes the Game in Enterprise Search</h4> <P> C. Seuss, CEO, Northern Light Group <P> Researchers trolling online for information in a typical enterprise environment today are doing little more than crossing their fingers and hoping for amazing good luck. That's because the typical enterprise search engine responds to a query with a list of documents and links, relevance ranked to some standard, that are virtually dropped on the user's desk. The user typically clicks on the first several results, reads them and hopes that all they need to know about the topic they are researching is contained in those first few documents. <P> But text analytics embedded into an enterprise search engine is creating a far better solution for truly gaining in-depth understanding of a topic through online research. Text analytics is growing beyond its roots in "reputation management" applications, and can now be found analyzing and interpreting literature search results related to companies' product and marketing strategies, corporate acquisition opportunities, and other issues. Mr. Seuss will offer examples of how text analytics enables powerful "meaning extraction" in the fields of drug discovery and information technology, to accelerate "time-to-insight" for researchers. <P> The application of text analytics to an enterprise search engine alters the very notion of what a "search result" can be, and dramatically enhances the depth of insight and information that the "results list" can provide to the user. It guides the user to those documents that truly contain the most relevant information in response to their specific research query. <P> <hr width="10%" /> <P> <h4>PART II | Is the Semantic Web Moving Fast Enough for Text Analytics?</h4> <P> Stefan Andreasen, CTO/Founder, Kapow Technologies <P> More and more organizations are benefiting from the treasure-trove of data available on the Web to feed their text analytics applications and power information solutions for voice of the customer, buzz metrics, brand protection, anti-piracy and open source intelligence. <P> Tim Berners-Lee's vision for the internet as a place to find and share data has - for the most part - come true. Unfortunately, most of the data on the Web is locked into HTML and AJAX code with no easy way for a text analytics application to access it, at least not without getting a lot of noise that will spoil the results. <P> The semantic Web promises a world in which machines become capable of analyzing all data on the Web without any human involvement. This would allow for automated access of accurate data, but will this world ever exist, and can we really afford to wait? <P> This presentation will review several real-world examples that illustrate how companies and their knowledge workers are unlocking noise-free Web data and integrating it with innovative text analytics applications. <P> In this educational session you will learn about: <ul> <li>The value of Web data for text analytics</li> <li>The importance of data quality, data coverage and being able to rapidly access new data sources as requirements change</li> <li>Real-world business examples within voice of the customer, buzz monitoring, anti-piracy, pricing and demand intelligence and open source intelligence</li> <li>What is Web Data Services and how it works</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3108 http://purl.org/dc/elements/1.1/description This discussion features representatives from major media companies who are seriously investigating or presently using semantic technologies in their sites. The conversation will focus on the business and operational benefits of using semantic technologies in publishing and media sites. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3343 http://purl.org/dc/elements/1.1/description Advertising on the World Wide Web is based around automatically matching web pages with appropriate advertisements, in the form of banner ads, interactive adverts, or text links. Primarily this has been done by manual classification of pages, or more recently using information retrieval or natural language processing techniques to find the most important keywords from the page, and match these to keywords being used by adverts. We propose a new model for online advertising, based around lightweight embedded semantics. This will improve the relevancy of adverts on the World Wide Web and help to kick-start the use of RDFa as a mechanism for adding semanticly rich information to the Web. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3343 http://purl.org/dc/elements/1.1/abstract Semantic advertising framework developed at The University of Aberdeen
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http://data.semanticuniverse.com/resource/semtech-2010-3343 http://purl.org/dc/elements/1.1/title A framework for semantic advertising on Web 3.0
http://data.semanticuniverse.com/resource/semtech-2010-3343 http://www.w3.org/2000/01/rdf-schema#label A framework for semantic advertising on Web 3.0
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http://data.semanticuniverse.com/resource/semtech-2010-2834 http://purl.org/dc/elements/1.1/abstract This talk will examine challenges in exposing data stored in relational databases for the purposes of querying via SPARQL and other semantic web technologies. This is based on work from a Human Resources data integration project in the Department of Defense.
http://data.semanticuniverse.com/resource/semtech-2010-2834 http://purl.org/dc/elements/1.1/description For decades enterprises have stored their most important data in relational databases. For semantic web information approaches to realize their full potential, they must unlock the relational data at the core of the enterprise. <P> This talk will examine the key challenges in integrating relational data with semantic systems such as data types, unique identification, normalization, data mapping, etc. These issues will be considered in the light of a real data integration project under way in the Department of Defense. <P> Common patterns of data integration such as export/ETL, query rewriting, and hybrid approaches will be considered. Existing tools such as D2RQ, SquirrelRDF, Triplify, etc. will be described and compared. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2834 http://www.w3.org/2000/01/rdf-schema#label Releasing Relational Data to the Semantic Web
http://data.semanticuniverse.com/resource/semtech-2010-2834 http://purl.org/dc/elements/1.1/title Releasing Relational Data to the Semantic Web
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http://data.semanticuniverse.com/resource/semtech-2010-2880 http://purl.org/dc/elements/1.1/description KMI?s goal is to provide stakeholders with a semantically integrated view of Eastern Range information?a Single Integrated Range Picture?by transforming distributed, heterogeneous information into semantically enriched knowledge that improves situation awareness and understanding. However, situational understanding differs depending on each stakeholder?s area of responsibility (AOR), background, experience, and problem-solving need. <P> This year, we focus on the challenges of semantically representing and integrating different stakeholder points-of-view, or understandings of information, including operations requirements, systems and components, system status, problems, mission impacts and resolution actions. For example, a range engineer may focus on system problems, whereas a commander needs to understand mission requirements and problem impacts; each is working from an incomplete understanding of the other?s knowledge base and AOR, creating ?semantic gaps? in situation assessment. These semantic gaps can lead to situation misunderstandings if they are not properly filled, a process currently performed by knowledgeable staff translating ?engineering-speak? into ?commander-speak? in daily Situation Reports (SITREPs). <P> This briefing will cover the following points: <ul> <li>Project: KMI overview and a status update</li> <li>Process: Semantic analysis/ontology modeling process and knowledge sources used</li> <li>Product: SITREP and Mission Requirements applications and ontologies</li> <li>Problem: Semantic points-of-view challenge, our approach and next steps</li> </ul> <P> This work was sponsored by the USAF 45SW and AFRL. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2880 http://swrc.ontoware.org/ontology#keywords ontology-based-information-integration
http://data.semanticuniverse.com/resource/semtech-2010-2880 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dr-kent-d-bimson
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http://data.semanticuniverse.com/resource/semtech-2010-2880 http://purl.org/dc/elements/1.1/title Case Study Year 5: USAF 45th Space Wing Knowledge Management Initiative ? Representing Semantic Points-of-View Using SITREP and Mission Ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-2880 http://purl.org/dc/elements/1.1/abstract Year five update on the USAF 45th Space Wing?s Knowledge Management Initiative, focused on using ontologies to enrich legacy information. This year?s presentation focuses on the challenge of representing different points-of-view in situational understanding using ontologies.
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http://data.semanticuniverse.com/resource/semtech-2010-2880 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/randy-caldwell
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http://data.semanticuniverse.com/resource/semtech-2010-2778 http://purl.org/dc/elements/1.1/title The SILK 2 System and RIF Dialect: Semantic Rules Grow Up
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http://data.semanticuniverse.com/resource/semtech-2010-2778 http://purl.org/dc/elements/1.1/abstract We demonstrate the SILK V2 system and language for semantic web rules and ontologies, including powerful reactive higher-order defaults and broad interoperability, and application use cases in science and business/government.
http://data.semanticuniverse.com/resource/semtech-2010-2778 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2010-2778 http://swrc.ontoware.org/ontology#keywords knowledge-representation
http://data.semanticuniverse.com/resource/semtech-2010-2778 http://www.w3.org/2000/01/rdf-schema#label The SILK 2 System and RIF Dialect: Semantic Rules Grow Up
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http://data.semanticuniverse.com/resource/semtech-2010-2778 http://swrc.ontoware.org/ontology#keywords ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-2778 http://purl.org/dc/elements/1.1/description We review and demonstrate the SILK V2 system and language for semantic web rules and ontologies. We show the power of its reactive higher-order defaults and broad interoperability. We survey several application use cases in science and business/government. <P> Part of Vulcan Inc.'s Project Halo, SILK is a highly ambitious R&D effort that is redefining the knowledge representation (KR) playing field for business rules and rule-based process management. It addresses fundamental requirements for scaling semantic web to widely-authored VLKBs (Very Large Knowledge Bases) in business and science that answer questions, proactively supply information, and reason powerfully. <P> SILK radically extends the KR power of W3C OWL, SPARQL, RIF and SQL. It has a rigorous semantics based on the theory of hyper logic programs and includes: <ul> <li>Defaults and robust conflict handling that cope with knowledge quality and context</li> <li>Higher-order and flexible meta-reasoning that elevate meta-data to meta-knowledge</li> <li>Actions and events, cf. production rules and process models that activate knowledge</li> </ul> The SILK language includes both a human-friendly ASCII syntax, and a proposed RIF (W3C Rule Interchange Format) dialect in markup, that like RIF draws heavily on the RuleML design approach. <P> SILK's application use cases include biomedical, e-commerce, policies,and ontology mapping. <P> The SILK system includes an efficient reasoner and supports deep integration, via web interchange, with RDF(S)/OWL rule-based ontologies, SPARQL triple stores. An advanced GUI is under development, as are additional interchange capabilities for first-order-logic and production rules. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3080 http://purl.org/dc/elements/1.1/abstract This talk discusses the enterprise-class inference engine with Oracle Database Semantic Technologies in Oracle Database 11g Release 2. Features, best practices in usage, and future plans are explained.
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http://data.semanticuniverse.com/resource/semtech-2010-3080 http://purl.org/dc/elements/1.1/title An Enterprise-Class Inference Engine Inside Oracle Database 11g Release 2
http://data.semanticuniverse.com/resource/semtech-2010-3080 http://swrc.ontoware.org/ontology#keywords jena
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http://data.semanticuniverse.com/resource/semtech-2010-3080 http://www.w3.org/2000/01/rdf-schema#label An Enterprise-Class Inference Engine Inside Oracle Database 11g Release 2
http://data.semanticuniverse.com/resource/semtech-2010-3080 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/vladimir-kolovski
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http://data.semanticuniverse.com/resource/semtech-2010-3080 http://purl.org/dc/elements/1.1/description As part of Oracle Spatial 11g, an option for Oracle Database 11g Enterprise Edition, Oracle provides a powerful parallel and incremental inference engine that scales easily with the hardware. <P> This session will highlight the following topics: <ul> <li>Overview of Oracle Database Semantic Data management capabilities</li> <li>Design of the parallel and incremental inference engine</li> <li>Support for rules in OWL 2 RL (OWLPrime), RDFS, SKOS, and SNOMED</li> <li>Support for user defined rules</li> <li>Best practices for performance</li> <li>Future plans for new inference capabilities</li> </ul> <P> Apart from the powerful inference capabilities built inside the Oracle semantic database, external reasoners can easily be plugged-in for additional reasoning support. A good example is PelletDb 1.0, which integrates with Oracle's inference engine through Jena APIs using the Jena Adaptor. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2999 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/tom-reamy
http://data.semanticuniverse.com/resource/semtech-2010-2999 http://purl.org/dc/elements/1.1/abstract Learn how to use the concept of Basic Level categories to semantic applications
http://data.semanticuniverse.com/resource/semtech-2010-2999 http://purl.org/dc/elements/1.1/description According to researchers such as George Lakoff and Eleanor Rosch, basic level categories are the easiest to learn and most useful kinds of categories and tend to show up at an intermediate level in a general to specific hierarchy. These features make them ideal for categorizing information for consumption by non-information professionals and presenting that information in a variety of structures. <P> This session looks at how to incorporate basic level categories into taxonomy and ontology creation, how to identify basic level categories for different audiences (what is a basic level category changes with the level of expertise within a field), and how to develop a number of browsing classifications to support a deep personalization based on how people think rather than either explicit or role-based personalization. In addition, this approach helps bridge the gap between experts and non-experts both by using basic level categories as organizing elements, and by building ontology structures that mimic expert behaviors that chunk multiple components into single structures that utilize different size chunks and how those chunks are related. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2999 http://www.w3.org/2000/01/rdf-schema#label Basic Level Categories for Knowledge Representation: Combining Cognitive Science and Library Science
http://data.semanticuniverse.com/resource/semtech-2010-2999 http://purl.org/dc/elements/1.1/title Basic Level Categories for Knowledge Representation: Combining Cognitive Science and Library Science
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http://data.semanticuniverse.com/resource/semtech-2010-2792 http://purl.org/dc/elements/1.1/title Unhappy with Internal Corporate Search? Come Learn Tips and Tricks for Building a Controlled Vocabulary Ontology
http://data.semanticuniverse.com/resource/semtech-2010-2792 http://purl.org/dc/elements/1.1/description Employing a controlled vocabulary ontology makes searches more efficient and precise, and educates employees regarding corporate lingo, allowing them to contribute to the corpus of terms. It promotes internal corporate search to rival internet search. <P> We will cover our experiences implementing a controlled vocabulary ontology at Sandia National Laboratories, focusing on construction of this ontology from both content and the technical perspectives, including: <P> <ul> <li>The tool used building a polyhierarchical taxonomy</li> <li>Examples of two methods of indexing the content</li> <li>Tips on how to build future search capabilities</li> <li>Sorting suggestions based on preferred, alternate and related terms using SPARQL queries</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2792 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/bettina-k-schimanski
http://data.semanticuniverse.com/resource/semtech-2010-2792 http://purl.org/dc/elements/1.1/abstract Unhappy with internal corporate search? One improvement is to implement a controlled vocabulary ontology. We?ll present our work on the construction of an ontology from the content and technical perspectives.
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http://data.semanticuniverse.com/resource/semtech-2010-2967 http://purl.org/dc/elements/1.1/title Semantic Wikis and Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2967 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-2010-2967 http://purl.org/dc/elements/1.1/description Semantic web technologies have recently been applied to data publication in social media and web commerce areas. Wikis are a significant portion of web 2.0 phenomena. Semantic wikis combine the strength of both and offer great power and flexibility. This tutorial will cover what semantic wikis are, a brief history, the state of art, case study and examples, extensions, applications and trends, including examples such as Semantic MediaWiki (SMW), Freebase, Knoodl, etc. We will go deep into the popular SMW and its extensions. Attendees will learn how to build a social semantic web application in 30 minutes and get a provided disk for hands-on exercises as well as a base to build their own semantic web applications. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2967 http://www.w3.org/2000/01/rdf-schema#label Semantic Wikis and Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2935 http://purl.org/dc/elements/1.1/title Highly Available RDF Data at Enterprise Scale: The Bigdata® High-Availability Architecture
http://data.semanticuniverse.com/resource/semtech-2010-2935 http://purl.org/dc/elements/1.1/abstract To give the community an update on the direction of the high-availability architecture for bigdata®, an open-source horizontally-scaled general-purpose storage and computing fabric for ordered data and RDF.
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http://data.semanticuniverse.com/resource/semtech-2010-2935 http://www.w3.org/2000/01/rdf-schema#label Highly Available RDF Data at Enterprise Scale: The Bigdata® High-Availability Architecture
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http://data.semanticuniverse.com/resource/semtech-2010-2935 http://swrc.ontoware.org/ontology#keywords bigdata
http://data.semanticuniverse.com/resource/semtech-2010-2935 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/bryan-thompson
http://data.semanticuniverse.com/resource/semtech-2010-2935 http://purl.org/dc/elements/1.1/description Bigdata® is a pure-Java, open-source noSQL parallel database engine with a high-performance RDF layer. Over the last six months we have been working to create a shared-nothing High Availability (HA) architecture for bigdata® with service failover, a quorum model for persistent services, and shard affinity to improve utilization of compute resources. We have also designed a shared-disk HA architecture to support infinite history and general decoupling of compute resources from disk resources. With shared-nothing, data on disk is tightly coupled to the machine that hosts the services that manage that data, creating hotspots around particular data shards. The shared-disk HA architecture decouples the processors from the disk to enable massive compute concurrency and the parallel decomposition of read, write, and closure operations. Index data files in the shared disk model are stored on a separate distributed file system and the data services managing those files run on a compute cluster (all commodity hardware), taking ownership of data shards on an as-needed basis. This makes it possible to smoothly add or drop services in response to demand and creates tremendous opportunities to exploit parallelism in private clouds and "share" computing resources with batch-oriented clustered applications, such as map/reduce jobs, long-running graph queries, or the RDFS closure over hundreds of billions of triples. The bigdata® High Availability architecture enables: <ul><li>Retention of infinite database history. (Bigdata® is an immortal database with the ability to read from historical commit points.)</li> <li>Service failover and a high degree of operational continuity.</li> <li>Arbitrary compute concurrency via parallel decomposition of complex tasks.</li> <li>Partitioning of compute resources so that long running queries do not interfere with norma l l ow-latency query processing.</li> <li>Blindingly fast parallel closure of RDFS and OWL entailments.</li> </ul> <P>
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http://data.semanticuniverse.com/resource/marco-neumann http://www.w3.org/2000/01/rdf-schema#label Marco Neumann
http://data.semanticuniverse.com/resource/marco-neumann http://xmlns.com/foaf/0.1/name Marco Neumann
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http://data.semanticuniverse.com/resource/georgi-kobilarov http://www.w3.org/2000/01/rdf-schema#label Georgi Kobilarov
http://data.semanticuniverse.com/resource/georgi-kobilarov http://xmlns.com/foaf/0.1/name Georgi Kobilarov
http://data.semanticuniverse.com/resource/georgi-kobilarov http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/georgi-kobilarov http://www.w3.org/2001/vcard-rdf/3.0#title Managing Director
http://data.semanticuniverse.com/resource/georgi-kobilarov http://www.w3.org/2001/vcard-rdf/3.0#org Uberblic Labs
http://data.semanticuniverse.com/resource/christopher-j-o-baker http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/Person
http://data.semanticuniverse.com/resource/christopher-j-o-baker http://www.w3.org/2000/01/rdf-schema#label Christopher J O Baker
http://data.semanticuniverse.com/resource/christopher-j-o-baker http://xmlns.com/foaf/0.1/name Christopher J O Baker
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http://data.semanticuniverse.com/resource/christopher-j-o-baker http://www.w3.org/2001/vcard-rdf/3.0#title Industrial Research Chair in Knowledge Management and Semantic Technologies at Innovatia Inc., Canad
http://data.semanticuniverse.com/resource/christopher-j-o-baker http://www.w3.org/2001/vcard-rdf/3.0#org Innovatia Inc.
http://data.semanticuniverse.com/resource/advanced-document-sciences 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-2010-2903 http://purl.org/dc/elements/1.1/description The explosion of information within this landscape often evolves in silos with no clear visibility to the hidden semantic relationships between the data. These hidden relationships can have a significant business impact in the form of lost revenue, unmanaged risk, and missed saving or synergies with customers, partners, and suppliers. <P> Semantic technology provides an exciting opportunity to expose these relationships between data and provide the data management tools required to harvest information from today?s complex information landscape. <P> This presentation demonstrates the use of semantic technologies and techniques to provide visibility to complex relationships. Supplier management will be used as a case study to explore these relationships. <P> This presentation will explore the following topics: <ul> <li>Formal specification of relationships</li> <li>Use of RDFa and micro endpoints to publish semantic data</li> <li>Use of RDF triple store to manage relationships</li> <li>Use of SPARQL to query relationships</li> <li>The role of semantic search in information discovery</li> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2903 http://swrc.ontoware.org/ontology#keywords semantic-search
http://data.semanticuniverse.com/resource/semtech-2010-2903 http://swrc.ontoware.org/ontology#keywords rdfa
http://data.semanticuniverse.com/resource/semtech-2010-2903 http://swrc.ontoware.org/ontology#keywords integration
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http://data.semanticuniverse.com/resource/semtech-2010-2903 http://swrc.ontoware.org/ontology#keywords enterprise-semantics
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http://data.semanticuniverse.com/resource/semtech-2010-2903 http://www.w3.org/2000/01/rdf-schema#label Semantic Relationships Within the Enterprise
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http://data.semanticuniverse.com/resource/semtech-2010-2903 http://purl.org/dc/elements/1.1/title Semantic Relationships Within the Enterprise
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http://data.semanticuniverse.com/resource/semtech-2010-2903 http://purl.org/dc/elements/1.1/abstract The explosion of information within this landscape often evolves in silos with no clear visibility to the hidden semantic relationships between the data. Semantic technology can be used to expose these relationships.
http://data.semanticuniverse.com/resource/semtech-2010-2903 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-2010-2903 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/wayne-haubner
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://www.w3.org/2000/01/rdf-schema#label OASIS Integrated Collaboration Object Model (ICOM)
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://swrc.ontoware.org/ontology#keywords interoperability
http://data.semanticuniverse.com/resource/semtech-2010-3167 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/semtech-2010-3167 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/eric-chan
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://swrc.ontoware.org/ontology#keywords icom
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://purl.org/dc/elements/1.1/title OASIS Integrated Collaboration Object Model (ICOM)
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/laura-dragan
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://swrc.ontoware.org/ontology#keywords collaboration
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://swrc.ontoware.org/ontology#keywords integration
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http://data.semanticuniverse.com/resource/semtech-2010-3167 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-social-networks-and-collaboration
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://swrc.ontoware.org/ontology#keywords model
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/deirdre-lee
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://purl.org/dc/elements/1.1/abstract OASIS Integrated Collaboration Object Model (ICOM) Technical Committee representatives will present the concomitant representations of ICOM in RDF and UML, influenced by the interplay of RDF and UML modeling methodologies.
http://data.semanticuniverse.com/resource/semtech-2010-3167 http://swrc.ontoware.org/ontology#keywords ontology
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http://data.semanticuniverse.com/resource/semtech-2010-3167 http://purl.org/dc/elements/1.1/description OASIS Integrated Collaboration Object Model (ICOM) Technical Committee (http://wiki.oasis-open.org/icom), formed by Cisco Systems, DERI, EcoSpace, KnowledgeTree, and Oracle Corporation, specifies the standards for collaboration objects, along with the classes, attributes, relationships, constraints, and behavior for a broad range of collaboration activities in a complete, integrated, and interoperable collaboration environment. <P> The ICOM specifications will encompass and improve on a range of models which are part of existing standards and technologies to eliminate the impedances, promote seamless transitions between components, and reduce the fragmentation of collaboration tools. Defined from the outset for concomitant representations and transformations between RDF and UML, ICOM forms a bridge between the Semantic Web and object-oriented application development. <P> The work is inspired by Vannevar Bush, Doug Engelbart, and Tim Berners-Lee?s progressive visions towards ?the global network of knowledge to augment the human intellect?. The ICOM standards and technologies can supplement the network of collaboration entities. <P> ICOM is extensible and includes diverse classes of objects for: <ul> <li>Teamwork: shared workspaces, discussion forums, real-time conferences, presence, etc.</li> <li>Communication: e-mail, instant message, telephony, RSS, etc.</li> <li>Content: text and multi-media contents, contextual connections, taxonomies, folksonomies, tags, saved searches, etc.</li> <li>Coordination: address books, calendars, tasks, journals, etc.</li> <li>Social networking: articulated social networks among users, communities, groups, activities, wiki pages, blogs, recommendations, social bookmarking, etc.</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2879 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2010-2879 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/alexandre-passant
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http://data.semanticuniverse.com/resource/semtech-2010-2879 http://www.w3.org/2000/01/rdf-schema#label SMOB - A Framework for Semantic MicrOBlogging
http://data.semanticuniverse.com/resource/semtech-2010-2879 http://swrc.ontoware.org/ontology#keywords sioc
http://data.semanticuniverse.com/resource/semtech-2010-2879 http://purl.org/dc/elements/1.1/description SMOB is an open-source Semantic MicrOBlogging framework that enables a distributed and semantic microblogging experience, using state-of-the-art Linked Data and Semantic Web technologies. To enable data-ownership and portability, SMOB is based on an architecture relying on distributed SMOB hubs that anyone can install, each hub communicating with other ones (to share status messages and following/followers), using SPARQL Update via HTTP. SMOB is available under the terms of the GNU GPL at http://smob.me <P> In this session, we will discuss: Issues with current microblogging systems Overview of SMOB Architecture of SMOB and communication between Hubs <P>
http://data.semanticuniverse.com/resource/semtech-2010-2879 http://purl.org/dc/elements/1.1/title SMOB - A Framework for Semantic MicrOBlogging
http://data.semanticuniverse.com/resource/semtech-2010-2879 http://purl.org/dc/elements/1.1/abstract We will present the principles and architecture of SMOB (http://smob.me) an open-source Semantic MicrOBlogging framework enabling a distributed and semantic microblogging experience, using Linked Data and Semantic Web technologies
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http://data.semanticuniverse.com/resource/wayne-haubner http://xmlns.com/foaf/0.1/name Wayne Haubner
http://data.semanticuniverse.com/resource/wayne-haubner http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com/uploads/images/bios/1858.jpg^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/wayne-haubner http://www.w3.org/2001/vcard-rdf/3.0#title VP Development
http://data.semanticuniverse.com/resource/wayne-haubner http://www.w3.org/2001/vcard-rdf/3.0#org SAP
http://data.semanticuniverse.com/resource/orbis-technologies-inc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/net/biblio#Organization
http://data.semanticuniverse.com/resource/orbis-technologies-inc http://xmlns.com/foaf/0.1/name Orbis Technologies, Inc.
http://data.semanticuniverse.com/resource/orbis-technologies-inc http://xmlns.com/foaf/0.1/member http://data.semanticuniverse.com/resource/steve-hamby
http://data.semanticuniverse.com/resource/orbis-technologies-inc http://www.w3.org/2000/01/rdf-schema#label Orbis Technologies, Inc.
http://data.semanticuniverse.com/resource/semtech-2010-3181 http://purl.org/dc/elements/1.1/title Semantics for Emergency Response and Disaster Management Systems
http://data.semanticuniverse.com/resource/semtech-2010-3181 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/bob-smith
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http://data.semanticuniverse.com/resource/semtech-2010-3181 http://swrc.ontoware.org/ontology#keywords water
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http://data.semanticuniverse.com/resource/semtech-2010-3181 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-3181 http://purl.org/dc/elements/1.1/abstract Effective emergency response to a building requires ongoing situation awareness. Ontology technologies aid in identifying relevant data, formatting information for exchange and presenting information to users, systems, and devices.
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http://data.semanticuniverse.com/resource/semtech-2010-3181 http://purl.org/dc/elements/1.1/description <h4>PART I | Enabling Emergency Response through Information Exchange Standards</h4> <P> Michelle A. Raymond, Systems Architect, Michelle A. Raymond<br> Steven R. Ray, Distinguished Research Fellow, Carnegie Mellon University <P> When a facility requires emergency response, knowing what to communicate with whom is critical. The objective of the Open Floor Plan Display/Exchange (OFPD/X) project is to develop a system for interactive real-time data reporting using open standards. Current efforts include the Golden Gate Safety Network (GGSN) and Carnegie Mellon University Silicon Valley (CMUSV) Disaster Management Initiative, Floor Plan Markup Language Data Dictionary at the Ontolog Building Service Performance project, and ongoing collaboration with standards development organizations and technical committees. The Building Information Service ontology information structure will include the structure of access policies, building information and automation system data types, and incident types and properties. This ontology is central to interoperability on a large scale. What to communicate, methods of communication, and who receives what are specified in the instance ontology. The ontology specifies both required type of information and associations with a facility's specific building information. <P> This session will explore the following topics: <ul> <li>System information management requirements</li> <li>Ontology structure and application requirements</li> <li>Strengths and weaknesses of applicable standards</li> <li>Gaps in current ontology technologies within the facilities and emergency domains</li> <li>Steps forward</li> </ul> <hr width="10%" /> <P> <h4>PART II | Disaster Management Systems: A Proposal for Conducting Haitian Water System Recovery Planning</h4> <P> Bob Smith, Sustainability Projects, Tall Tree Labs<br> Rex Brooks, President & CEO, Starbourne Communications Design <P> Water systems are complex, vulnerable and essential. We will walk the audience through the use of Model-Based Semantic Analysis of Linked Data for the purpose of designing a resilient and reliable Water System for Haiti as it recovers from the recent disaster. Specific attention will be given to planning for future emergencies in countries prone to both earthquakes and hurricanes. <P> We will focus on the following points: <ul> <li>Meaning of resilience</li> <li>Sewage systems, earthquakes and major storms</li> <li>Monitoring system flows</li> <li>Testing interoperability of linked data sources</li> <li>Using Stimulus Funding reports as data source for business intelligence</li> <li>Environmental sustainability</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3268 http://purl.org/dc/elements/1.1/abstract Demonstrate the use of semantics to create a better travel experience.
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http://data.semanticuniverse.com/resource/semtech-2010-3268 http://purl.org/dc/elements/1.1/description The majority of today's business and leisure travel is booked online. The post-booking experience typically leaves travelers with the predicament of gathering together important trip data (flight numbers, hotel address, rental car confirmation number, frequent travel program identification, check-in time, etc.) that is dispersed throughout several booking confirmation emails. Join Andy Denmark, VP of Engineering at TripIt and explore how semantic technology has transformed this unstructured data into a structured travel itinerary and revolutionized the post-booking travel experience. Additional discussion will examine semantic technology and the future of travel, with a focus on the implications for individual travelers and corporate travel programs. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3268 http://purl.org/dc/elements/1.1/title Semantics and Travel
http://data.semanticuniverse.com/resource/semtech-2010-3268 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/andy-denmark
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http://data.semanticuniverse.com/resource/semtech-2010-3236 http://purl.org/dc/elements/1.1/title Real-Time SemanticWeb with Twitter Annotations
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http://data.semanticuniverse.com/resource/semtech-2010-3236 http://purl.org/dc/elements/1.1/abstract We discuss a semantic data aggregator which brings together structured microblog annotations with Semantic Web vocabularies and best practices in order to augment the Semantic Web with real-time, user-driven data, enabling a new breed of query services.
http://data.semanticuniverse.com/resource/semtech-2010-3236 http://purl.org/dc/elements/1.1/description The ability of millions of average Web users to publish short, timestamped and even geotagged microblog posts, at a moment's notice, presents new opportunities for real-time and location-based services. Much as these services are changing the nature of search on the Web, so the Semantic Web will be both challenged and enhanced by real-time content. Furthermore, the ability to annotate microblog posts using highly expressive vocabularies, as in Twitter's upcoming Twannotations functionality, will provide an endless stream of up-to-date, structured information about the world. In this presentation, we discuss a semantic data aggregator which brings together structured microblog annotations with Semantic Web vocabularies and best practices in order to augment the Semantic Web with real-time, user-driven data, enabling a new breed of query services. Emerging formats, modeling issues, publication and data ownership of microblog content, data storage and basic techniques for real-time, real-place semantic search are presented. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2773 http://www.w3.org/2000/01/rdf-schema#label Semantic Applications in the Financial Services Industry
http://data.semanticuniverse.com/resource/semtech-2010-2773 http://purl.org/dc/elements/1.1/title Semantic Applications in the Financial Services Industry
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http://data.semanticuniverse.com/resource/semtech-2010-2773 http://purl.org/dc/elements/1.1/description There are three main benefits of semantic technologies: <ol> <li>The ability to structure unstructured data</li> <li>The ability to quickly and efficiently integrate data from many disparate sources</li> <li>The ability to deeply mine and identify correlations and relationships between data points that would otherwise require a supercomputer</li> </ol> This presentation will include real examples that highlight each of the major benefits of semantic technologies. Applications to be illustrated include Mutual Fund Information Portal, Counterparty Risk and Exposure, and Alternative Investments Document Processing. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2773 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/drew-warren
http://data.semanticuniverse.com/resource/semtech-2010-2773 http://purl.org/dc/elements/1.1/abstract To educate the audience on the practical application and benefits of semantic technologies in the financial services space.
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http://data.semanticuniverse.com/resource/rensselaer-polytechnic-institute http://www.w3.org/2000/01/rdf-schema#label Rensselaer Polytechnic Institute
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http://data.semanticuniverse.com/resource/semtech-2010-2948 http://purl.org/dc/elements/1.1/description The W3C?s Data Access Working Group is currently developing a suite of specifications for the next generation of SPARQL, the RDF querying language. Included in this suite is a specification for a minimal, uniform, HTTP protocol for managing RDF graphs. This protocol is meant to be a complement to the SPARQL Update language also being developed simultaneously and the intent is to define a ?RESTful? protocol for managing RDF content. However, the question of what it means for a protocol to be RESTful and what is the appropriate use of HTTP for accessing and managing RDF graphs natively are difficult. <P> In this presentation, the author will attempt to shed some light on what it means for a protocol to be RESTful, why this is important for a protocol that manages RDF, and some of the open questions around the ongoing effort to standardize such a protocol. <P> In particular, the following questions will be discussed: <ul> <li>What are the various kinds of URIs that an RDF graph can have and the consequences of each on how the graph can be managed in a protocol?</li> <li>Are the constraints of a RESTful protocol appropriate for the various ways in which we need to manipulate an RDF graph?</li> <li>How would such a protocol support updating RDF using alternative syntaxes (RDFa and GRDDL for example)?</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2948 http://www.w3.org/2000/01/rdf-schema#label The Characteristics of a RESTful Semantic Web and Why They Are Important
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http://data.semanticuniverse.com/resource/semtech-2010-2948 http://purl.org/dc/elements/1.1/title The Characteristics of a RESTful Semantic Web and Why They Are Important
http://data.semanticuniverse.com/resource/semtech-2010-2948 http://purl.org/dc/elements/1.1/abstract In this presentation, the author will attempt to shed light on what it means for a protocol to be RESTful, why it is important for a protocol that manages RDF, and some of the open questions around the ongoing effort to standardize such a protocol.
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http://data.semanticuniverse.com/resource/semtech-2010-3148 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3148 http://purl.org/dc/elements/1.1/title Description Logic: A Formal Foundation for Ontology Languages and Tools (Part 2)
http://data.semanticuniverse.com/resource/semtech-2010-3148 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/ian-horrocks
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http://data.semanticuniverse.com/resource/semtech-2010-3148 http://purl.org/dc/elements/1.1/description Description Logics (DLs) are best known as the basis for widely used ontology languages and reasoning systems. We will consider how reasoning systems for different OWL profiles are actually implemented, and gaze into the future of ontology systems through recent research. We explore: Different kinds of reasoning needed in ontology applications Examine how DL/ontology systems perform such reasoning tasks Study the tableau reasoning technique widely used in OWL (2) DL reasoners Study the deductive technique widely used in OWL 2 EL reasoners Study the query rewriting technique widely used in OWL 2 QL reasoners <P>
http://data.semanticuniverse.com/resource/semtech-2010-3148 http://www.w3.org/2000/01/rdf-schema#label Description Logic: A Formal Foundation for Ontology Languages and Tools (Part 2)
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http://data.semanticuniverse.com/resource/semtech-2010-2930 http://swrc.ontoware.org/ontology#keywords rdfa
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http://data.semanticuniverse.com/resource/semtech-2010-2930 http://www.w3.org/2000/01/rdf-schema#label Semantic Tools for More Profitable Online Commerce
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http://data.semanticuniverse.com/resource/semtech-2010-2930 http://purl.org/dc/elements/1.1/title Semantic Tools for More Profitable Online Commerce
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http://data.semanticuniverse.com/resource/semtech-2010-2930 http://purl.org/dc/elements/1.1/description <h4>PART I | Increasing Product and Service Visibility through Front-end Semantic Web</h4> <P> Jay Myers, Lead Web Development Engineer, bestbuy.com <P> Web developers have been heavily focused on providing visually rich experiences to entice users to purchase goods and services. With emerging front-end semantic technologies, there are now a number of ways to increase visibility of product offers, services, and store locations on the web using semantics. By utilizing HTML markup standards like Microformats, RDFa, and Microdata, front-end web developers can contribute to a web of product data, enabling enhanced machine learning while retaining rich visual experiences for humans. This presentation highlights current in-production semantic solutions, discusses challenges, and explores future opportunities for front-end semantic web. <hr width="10%" /> <P> <h4>PART II | SEO, RDF and GoodRelations - An Implementation by a Major Industry Online Retailer</h4> <P> Barbara H. Starr, Semantic Web Strategist, Ontologica<br> Paul Bruemmer, SEO/SEM Executive Consultant, PB Communications <P> A major online retailer is in the process of implementing RDFa and the goodrelations ontology on their website. They will be amongst the first members of the online retail world to take this step. The session will discuss the story and process of the adoption of GoodRelations and RDFa. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3194 http://purl.org/dc/elements/1.1/description New tools emerge every day that apply semantic technologies to text, but what about video? Traditionally video has been seen as a black box for metadata, but this is changing with the emergence of captioning, translation and user tagging. This presentation will look at real world examples of how leading semantic extraction and content APIs, as well as Linked Data sources, are being used to enrich the video viewing experience. ViewChange.org, funded by the Bill & Melinda Gates Foundation, is not only mashing up these APIs, but using them to create social change. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3194 http://www.w3.org/2000/01/rdf-schema#label Semantic Web Tools for Video and Social Change
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http://data.semanticuniverse.com/resource/semtech-2010-3337 http://purl.org/dc/elements/1.1/description Over the last several years there has been increasing commercial interest in semantic technologies, as evidenced by this conference, with many anticipating that these technologies will also benefit software engineering and vice versa. Since the initial SWESE workshop five years ago, there have been a number of attempts to bring together languages and tools, such as the Unified Modeling Language (UML), originally developed to support software engineering, and in particular, objectoriented development, with Semantic Web languages such as RDF and OWL. UML has since evolved as an increasingly general graphical modeling notation, with significant tooling support, and is used in a variety of engineering disciplines, ranging from systems engineering to business process modeling and domain specific design. The Semantic Web Best Practice and Deployment Working Group (SWBPD) in W3C included a Software Engineering Task Force (SETF) to investigate potential benefits which this series of workshops has continued to move forward. The Object Management Group?s related standardization effort, represented to date in the Ontology Definition Metamodel (ODM), has expanded to address mappings from the Meta Object Facility (MOF) to RDF, APIs for knowledge base access, and domainspecific interfaces such as those defined in the Common Terminology Services (CTS2) effort. Recently, more and more researchers are also investigating how to bridge the two kinds of languages so as to improve guidance and traceability in software development. <P> This half-day workshop, including keynote and invited presentations as well as several technical talks, will present competing and complementary visions for Semantic Web enabled software engineering, and close with a panel session to discuss requirements and directions participants have for the bridge between these disciplines. The workshop is open to all members of the SemTech community, and we invite anyone who is interested in this focus area to join us. <br> <P> Full abstracts for the individual talks, including invited presentations and our keynote, on the workshop site, which is: <br> http://www.abdn.ac.uk/~r01srt7/swese2010/index.php <P> <br> <P> <strong>Program</strong><br><br> 8:30 am to 9:30 am: Keynote<br><br> <strong>Semantic Web Enabled Software Engineering - State of the Art and Near Term Roadmap</strong><br> Jeff Z. Pan, University of Aberdeen and Elisa Kendall, Sandpiper Software <br><br> 9:30 am to 9:45 am: Coffee Break <br><br> 9:30 am to 10:45 am: Refereed Papers<br><br> <strong>Validating Graph-based Modeling Constraints by Transformation to Ontology Language</strong><br> Tobias Walter, University of Koblenz-Landau, Hannes Schwarz, University of Koblenz-Landau, and Yuan Ren, University of Aberdeen<br><br> <strong>Modelling and Validating Multilevel Models with OWL FA</strong><br> Nophadol Jekjantuk, University of Aberdeen, Gerd Gröner, University of Koblenz-Landau, Jeff Z. Pan, University of Aberdeen, and Yuting Zhao, University of Aberdeen<br><br> <strong>Semantic Web-based Source Code Search</strong> Iman Keivanloo, Laleh Roostapour, Philipp Schugerl, and Juergen Rilling, Concordia University <br><br> 10:45 am to 11:00 am: Coffee Break <br><br> 11:00 am to 12:00 pm Invited Talks<br><br> <strong>The Challenges of Managing Emerging Semantic Technology Projects</strong><br> Mark Arquette, MD Anderson Cancer Center <br><br> <strong>Application of Semantic Technologies to Software and Systems Engineering at JPL</strong><br> Steven Jenkins, Jet Propulsion Laboratory, California Institute of Technology <br><br> 12:00 pm to 12:30 pm Panel Discussion<br><br> <strong>Promoting SWESE Methods & Technologies - Where Do We Go From Here?</strong><br> Moderators: Jeff Z. Pan and Yuting Zhao, University of Aberdeen<br><br> Participants: <br>Mark Arquette, MD Anderson Cancer Center <br>Steven Jenkins, Jet Propulsion Laboratory, California Institute of Technology<br>Elisa Kendall, Sandpiper Software<br>Evan Wallace, US National Institute of Standards and Technology <br><br><br> <P> <strong>Workshop Organizers:</strong><br> Jeff Pan, Yuting Zhao, Kalina Bontcheva, Ljiljana Stojanovic and Elisa Kendall <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2828 http://purl.org/dc/elements/1.1/description The Semantic Web is crossing the chasm between the innovative focus of pioneers and early adopters to the pragmatic focus of early mainstream adopters. In this talk, Dr. Daniel will lay out a six-step roadmap to go from typical data practices to having content which fully participates in the Semantic Web. Those steps can be remembered with the mnemonic SAFARI: <ul> <li>Start Simple: Mapping current data and metadata to the Dublin Core's "First Fifteen" elements</li> <li>Add to the Core: Adding additional Dublin Core metadata elements and local elements; and integrating multiple datasets together</li> <li>Faceted Taxonomy: Shifting from text values in the various fields to a faceted taxonomy with managed lists of values</li> <li>Adopt Standards: Agreeing to and using standardized vocabularies for key parts of the business</li> <li>RDF and Web Identifiers: Switching to URL identifiers for field names, vocabulary names, vocabulary values, etc., relating this to RDF, and hiding the details from normal situations</li> <li>Integrate: Integrating local information with the Linked Data cloud, controlling access, and putting the broad array of data to use</li> </ul> The roadmap will be useful for managers and senior technologists as they plan for the future of their organization's content and the more sophisticated uses of that content enabled by semantic technologies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2828 http://www.w3.org/2000/01/rdf-schema#label Six Step SAFARI from the Dublin Core to the Semantic Web
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http://data.semanticuniverse.com/resource/semtech-2010-2828 http://purl.org/dc/elements/1.1/abstract Give attendees a roadmap to get from providing no extra information about their structured and unstructured content to making that content a full participant in the Semantic Web.
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http://data.semanticuniverse.com/resource/semtech-2010-2874 http://purl.org/dc/elements/1.1/title Application of Fundamentals of Artificial Intelligence Components (Planners and Heuristic Search) to Distributed Reasoning on Very Large Data Sets
http://data.semanticuniverse.com/resource/semtech-2010-2874 http://www.w3.org/2000/01/rdf-schema#label Application of Fundamentals of Artificial Intelligence Components (Planners and Heuristic Search) to Distributed Reasoning on Very Large Data Sets
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http://data.semanticuniverse.com/resource/semtech-2010-2874 http://purl.org/dc/elements/1.1/description Reasoners for the semantic web have a variety of architectures and leverage different algorithms. This session focuses on architectural approaches based on Planners and Heuristic search that lend themselves to reasoners with search-like requirements that must search through very large amounts of data (potentially in the peta-bytes) to find complex results requested by the client to the reasoner. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2874 http://purl.org/dc/elements/1.1/abstract To show how to apply basic theoretical principles of planners and heuristic search in building effective reasoners for semantic web reasoning
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http://data.semanticuniverse.com/resource/semtech-2010-2842 http://purl.org/dc/elements/1.1/abstract Hypios.com is a social marketplace for solutions. We would like to present the Social Semantic Web technologies we are using and developing to bring advanced functionalities to users.
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http://data.semanticuniverse.com/resource/semtech-2010-2842 http://purl.org/dc/elements/1.1/description Hypios.com connects companies that face a certain problem to a social network of competent problem solvers (often researchers and Ph.D.'s). Our Research Department is building a Social Semantic Web technology to support the problem-solving network. We shall present: <P> The structure and objectives of Problem Solving Networks Scenarios of use of Ontologies in the Problem Solving Social Networks Benefits of Semantic Technologies for Problem-Solver Matching and Recommender Systems How to use Linked Data to find Experts on a particular topic Collecting Traces on the Social Web and putting them in Semantic Form in order to gain additional knowledge about users and offer a personalized service Outlook for the future of Semantic Problem Solving Networks <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3028 http://purl.org/dc/elements/1.1/description One of the major challenges inhibiting the effective use of distributed resources in government systems stems from the inability to effectively find, understand, and process information across heterogeneous mission domains. The sheer amount of available data and data providers, coupled with the manually-driven, time-intensive processes typically utilized to access these providers, prevent decision makers from receiving the information they need in a timely manner to decide on critical mission threads. <P> In order to provide a cross-domain information and resource sharing platform capable of supporting unanticipated users and uses, we developed the Resource Broker Framework (RBF). The RBF leverages semantics-driven federated brokering agents and a modular software component framework for dynamically composing and tasking heterogeneous resources including sensors, processors, databases, networks, and even humans into resilient, mission-oriented workflows. <P> This presentation will discuss the concept and architecture of the RBF, specifically focusing on the use of semantics technologies for resource registration, discovery, and planning to form complex workflow specifications. The RBF?s pluggable workflow composition service utilizes a SPARQL-driven, template-based planning approach powered by a generative hierarchical task network planner. Additionally, we will discuss the RBF?s semantic resource registry which provides a semantic interface to XSD-based, non-semantically described resources and facilitates intelligent discovery through resource metadata augmented with OWL markup. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3028 http://www.w3.org/2000/01/rdf-schema#label Semantic Framework for Automatic Resource Brokering in Distributed Government Systems
http://data.semanticuniverse.com/resource/semtech-2010-3028 http://purl.org/dc/elements/1.1/abstract This presentation will discuss the development of a semantic framework for automatic resource brokering as a mechanism to improve information discovery and acquisition capabilities across distributed government systems.
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http://data.semanticuniverse.com/resource/semtech-2010-3028 http://purl.org/dc/elements/1.1/title Semantic Framework for Automatic Resource Brokering in Distributed Government Systems
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http://data.semanticuniverse.com/resource/semtech-2010-3217 http://purl.org/dc/elements/1.1/description True Knowledge is a Cambridge, UK based internet technology business. We have developed a complete question answering system that combines a knowledge base of over 250m triples; a query language that represents questions in language-independent form; a query-answering system that answers these queries using a generalised inference system and a natural language translation system that takes questions in English (or potentially any other language) and translates them to the queries. The user experience is thus getting direct accurate answers to questions on any topic. <P> The system is live and is used by millions of internet users. It can be tried on www.trueknowledge.com <P> The talk will explain how the system works, what the remaining challenges are and will include a live demonstration <P>
http://data.semanticuniverse.com/resource/semtech-2010-3217 http://purl.org/dc/elements/1.1/title True Knowledge: Open-Domain Question Answering at Scale using a Triple Store and Inference
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http://data.semanticuniverse.com/resource/semtech-2010-3217 http://purl.org/dc/elements/1.1/abstract An overview of True Knowledge's application for automatic question answering, a system which combines natural language translation with structured data and a query language to deliver a fully automated solution.
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http://data.semanticuniverse.com/resource/semtech-2010-3010 http://purl.org/dc/elements/1.1/title Configuring the Cloud: Automated Planning As a Semantic Technology
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http://data.semanticuniverse.com/resource/semtech-2010-3010 http://purl.org/dc/elements/1.1/description Automated, domain-independent planning is one of the core areas within AI. Yet, despite its AI origin, it has rarely been integrated with semantic technologies like OWL, RDF, and SPARQL. <P> In this talk we will discuss why automated planning is under-utilized in semantic technologies, and we'll discuss a real-world example of how it can solve real-world problems. As a semantic technology, our automated planning solution combines the expressive power of OWL-based automated reasoning, via Pellet, with the power of hierarchical, domain-independent planning. As a real-world example, we will present Elastra's automation architecture for configuration management in a cloud computing environment. Elastra uses planning to automate deployment of services onto virtualized environments. <P> This presentation will explore the following topics: <ul> <li>Introduction to automated, domain-independent planning technology, and its applicability to solve real-world problems</li> <li>HotPlanner - hierarchical planner that uses semantic techology (based on OWL-S) to solve planning problems</li> <li>Elastra configuration management for cloud computing environment</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-3010 http://purl.org/dc/elements/1.1/abstract Describe Hierarchical Planning as an application of semantic technologies using Clark & Parsia's HotPlanner, together with Pellet reasoner, in Elastra's cloud management offerings.
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http://data.semanticuniverse.com/resource/semtech-2010-2754 http://purl.org/dc/elements/1.1/abstract Natural language processing can identify key data entities such as Who, What, When, and Where and relationships between them and present the results using government standards such as NIEM and UCore
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http://data.semanticuniverse.com/resource/semtech-2010-2754 http://purl.org/dc/elements/1.1/description Natural Language Processing can be used for content stored in many different formats to flexibly extract entities and relationships needed by different Communities of Interest instead of enforcing a one-size-fits-all type of entity extraction. As new requirements are identified (e.g., the impact of Swine Flu), new rules can be added quickly and easily so the new entities can be extracted and tagged within hours of the requirement being identified. <P> The extracted entities can be stored in both a Triple Store and in a relational database. They can also be automatically tagged with XML tags to automatically create XML documents with all the content tagged with either or both of the government information sharing standards: NIEM and/or UCore. The resulting fine grained tagged documents provide transparent data easily used in loosely coupled applications. <P> This transparent data with NIEM or UCore conformant tags can be automatically created from many sources, including the following: <ul> <li>Cross-domain internal sources such as after action reports, findings, intelligence analyses, analyst or investigator notes, Email, and internal legacy data on file servers in hundreds of different formats</li> <li>Third party files such as wire tap transcripts, files and Email seized under a subpoena, or suspicious activity reports</li> <li>Public sources such as web pages, blogs, news wire, and broadcast news sources</li> <li>Memo and notes fields in relational databases</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2754 http://www.w3.org/2000/01/rdf-schema#label The Use of Semantic Analytics to Achieve Data Transparency Using Government Standards for Information Sharing (Face-to-Face Session)
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http://data.semanticuniverse.com/resource/semtech-2010-3111 http://purl.org/dc/elements/1.1/abstract Agenda 6:15pm Lotico Semantic Social Networks - Marco Neumann 6:30pm Smart Mobs - Howard Rheingold 7:30pm Meet Semantic Web Community Organizers from Around the World 8:15pm Closing
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http://data.semanticuniverse.com/resource/semtech-2010-3111 http://purl.org/dc/elements/1.1/title Meetup of Meetups: Semantic Social Networks and Smart Mobs: Special Guest Howard Rheingold
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http://data.semanticuniverse.com/resource/semtech-2010-3111 http://purl.org/dc/elements/1.1/description <b>Agenda</b> <P> 6:15pm Lotico Semantic Social Networks - Marco Neumann<br /> 6:30pm Smart Mobs - Howard Rheingold<br /> 7:30pm Meet Semantic Web Community Organizers from Around the World<br /> 8:15pm Closing<br /> <P> Smart mobs emerge when communication and computing technologies amplify human talents for cooperation. The impacts of smart mob technology already appear to be both beneficial and destructive, used by some of its earliest adopters to support democracy and by others to coordinate terrorist attacks. The technologies that are beginning to make smart mobs possible are mobile communication devices and pervasive computing - inexpensive microprocessors embedded in everyday objects and environments. Already, governments have fallen, youth subcultures have blossomed from Asia to Scandinavia, new industries have been born and older industries have launched furious counterattacks. <P> Street demonstrators in the 1999 anti-WTO protests used dynamically updated websites, cell-phones, and "swarming" tactics in the "battle of Seattle." A million Filipinos toppled President Estrada through public demonstrations organized through salvos of text messages. <P> The pieces of the puzzle are all around us now, but haven't joined together yet. The radio chips designed to replace barcodes on manufactured objects are part of it. Wireless Internet nodes in cafes, hotels, and neighborhoods are part of it. Millions of people who lend their computers to the search for extraterrestrial intelligence are part of it. The way buyers and sellers rate each other on Internet auction site eBay is part of it. Research by biologists, sociologists, and economists into the nature of cooperation offer explanatory frameworks. At least one key global business question is part of it - why is are some companies profiting from enhanced wireless Internet services while some mobile operators struggle to avoid failure? <P> The people who make up smart mobs cooperate in ways never before possible because they carry devices that possess both communication and computing capabilities. Their mobile devices connect them with other information devices in the environment as well as with other people's telephones. Dirt-cheap microprocessors embedded in everything from box tops to shoes are beginning to permeate furniture, buildings, neighborhoods, products with invisible intercommunicating smartifacts. When they connect the tangible objects and places of our daily lives with the Internet, handheld communication media mutate into wearable remote control devices for the physical world. <P> Media cartels and government agencies are seeking to reimpose the regime of the broadcast era in which the customers of technology will be deprived of the power to create and left only with the power to consume. That power struggle is what the battles over file-sharing, copy-protection, regulation of the radio spectrum are about. Are the populations of tomorrow going to be users, like the PC owners and website creators who turned technology to widespread innovation? Or will they be consumers, constrained from innovation and locked into the technology and business models of the most powerful entrenched interests? <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3009 http://purl.org/dc/elements/1.1/title User Interfaces for Semantic Web: Do They Have to Be Ugly?
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http://data.semanticuniverse.com/resource/semtech-2010-3009 http://purl.org/dc/elements/1.1/description Can a breakthrough happen with data and algorithms alone? Without prettiness? <P> In this talk, I'll try to expose some reasons why so many interfaces look like they were stolen from the eighties. We'll go through areas of inherent difficulties of representing and manipulating semantic data and see which problems can be addressed through pure work, which through better platform technologies, and which simply need a good user interface designer. <P> Emphasis will be on web interfaces and technologies around them-from HTML, RDFa, JavaScript, visualization libraries to lately very hot MicroData. What's wrong that projects like Frebase Parallax and Simile aren't (yet) a common framework? <P>
http://data.semanticuniverse.com/resource/semtech-2010-3009 http://swrc.ontoware.org/ontology#keywords html5
http://data.semanticuniverse.com/resource/semtech-2010-3009 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-3009 http://purl.org/dc/elements/1.1/abstract Semantic Web is growing - RDF, Open Linked Data, first major consumers. But one thing remains constant: user interfaces aren't pretty. Why?
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http://data.semanticuniverse.com/resource/semtech-2010-3055 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/atanas-kostadinov-kiryakov
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http://data.semanticuniverse.com/resource/semtech-2010-3055 http://purl.org/dc/elements/1.1/description Reason-able views represent a sort of search engines, or indices that allow efficient access to parts of the Linking Open Data (LOD) cloud. Linked Data Semantic Repository (http://ldsr.ontotex.com) combines several of the central datasets of LOD (e.g. DBPedia, Freebase, Geonames) in a repository containing more than 1B explicit statements. After inference, there are 4B different retrievable statements describing about 250M resources. For some entities LDSR contains fairly big volumes of data (e.g. 1380 statements for San Francisco), thus, a good visualisation facility need to find a way to present a ?good? fraction of the information. We have developed a mechanism, called RDF priming, for ranking the importance of the information in an RDF graph with respect to both its topology (e.g. PageRank) and the relevance to specific query and user context. We present the benefits of RDF priming for LDSR exploration, along with the technical solution allowing us to perform ranking in a graph of several billion statements in real time. We apply the CUDA architecture that allows using NVIDIA Graphical Processing Units (GPU) for massively parallel computations. In this context, a CUDA card priced around $400 performs several times faster than a dual-CPU server worth $4000. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3055 http://swrc.ontoware.org/ontology#keywords gpu
http://data.semanticuniverse.com/resource/semtech-2010-3055 http://purl.org/dc/elements/1.1/title Using GPUs to Browse Through Billions of Linked Data Facts
http://data.semanticuniverse.com/resource/semtech-2010-3055 http://swrc.ontoware.org/ontology#keywords data-management
http://data.semanticuniverse.com/resource/semtech-2010-3055 http://www.w3.org/2000/01/rdf-schema#label Using GPUs to Browse Through Billions of Linked Data Facts
http://data.semanticuniverse.com/resource/semtech-2010-3055 http://purl.org/dc/elements/1.1/abstract Several linked data datasets are loaded in a repository to facilitate their comprehension and usage. A mechanism for context-aware ranking enables better browsing; massively parallel implementation using GPU is presented.
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http://data.semanticuniverse.com/resource/semtech-2010-2988 http://purl.org/dc/elements/1.1/abstract To highlight the importance of and suggest a partial solution to the growing problems related to the lack of URI management guidelines. If unaddressed these problems could severely retard the growth of the semantic web and exploitation of linked open data.
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http://data.semanticuniverse.com/resource/semtech-2010-2988 http://www.w3.org/2000/01/rdf-schema#label Avoiding a Semantic Web Road Block: URI Management and Ontology Evolution
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http://data.semanticuniverse.com/resource/semtech-2010-2988 http://swrc.ontoware.org/ontology#keywords ontology-driven-applications
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http://data.semanticuniverse.com/resource/semtech-2010-2988 http://purl.org/dc/elements/1.1/description We highlight the importance of creating a set of guidelines for managing URIs during ontology evolution and linking open data. We examine some potential and actual negative impacts of making the wrong decision. For example, the new version of SKOS changes the semantics for existing terms without changing the URI. This adds a heavy load on developers of ontology-driven applications to keep them from breaking. Alternatively, minting a whole set of new URIs when the meaning for most of the terms is unchanged, causes an unnecessary proliferation of URIs that adds computational and conceptual overheads. We suggest a way forward based on examining two root causes of the problem: 1) URIs are overloaded and 2) there is no good technology for change management. As linked data grows and as applications are driven more and more by ontologies, the negative impacts of inadequate URI management could severely retard the growth of the semantic web. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2988 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-f-uschold
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http://data.semanticuniverse.com/resource/semtech-2010-3290 http://purl.org/dc/elements/1.1/title Socially Powered eLearning
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http://data.semanticuniverse.com/resource/semtech-2010-3290 http://purl.org/dc/elements/1.1/description More and more learners are relying on social networks of friends, mentors, and experts (so called informal learning ) to acquire necessary knowledge for their jobs and careers. This session will describe some of the recent activity at DERI in using Social Networking to enable informal learning. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3290 http://purl.org/dc/elements/1.1/abstract More and more learners are relying on social networks of friends, mentors, and experts (so called informal learning ) to acquire necessary knowledge for their jobs and careers. This session will describe some of the recent activity at DERI in using Social Networking to enable informal learning.
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http://data.semanticuniverse.com/resource/semtech-2010-3212 http://purl.org/dc/elements/1.1/title Experts Panel on Semantic Complex Event Processing
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http://data.semanticuniverse.com/resource/semtech-2010-3212 http://purl.org/dc/elements/1.1/description Details to come shortly <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2956 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-wilkinson
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http://data.semanticuniverse.com/resource/semtech-2010-2956 http://www.w3.org/2000/01/rdf-schema#label Monitoring Healthcare Innovation: A Case Study in Using OWL, Linked Data and RDFa
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http://data.semanticuniverse.com/resource/semtech-2010-2956 http://purl.org/dc/elements/1.1/description The UK?s National Health Service (NHS) is the largest healthcare provider in the world. Allocating its resources in such a way as to give optimal service requires efficient planning in the short and medium term. But to ensure that budgets continue to be used effectively in the future, the planning process needs to take into account changes in technology and techniques that may become available over the longer term. <P> Monitoring innovations that are being made today, so as to anticipate their likely impact in the future is called "horizon scanning", and it?s an ideal application of semantic web technologies: <ul> <li>Tools need to represent information in a playful manner so that users can find previously unknown relationships.</li> <li>A broad range of data sources need to be published, consumed, and integrated?something that is only possible with a combination of Linked Data, RDFa and flexible ontologies.</li> </ul> This session will look at the need for horizon scanning in large organizations, and how semantic web technologies can be used to meet this need. It will draw on the work by the NHS to provide many examples and illustrations, in particular looking at how ontologies, RDFa and Linked Data can provide the glue that binds the semantic toolkit together. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2956 http://purl.org/dc/elements/1.1/title Monitoring Healthcare Innovation: A Case Study in Using OWL, Linked Data and RDFa
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http://data.semanticuniverse.com/resource/semtech-2010-2956 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-birbeck
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http://data.semanticuniverse.com/resource/semtech-2010-2956 http://purl.org/dc/elements/1.1/abstract To allocate resources efficiently the UK's health service must monitor and take into account factors from demographics to new technology and practices. Here we look at how OWL, Linked Data and RDFa have been used together to help the NHS to monitor healthcare innovation.
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http://data.semanticuniverse.com/resource/semtech-2010-3188 http://purl.org/dc/elements/1.1/title Semantics in the Cloud
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http://data.semanticuniverse.com/resource/semtech-2010-3188 http://purl.org/dc/elements/1.1/description <h4>PART I | Cloud- and Cluster-Computing Technologies for the Semantic Web</h4> <P> Kurt Rohloff, Scientist, BBN Technologies <P> Many popular SemWeb technologies are deployed on a single (or a small number of) machine(s) at a time. This is fine when the data processed is small, but this creates horrible processing/coordination bottlenecks for web-scale data problems. The underserved need for distributed computing technologies and the recent development of web-scale distributed computing technologies (such MapReduce implemented in Hadoop) has drive the development of cloud- and cluster-based SemWeb technologies to serve the fundamentally www-scale SemWeb vision. I propose to organize either a panel discussion or a talk that will survey the state-of-the-art in cloud- and cluster-based computing technologies applicable to highly scalable SemWeb information processing. This overview will include a survey of the relevant highly-scalable SemWeb projects such as larKC and Sindice, discussions of the underlying distributed computing technologies that enable these projects and consideration of other cloud- and cluster-based computing technologies that could be used for further advancement. <P> <hr width="10%" /> <P> <h4>PART II | Leveraging Semantic Technologies for Cloud and Grid Data Center Automation</h4> <P> Geoff Brown, CEO, m2mi Corp. <P> This technical presentation explores and elaborates on how semantic technology has been successfully leveraged to help resolve infrastructure issues related to Rich Internet Application delivery for Grid and Cloud based deployments. Key issues such as automated configuration, security and infrastructure orchestration are explored and resolved. The presentation uses a series of use-cases to compare and contrast how early success has been secured and obstacles overcome. <P> The presentation favors a gradual migration to Grid and Cloud based systems rather than a big bang approach. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2970 http://purl.org/dc/elements/1.1/description "Semantic Search" is a buzzword that has generated a lot of interest, but can we quantify exactly how it impacts search? Looking at the entire "search ecosystem," we will show how open standards, such as the upcoming RDB2RDF standard on exporting data from relational database to Linked Data, and work on microformats, GRDDL, and RDFa can expose data previously hidden on the "Deep Web". <P> Using real-world examples from the query log of a major search engine, we will demonstrate how evaluation techniques pioneered in information retrieval can be applied to semantic search, ranging from the classic "Cranfield paradigm" of precision and recall to complex entity-centric techniques. Also, we will end on market-based measures based on profitability via direct sales and ad revenue. Lastly, we will consider barriers preventing further profitability in the semantic search market, ranging from incompatible vocabularies for data producers to lack of standardized javascript APIs for developers. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2970 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-2970 http://purl.org/dc/elements/1.1/title Evaluating and Evolving Semantic Search: From the Deep Web to User Impact
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http://data.semanticuniverse.com/resource/semtech-2010-2970 http://purl.org/dc/elements/1.1/abstract We overview methods for evaluation of semantic search using real-world examples, taking into account profitability and the entire ecosystem necessary to expose the Deep Web to the Semantic Web.
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http://data.semanticuniverse.com/resource/semtech-2010-2868 http://purl.org/dc/elements/1.1/abstract Description of a freely available high level ontology designed as a basis for domain ontology development.
http://data.semanticuniverse.com/resource/semtech-2010-2868 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2010-2868 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dave-mccomb
http://data.semanticuniverse.com/resource/semtech-2010-2868 http://purl.org/dc/elements/1.1/title Gist: The Minimalist Upper Ontology
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http://data.semanticuniverse.com/resource/semtech-2010-2868 http://purl.org/dc/elements/1.1/description Gist is an open source upper ontology. It consists of fewer than 200 classes and properties, selected on their ability to provide unambiguous building blocks for domain specific ontologies. This presentation will briefly describe the need that gist fills, outline how it is organized and present studies on how gist was used in client projects. At the conclusion of this presentation participants will: Know how to obtain gist, and how to include it in their ontology building or mapping projects Appreciate how basing an ontology on concrete well agreed concepts leads to less ambiguity in derived ontologies Understand the twelve concept families the ontology is organized into Take home an 11 x 17 "placemat" that can be used as an aid in ontology building. <P>
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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/semtech-2010-3170 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-marketing-and-advertising
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://purl.org/dc/elements/1.1/description How do you build a semantic web site, or assess the semantic-friendliness of your current site and make it more semantically-rich? How can you use analytical tools to assess search engine and web site performance? How do you enrich content and meta content? What is RDFa, and how can you use it to improve web performance? How do you shift from standard content publishing into semantic publishing? This panel will explore the best practices in implementing SEO, RDFa and enriched content technologies to create and maintain Web 3.0 sites. <P> Real-world examples will explain how this technology was applied to commercial and government sites, including why semantic technology was added, what technology was used, the how-to of implementation, the technical and organizational difficulties encountered, and the benefits. Find out tactical steps for web property owners to transform current content into semantically-rich and maintainable web pages. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2010
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-24T11:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://purl.org/dc/elements/1.1/title Building Web 3.0 Web Sites
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T10:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-windholtz
http://data.semanticuniverse.com/resource/semtech-2010-3170 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-birbeck
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http://data.semanticuniverse.com/resource/semtech-2010-3170 http://www.w3.org/2000/01/rdf-schema#label Building Web 3.0 Web Sites
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http://data.semanticuniverse.com/resource/semtech-2010-3345 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-ontology-design-and-engineering
http://data.semanticuniverse.com/resource/semtech-2010-3345 http://purl.org/dc/elements/1.1/title History and Genealogy Semantics
http://data.semanticuniverse.com/resource/semtech-2010-3345 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-2010-3345 http://purl.org/dc/elements/1.1/description This discussion will be about developing best practices and identify existing or new ontologies for historical and genealogical linked data. This would be a great opportunity to work on some examples as a team, to identify or create vocabularies, and develop best practices. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3345 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2010
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http://data.semanticuniverse.com/resource/semtech-2010-3345 http://purl.org/dc/elements/1.1/audience Technical
http://data.semanticuniverse.com/resource/semtech-2010-3345 http://www.w3.org/2000/01/rdf-schema#label History and Genealogy Semantics
http://data.semanticuniverse.com/resource/semtech-2010-3345 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2010-3345 http://purl.org/dc/elements/1.1/abstract Developing best practices and identify existing or new ontologies for historical and genealogical linked data.
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http://data.semanticuniverse.com/resource/david-s-newman http://www.w3.org/2001/vcard-rdf/3.0#title Strategic Planning Manager Enterprise Architecture
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http://data.semanticuniverse.com/resource/semtech-2010-3068 http://purl.org/dc/elements/1.1/abstract This presentation will detail how existing ontologies such as FOAF, SIOC and CommonTag have been put together and extended in an Enterprise 2.0 scenario for interlinking people, communities and their data.
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http://data.semanticuniverse.com/resource/semtech-2010-3068 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-2010-3068 http://purl.org/dc/elements/1.1/title Selecting and Extending Popular Lightweight Ontologies for Enterprise 2.0 Use
http://data.semanticuniverse.com/resource/semtech-2010-3068 http://purl.org/dc/elements/1.1/description With the recents trends around the Social Semantic Web, (i.e., an overall synergy between the Social Web and the Semantic Web), various lightweight ontologies such as FOAF, SIOC, or CommonTag are now available on the Web. While mainly used on the Web, these models can also be efficiently used in enterprise environments to represent social information from blogs, wikis, and other Enterprise 2.0 services. However, there is still a lack of understanding about how these models can be used for such purposes. In addition, they do not completely cover some basic needs and thus needs to be extended to fully exploit their potential for data integration and management. <P> In this session, attendees will learn: <ul> <li>Which suitable ontologies are available on the Web to represent information about people, communities and tags</li> <li>How these ontologies could be used in enterprise settings</li> <li>What are their limits and how they could be extended</li> <li>How the extended and integrated model can be used to represent people, communities and their data in Enterprise 2.0 settings</li> <li>How to query data based on these models</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2850 http://purl.org/dc/elements/1.1/abstract Semantic Web standards provide durable references to model components, making possible a unique method for tracking the impact of changes to complex models. We illustrate the application of this method to financial models and controlled vocabularies.
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http://data.semanticuniverse.com/resource/semtech-2010-2850 http://purl.org/dc/elements/1.1/title Change Impact Analysis: A Semantic Model-driven Approach
http://data.semanticuniverse.com/resource/semtech-2010-2850 http://purl.org/dc/elements/1.1/description The importance of agile information sharing is becoming a critical, competitive business driver. More organizations view core business information models as important corporate assets to be actively managed. For a complex model, the impact of a proposed change can be subtle and far-reaching. Change to one part of the model could amplify or undermine the effect of a change to another part. A key issue in model management is the ability to determine when and how a proposed change to a model interacts with changes made by others. <P> We developed a method based on the Semantic Web representation of a model that enables a system to automatically detect when one model modification can potentially impact another. This capability is part of a flexible, semantic model-driven approach to data integration and a wide variety of applications/solutions. It can be used pro-actively for analyzing proposed changes, or retro-actively, to detect possible conflicts in committed modifications. <P> We will illustrate the method in two areas: financial instrument models and SKOS vocabularies. <P> This presentation will also address the following topics: <ul> <li>Recording rationale for changes</li> <li>Models and Collaboration</li> <li>Predicting impact</li> <li>Preventing conflict</li> <li>Impact analysis, RDF, and Social Networking</li> <li>Using models rather than code for orchestrating change management</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3082 http://purl.org/dc/elements/1.1/description David Siegel is the first author to articulate the capabilities and potential of the Semantic Web for business people. And he has a message for business people and developers alike: Customers want to pull information, products, and services to them. They want to be much more in control than they are today. When companies start collaborating, customers win. That collaboration is what will bring the semantics onto the web, rather than in semantic silos that have no leverage. If we're going to accelerate the semantic web, we'll need to make it more useful to more people, and that opportunity is here, now, in the shift from pushing to pulling. By looking at the business landscape from a pull perspective, we will show how everyone can win. Don't miss this action-packed session full of examples and new videos based on David's book, "Pull". <P>
http://data.semanticuniverse.com/resource/semtech-2010-3082 http://swrc.ontoware.org/ontology#keywords business
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http://data.semanticuniverse.com/resource/semtech-2010-3082 http://purl.org/dc/elements/1.1/title Pull: The Business Shift Behind the Semantic Web
http://data.semanticuniverse.com/resource/semtech-2010-3082 http://www.w3.org/2000/01/rdf-schema#label Pull: The Business Shift Behind the Semantic Web
http://data.semanticuniverse.com/resource/semtech-2010-3082 http://purl.org/dc/elements/1.1/abstract David Siegel is the first author to articulate the capabilities and potential of the Semantic Web for business people.
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http://data.semanticuniverse.com/resource/semtech-2010-2748 http://swrc.ontoware.org/ontology#keywords tutorial
http://data.semanticuniverse.com/resource/semtech-2010-2748 http://www.w3.org/2000/01/rdf-schema#label Rapid Prototyping with the Jena Command Line Utilities
http://data.semanticuniverse.com/resource/semtech-2010-2748 http://swrc.ontoware.org/ontology#keywords rdf
http://data.semanticuniverse.com/resource/semtech-2010-2748 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-wallace
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http://data.semanticuniverse.com/resource/semtech-2010-2748 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. 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: <P> Transforming RDF files between various formats (RDF/XML, Turtle/N3, N-Triples) Merging multiple RDF files Issuing SPARQL queries against RDF Files Filtering triples <P>
http://data.semanticuniverse.com/resource/semtech-2010-2748 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2010-2748 http://purl.org/dc/elements/1.1/title Rapid Prototyping with the Jena Command Line Utilities
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http://data.semanticuniverse.com/resource/semtech-2010-2748 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.
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http://data.semanticuniverse.com/resource/semtech-2010-3050 http://purl.org/dc/elements/1.1/abstract Publishing data which is syntactically, semantically, pragmatically correct and adheres to best practices is key to getting return out of investments for joining the Web of Data. I will present the comprehensive free tools now available and how to use them.
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http://data.semanticuniverse.com/resource/semtech-2010-3050 http://purl.org/dc/elements/1.1/title Comprehensive Validation: Pragmatically Join the "Web of Data," the Easy and Supported Way
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http://data.semanticuniverse.com/resource/semtech-2010-3050 http://swrc.ontoware.org/ontology#keywords validation
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http://data.semanticuniverse.com/resource/semtech-2010-3050 http://purl.org/dc/elements/1.1/description As Google, Yahoo!, and others have already started supporting data embedded in Web Pages (rich snippets and more), publishing data which is syntactically, semantically, pragmatically correct, and adheres to best practices, is key. <P> In this session, we will introduce a comprehensive Web of Data validator service, which automatically and sequentially looks after many aspects of Web data publishing, guiding webmasters and developers alike. <P> The following aspects will be discussed: <ul> <li>Full syntactic compliance, RDFa, HTML5, Linked Data, Microformats and more; what to use and when and how to make sure</li> <li>Content visualization and debugging with modern tools</li> <li>Pragmatic web ontology reasoning - mind and see what you "mean" when you use an RDF(a) property</li> <li>Pedantic validation, spot and avoid incorrect use of properties and datatypes</li> <li>Domain specific validation - eCommerce RDFa data validation and more</li> <li>Toward entity level validation - how well does your data "automatically link" with the rest of the web?</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2794 http://swrc.ontoware.org/ontology#keywords enterprise-projects
http://data.semanticuniverse.com/resource/semtech-2010-2794 http://swrc.ontoware.org/ontology#keywords natural-language-processing
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http://data.semanticuniverse.com/resource/semtech-2010-2794 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-23T10:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-2794 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-2010-2794 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2010-2794 http://purl.org/dc/elements/1.1/description Solving business problems in an enterprise with Semantic Technologies requires significant collaboration across purpose-built software architectures, including NLP, machine learning, AI, sentiment analysis, ontologies, and additional components. However, none of these technologies can move forward alone. By using these technologies together, semantics-based applications will be able to improve performance over existing technologies. <P> This presentation addresses enterprise use cases in business intelligence, reporting, system integration, and knowledge management to show how combinations of these technologies can work in conjunction to gain a foothold in enterprise data analysis and assessment. Practical recommendations will be shared in an open dialogue. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2794 http://swrc.ontoware.org/ontology#keywords pragmatic-experience
http://data.semanticuniverse.com/resource/semtech-2010-2794 http://swrc.ontoware.org/ontology#keywords ontology
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http://data.semanticuniverse.com/resource/semtech-2010-2794 http://purl.org/dc/elements/1.1/abstract Organizations exploring semantic technologies weigh the pros and cons of machine-based techniques and ontological-based techniques. In this presentation we will emphasize the need to adopt a hybrid approach, and make recommendations as to the places these capabilities have the biggest return on investment.
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http://data.semanticuniverse.com/resource/semtech-2010-2794 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/gary-carlson
http://data.semanticuniverse.com/resource/semtech-2010-2794 http://www.w3.org/2000/01/rdf-schema#label Components of a Semantic Enterprise
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http://data.semanticuniverse.com/resource/semtech-2010-2794 http://purl.org/dc/elements/1.1/title Components of a Semantic Enterprise
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http://data.semanticuniverse.com/resource/semtech-2010-2794 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/christine-jm-connors
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http://data.semanticuniverse.com/resource/semtech-2010-3271 http://purl.org/dc/elements/1.1/abstract The authors will present their current work and discuss the benefits of complementary approaches for Life Sciences.
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http://data.semanticuniverse.com/resource/semtech-2010-3271 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/m-scott-marshall
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http://data.semanticuniverse.com/resource/semtech-2010-3271 http://www.w3.org/2000/01/rdf-schema#label Applications of Biomedical Ontologies and Resources
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http://data.semanticuniverse.com/resource/semtech-2010-3271 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jeffrey-grethe
http://data.semanticuniverse.com/resource/semtech-2010-3271 http://purl.org/dc/elements/1.1/title Applications of Biomedical Ontologies and Resources
http://data.semanticuniverse.com/resource/semtech-2010-3271 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/mark-musen
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http://data.semanticuniverse.com/resource/semtech-2010-3271 http://purl.org/dc/elements/1.1/description As steadily more structured vocabularies and ontologies are made available on the Web, attention is turning towards how to share and annotate data using these vocabularies. Meanwhile, the work on creating and extending ontologies continues, now with the new possibilities provided by OWL 2. Two complementary approaches are being applied: the former enhances the use of identifiers to link data and interoperates at the level of RDF, the latter stresses the benefit of OWL 2 ontologies and formal semantics in order to interoperate at a semantic and reasoning level. The authors will present the current state of work and discuss the benefits of these complementary approaches for Life Sciences. <P> <ol> <li>A new era of collaborative research is becoming possible, enabled by steadily increasing numbers of inter-linked resources. In order for these resources to add value to each other through 'linking', a sustainable and common system of shared identifiers, vocabularies, and data provenance practice is required. The W3C Health Care and Life Sciences Interest Group promotes the use of such identifiers and best practices by creating a translational medicine ontology and bridging the data of multiple disciplines in demonstrations of data federation across the enterprise. <P> <li>Moving life sciences ontologies to OWL 2 provides several advantages: interoperability, semantics, reasoning services. Interoperability is important for shared use across different domains. Once converted to OWL 2, ontologies become easier to be connected and combined with other ontologies. Semantics (meaning) of terms is formally specified thanks to the underlying logics, thus preventing possible errors of annotation. Another major practical benefit of converting biomedical ontologies to OWL 2 is that it makes ontologies amenable to the multitude of existing OWL tools and services, in particular powerful reasoners. Reference ontologies for Disease(SNOMED), Anatomy (FMA), the Gene Ontology and other OBO ontologies, which constitute the backbone of semantic applications in Life Sciences, are already available in OWL 2. </ol> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2983 http://purl.org/dc/elements/1.1/title Meaningful Use of Electronic Medical Records through Semantic Technologies: The Cleveland Clinic Experience
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http://data.semanticuniverse.com/resource/semtech-2010-2983 http://purl.org/dc/elements/1.1/abstract Practical issues and challenges faced by Cleveland Clinic's long term project to apply semantic technologies to the meaningful use of electronic medical records.
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http://data.semanticuniverse.com/resource/semtech-2010-2983 http://purl.org/dc/elements/1.1/description Medical records come in many forms, including enterprise-wide electronic health records mandated by the 2009 federal stimulus package; lab and clinic-based data management systems; administrative databases for scheduling, billing and inventory control; and secondary databases for clinical research and quality reporting. Making meaningful use of these disparate data sources to improve the cost and quality of patient care turns on our ability to accurately model their complex semantics and exploit these semantics through machine processing. <P> Since 2003, Cleveland Clinic has applied semantic technologies to making use of diverse data derived from the treatment of over 200,000 patients with cardiovascular disease over the past 30 years. <P> This presentation outlines the practical issues and challenges faced, and describes how some of these issues have been overcome while others remain unsolved. <P> Topics covered include: <ul> <li>Domain ontology development and utilization</li> <li>Linking domain ontologies to specific instance data models</li> <li>Data definition, validation and aggregation</li> <li>Data utilization for health care quality analysis and reporting</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3169 http://purl.org/dc/elements/1.1/description Improved user experience, brand protection, increased monetization ? semantic targeting is changing the world of online advertising. How can you reach niches within your market, prevent ads from being served on negative or inappropriate content pages, and make the most of your ad inventory? This panel will explain how to use semantics to match on concepts, not just keywords, and substantially improve your results. <P> But semantics is not just about better ways to match ads to content. It?s also about avoiding consumer distractions and brand degradation. It?s about reaching new consumer niches. It?s about reducing regulatory exposure by providing alternatives for consumer privacy and cookie-less browsing. And it?s about improving the consumer experience with contextual search and navigation. Find out how major ad networks, brands, and publishers are using semantics to accomplish all of these objectives. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3183 http://purl.org/dc/elements/1.1/description <h4>PART I | Thought Networking: Building the Semantic Web with Consumer-directed Semantic Networking</h4> <P> Peter Sweeney, Founder & Co-President, Primal<br> Anne Hunt, VP Development, Primal <P> Much of the effort in semantic representation has focused on annotating content. Discussions have centered on whether to use a folksonomy or an expert-created shared ontology. The folksonomy route produces only semi-structured data and the expert route can't keep pace with the rate of new information generated on the Web. We need alternative strategies that harness the power of many non-technical contributors while providing individualized solutions. <P> In this session, we'll present thought networking as a consumer-directed approach that leverages consumers in a novel way. Under this framework, semantic networks are constructed in real time, based directly on consumer interactions. As software agents interact with the semantic data and the Web, formerly unstructured sources are annotated with the semantics that are provided by consumers. In this way, consumer-directed semantic networking can provide a wealth of knowledge models and semantically annotated content to build the Semantic Web. <P> This presentation will address the following topics: <ul> <li>Reviews some of the challenges with content-directed semantic representation</li> <li>Introduces thought networking as a complementary, consumer-directed approach</li> <li>Discusses the technical feasibility of consumer-directed approaches, using real consumer-created networks and data from our consumer applications</li> <li>Presents the benefits and trade-offs of consumer-directed approaches</li> <li>Demonstrates real-world applications of thought networking as a consumer-directed approach</li> </ul> <P> <hr width="10%" /> <P> <h4>PART II | Crowd-Sourcing Ontologies/Taxonomies: Are the Results Better?</h4> <P> William Mougayar, Founder & CEO, Eqentia <P> Does crowd-sourcing the evolution and development of taxonomies and ontologies lead to improved results? This panel will discuss the practical experiences and various methods used. Is there a role for crowd-sourcing taxonomies and ontologies? This session will answer that question and include the following points of interest: <ul> <li>Benefits of crowd-sourcing via social media methods</li> <li>Limitations</li> <li>Integration of results into other apps</li> <li>Practical examples</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2817 http://purl.org/dc/elements/1.1/description Future software applications should become a more dynamic medium, e.g. for information dissemination, attention allocation, and automated reactions across all parts of the enterprise. Complex Event Processing (CEP) is an emerging enabling technology to apply actionable, context-aware knowledge from and against large amounts of event data in near real-time. <P> Building on Action/Event/Process Ontologies -- e.g., OWL-S, WSMO, SWSL, and PSL for Semantic Web Services -- there is now the prospect of combining event processing and semantic technologies into an area we term Semantic Complex Event Processing (SCEP). SCEP-enabled event processing engines will have (1) a description of what is happening in terms of events and event patterns based on situations and process states, as well as (2) a higher-level plan for the (re)actions and activities they can invoke, which can lead to (monitored) follow-up events. <P> Current research includes rule-based Event Processing Languages (EPLs) for the Web such as Reaction RuleML which employ reaction rules that have evolved from existing rule-based technologies such as Production Rules and Event-Condition-Action (ECA) rules. They use SCEP-generated facts and knowledge to derive further decisions and trigger automated reactions. Moreover, such EPLs can exploit the declarative expressive power of semantic rules as a means to specify knowledge in a way that is understood by 'the business' and is executable by CEP rule engines. <P> Existing practices and commercial applications already move toward semantically improved event processing to provide smarter business processes, and some TIBCO Software use cases will be discussed. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2817 http://purl.org/dc/elements/1.1/title Semantic Complex Event Processing - The Future of Dynamic IT
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http://data.semanticuniverse.com/resource/semtech-2010-2817 http://www.w3.org/2000/01/rdf-schema#label Semantic Complex Event Processing - The Future of Dynamic IT
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http://data.semanticuniverse.com/resource/semtech-2010-2817 http://purl.org/dc/elements/1.1/abstract Introduction to the concepts of semantic complex events, continuous event processing, and how these relate to "knowledge based systems".
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http://data.semanticuniverse.com/resource/semtech-2010-2863 http://purl.org/dc/elements/1.1/title Developing An Information Delivery Web Business Model
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http://data.semanticuniverse.com/resource/semtech-2010-2863 http://purl.org/dc/elements/1.1/abstract The Knowledge Dynasty proposes to be a search engine with a difference - a Research Engine.
http://data.semanticuniverse.com/resource/semtech-2010-2863 http://purl.org/dc/elements/1.1/description On the knowledgedynasty.info site, the visitor will be able to: <P> Interact with animated talking agents Receive tailored responses to queries (by e-mail) Receive submissions from individuals rather than from websites* Access a growing database of answers to previously asked questions Chat with animated agents in real time on almost any topic (eventual ability to handle voice communication) <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2831 http://www.w3.org/2000/01/rdf-schema#label Information Made Accountable: The Data Projection Model
http://data.semanticuniverse.com/resource/semtech-2010-2831 http://purl.org/dc/elements/1.1/title Information Made Accountable: The Data Projection Model
http://data.semanticuniverse.com/resource/semtech-2010-2831 http://purl.org/dc/elements/1.1/description As information systems become more sophisticated, there is a growing need to account for the origin of any information item, and how and why any of them is connected to others. This paper presents an approach, the Data Projection Model, based on semantic technologies that draw a parallel between accounting techniques and information management. The Data Projection Model can be seen as "double entry bookkeeping" applied to information management. Transactions (aka "binary relations", or RDF triples) are considered the foundation of the system. The "Data Projection Model" on which this approach is based has been implemented and is used within a semantic application deployed at the Internal Revenue Service. This presentation will present the model, its main application so far, and describe its relation with existing Semantic Web specifications, more specifically RDF and Topic Maps, and will show the wide range of applications to be built with it. <P> This presentation will address the following topics: <ul> <li>Information Management Made Accountable</li> <li>The core of RDF used as a microscope to any information system</li> <li>Description of Tax Map auditing for the IRS</li> <li>The relation between RDF and Topic Maps, revisited</li> <li>A plan for the future</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2831 http://purl.org/dc/elements/1.1/abstract The Data Projection Model is an application of RDF which bridges accounting techniques with information management. It operates as a semantic microscope that makes information accountable.
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http://data.semanticuniverse.com/resource/semtech-2010-3017 http://purl.org/dc/elements/1.1/description Semantic technologies are now actively being developed and deployed in a range of application settings: banking, e-commerce, search, web services, data integration and across a variety of e-science applications. As semantics are beginning to overcome the previous significant levels of semantic heterogeneity, large-scale data, complex data types, legacy systems, inflexible and unsustainable implementation technology, new requirements have emerged that fall under the broad category of provenance. Over the last few years, knowledge provenance, as an enabler for semantic web applications has matured and been applied in several application domains. Additionally a new incubator group has formed at W3C on provenance. We will motivate the growing need for knowledge provenance through a few project examples and describe knowledge provenance in action. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3017 http://purl.org/dc/elements/1.1/title Knowledge Provenance
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http://data.semanticuniverse.com/resource/semtech-2010-3017 http://purl.org/dc/elements/1.1/abstract Introduce the growing need for provenance through real world examples and show how semantic technologies can be enhanced through provenance-rich environments and applications.
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http://data.semanticuniverse.com/resource/semtech-2010-3238 http://purl.org/dc/elements/1.1/abstract This presentation will explore strategies and challenges in managing structured data inside a massively collaborative, multilingual community; specifically, smarter ways to manage templates inside Wikipedia, which could potentially be a foundation for further improvements to structured data in Wikipedia.
http://data.semanticuniverse.com/resource/semtech-2010-3238 http://swrc.ontoware.org/ontology#keywords wikipedia
http://data.semanticuniverse.com/resource/semtech-2010-3238 http://swrc.ontoware.org/ontology#keywords structured-data
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http://data.semanticuniverse.com/resource/semtech-2010-3238 http://purl.org/dc/elements/1.1/description Wikipedia contains more than 15 million articles in 265 languages. These articles are flat text. Structured data is presented in standardized layouts using community-developed templates. The use of templates offers a potential path to extract structure from the article source text, and indeed, projects like DBPedia have done so. Other projects, like Semantic MediaWiki, aim to enrich wiki syntax and the template system with relation types, backend storage, queries, and data export functionality. <P> The Wikimedia Foundation, which operates Wikipedia, is not blind to the potential of these technologies. Due to limited resources, we are focusing our attention on the most pressing user experience issues first. However, we have begun exploring smarter ways to manage templates inside Wikipedia, which could potentially be a foundation for further improvements to structured data in Wikipedia. In this presentation, we will discuss our thinking to-date, as well as some of the longer term challenges in managing structured data inside a massively collaborative, multilingual community. As an open source project, we will appeal to SemTech attendees to help us address these challenges. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3238 http://purl.org/dc/elements/1.1/title Wikipedia's Structured Data Challenge
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http://data.semanticuniverse.com/resource/semtech-2010-3284 http://purl.org/dc/elements/1.1/title Semantics for Situational and Contextual Awareness
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http://data.semanticuniverse.com/resource/semtech-2010-3284 http://purl.org/dc/elements/1.1/description <h4>PART I | A Clustering Environment for Situational Awareness, Data Understanding & Fusion</h4> <P> <i>Mala Mehrotra, President, Pragati</i> <P> Expozé-Aware is being developed under an AF SBIR project, as an extension of Pragati?s Expozé tool, to address identification of actionable intelligence for space situation awareness. It uses clustering technology to condense large amounts of data into understandable pieces of information chunks that can lead to enhanced understanding of potential threats in a hostile environment. Our visualization front-end aids the user in making contextual associations among disparate information pieces. <P> <hr width="10%" /> <P> <h4>PART II | Contextual Query Answering</h4> <P> <i>David Kolas, Scientist, BBN Technologies</i> <P> By encoding meaning in a structured way that a computer can understand, Semantic Web technology helps close the gap between questions that a user wants to ask and questions that a computer can answer. To close this gap further, we must account for the significant amount of assumed context inherent in a user's question through the use of terms such as near, far, and high-value. We accomplish this by including qualitative context-dependent terms into our ontology, and using Semantic Web rules to resolve the terms for a given user's context. In this manner, two users can ask the same question: ?What threats are near my intended route?? and each receives an answer tailored to their specific context. Our presentation will explain this process from beginning to end. We will also demonstrate a context-sensitive, query-answering system in the domain of Marine Corps raid missions. <P> Additional topics include the following: <ul> <li>Resolving context dynamically means users can leverage the same data in many different ways, including for purposes beyond the scope of the original data source</li> <li>Encoding of context enables users to ask questions more naturally</li> <li>Qualitative terms are added as structured classes and predicates in the ontology</li> <li>Context rules are encoded as SWRL</li> <li>Integration of geospatial context</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-3284 http://purl.org/dc/elements/1.1/abstract Part I: This presentation is about building human machine collaboration tools which reduce the information overload to the user while exposing valuable actionable intelligence information in a way that not only speeds up his/her decision making skills but also boosts the quality of their decision making.
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http://data.semanticuniverse.com/resource/semtech-2010-3031 http://www.w3.org/2000/01/rdf-schema#label Natural Language Processing and Semantic Models in an Imperfect World
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http://data.semanticuniverse.com/resource/semtech-2010-3031 http://purl.org/dc/elements/1.1/abstract For the semantic web to take advantage of text, it must be processed to extract structured knowledge through Natural Language Processing (NLP). However, NLP is imperfect and produces data with errors. This presentation will explore techniques to use semantic technology that can tolerate imperfect data.
http://data.semanticuniverse.com/resource/semtech-2010-3031 http://purl.org/dc/elements/1.1/title Natural Language Processing and Semantic Models in an Imperfect World
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http://data.semanticuniverse.com/resource/semtech-2010-3031 http://purl.org/dc/elements/1.1/description Much of the world?s information is stored as text. For the semantic web to take advantage of this information, the text must be processed to extract structured knowledge through Natural Language Processing (text-mining). Text is called ?unstructured data? but in reality it is ?complex data? because it is difficult to represent in a simple structured form. Rich ontologies are needed to represent this knowledge. <P> Although text-mining can be highly accurate, for the foreseeable future there will continue to be error in the output. This error must be taken into account when using data generated from NLP, and semantic applications must tolerate imperfect data. Current semantic techniques generally assume the data is perfect, and can grind to a halt when imperfect data is present. <P> In this session, we will explore techniques to utilize NLP data in semantic applications, with a demonstrated example of NLP applied to Life Science research. <P> This session will present the following: <ul> <li>A hybrid NLP system combining machine learning and rule-based approaches to extract assertions from text into RDF.</li> <li>A general knowledge representation ontology. Extracted assertions from NLP conform to this ontology.</li> <li>A domain specific (Life Science) knowledge ontology, leveraging the general model to include domain specific rules.</li> <li>Algorithms to asses the ?certainty? of an assertion from NLP.</li> <li>Algorithms to determine the relevancy of knowledge to a query.</li> <li>Techniques to utilize the knowledge model containing imperfect data.</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3252 http://purl.org/dc/elements/1.1/title Enterprise Semantic Data Integration
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http://data.semanticuniverse.com/resource/semtech-2010-3252 http://purl.org/dc/elements/1.1/description <h4>PART I | Semantic Models in Enterprise Data Integration</h4> <P> <i>Fran Clark, President, Arpeggio Technology</i> <P> Enterprise data integration continues to be the most significant challenge facing most large IT organizations. Over the years, various tools and techniques have been used with limited success. While individual projects have made positive strides, overall increases in business agility and developer efficiency have not been realized. <P> Semantic modeling approaches and technologies can improve the enterprise data integration process. They must, however, be augmented to be truly effective. <P> In this presentation, you will learn how to: <ul> <li>Design enterprise data service interfaces using an enterprise semantic model</li> <li>Create an exchange model to represent transformations required amongst transactional systems</li> <li>Tools and techniques that can be used to augment and leverage semantic modeling</li> </ul> <P> This presentation will also include a case study and demonstration of how these techniques were successfully applied at a leading financial services company. <P> <hr width="10%" /> <P> <h4>PART II | Enterprise Information Integration and Semantic Technologies at the World Bank</h4> <P> <i>Denisa Popescu, Information Architect, World Bank Group, Enterprise Architecture</i> <P> The first part of this presentation will cover an overview of the Enterprise Information Architecture for integration of information across the Banks' multiple repositories. I will briefly describe the unified information and functional architecture for both structured and unstructured information and its core tenets, as well as lessons learned: <ul> <li>Metadata Repository</li> <li>Master Data Authoritative Source</li> <li>Core Metadata Standard</li> <li>Automatic Metadata Capture</li> <li>Data Services</li> <li>Enterprise Search</li> <li>Unified Records Management</li> </ul> The last part of the presentation will focus on providing specific examples of the Bank's implementation of automatic metadata capture using semantic technologies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3252 http://purl.org/dc/elements/1.1/abstract Part I: Learn how to leverage semantic and other modeling techniques to enable enterprise data integration. Part II: Present the architecture of how the World Bank deals with integration of structured and unstructured information residing in disparate sources.
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http://data.semanticuniverse.com/resource/semtech-2010-2918 http://purl.org/dc/elements/1.1/title The Ten Myths of the Semantic Web Debunked (and how they hurt your success)
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http://data.semanticuniverse.com/resource/semtech-2010-2918 http://purl.org/dc/elements/1.1/description The excitement of the Semantic Web quickly creates myths. These undermine its potential and impede its progress across the corporate enterprise and the Internet. Our hands-on experience sees the falsehoods and damage that these myths harbor. We list the key myths and debunk them with a perspective earned in building Semantic Web solutions in multiple domains. This gives you the information you need to make an objective, informed decision with the support you need as to how to go forward with the Semantic Web. <P> Myths impact key areas that delay or eliminate semantic solutions leading to negative impacts for your bottom line and your competitiveness. The myths range from the specious need to develop the ultimate ontology to the false assumption that keywords and Google is all you need. <P> We use lots of examples to disprove the myths and give you an honest decision framework to properly position your semantic use. <P> This presentation will: <ul> <li>Identify the key myths and the damage they produce</li> <li>Refute the myths with working examples and case studies</li> <li>Develop a decision framework that properly considers the role of semantics</li> <li>Develop a risk-mitigated plan to move into the semantic age</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2918 http://purl.org/dc/elements/1.1/abstract Myths impede progress ? and Semantic Web is full of them. We debunk the critical 10 myths with clear evidence from our own research and hands-on development.
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http://data.semanticuniverse.com/resource/karthik-gomadam http://www.w3.org/2001/vcard-rdf/3.0#org Department of Electrical Engineering, University of Southern California
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http://data.semanticuniverse.com/resource/semtech-2010-2932 http://purl.org/dc/elements/1.1/title Visual Analysis of the Web of Linked Data: The S*QL Plugin for Cytoscape
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http://data.semanticuniverse.com/resource/semtech-2010-2932 http://purl.org/dc/elements/1.1/abstract We have developed a plug-in that works with Cytoscape to access and visualize RDF by coupling a SPARQL query framework with a high performance visualization and analytics engine.
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http://data.semanticuniverse.com/resource/semtech-2010-2932 http://purl.org/dc/elements/1.1/description Many applications have been created that interact with RDF: some query RDF via SPARQL endpoints, while others help visualize RDF data. Yet coupling both functions is essential in order to support interactive analytics on RDF content. Furthermore, RDF technologies should attempt to work with existing software that has a large community base. An example of this in the life sciences is the open-source Cytoscape application, which has a strong following and allows scientists to view and analyze complex gene and protein relations via rich graphs. <P> We describe here the S*QL plug-in technology which extends the Cytoscape architecture to handle RDF querying and visualization by supporting these analytic processes: <ul> <li>Query both SPARQL and RDBM (SQL) endpoints</li> <li>Visualize multiple data sources</li> <li>Propose and examine patterns within a single data space</li> <li>Examine implications of selected patterns across multiple displays, data tables</li> <li>Export selections with descriptive (semantic) meta-data</li> </ul> We apply S*QL to pathway data (BioPax) as well as Clinical Trials data. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3164 http://purl.org/dc/elements/1.1/title The Role of Semantic Technologies in the National Airspace System
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http://data.semanticuniverse.com/resource/semtech-2010-3164 http://purl.org/dc/elements/1.1/abstract This presentation will examine the role of semantic technology in implementing Net-Centric Operations in the National Airspace System.
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http://data.semanticuniverse.com/resource/semtech-2010-3164 http://purl.org/dc/elements/1.1/description In 2003, Congress and the President enacted Vision 100 ? the Century of Aviation Reauthorization Act, thus putting into motion a massive transformation ? known as ?NextGen? - of the National Airspace System (NAS). Net-Centric Operations (NCO), are at the center of the transformation, and will revolutionize the exchange of information in the NAS. Semantic technologies are critical to enabling Net-centric Operations. As the volume of air traffic increases, terrorism remains a constant threat, and criminals continue to use the airways to carry out illegal activities, decision making in the NextGen era will become ever more complex and fast-paced. Almost every significant decision, and its execution, will require cooperation and coordination between multiple, geographically dispersed participants. Information producers must be able to publish the information they have, and authorized consumers must be able to access the information they need, when they need it. Tools to organize, sort, analyze, and display information in user-friendly interfaces will be crucial to ensuring not only that users get all the information they need, but that they get only the information they need. Semantically federated search and mediation services, semantic document management systems, semantically-enhanced decision support tools, and intelligent agents will help NextGen users to discover and sort information, prevent information overload, and support automation of many currently time-consuming, labor intensive processes. <P>
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http://data.semanticuniverse.com/resource/peter-fox http://xmlns.com/foaf/0.1/name Peter Fox
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http://data.semanticuniverse.com/resource/denisa-popescu http://xmlns.com/foaf/0.1/name Denisa Popescu
http://data.semanticuniverse.com/resource/denisa-popescu http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com^^http://www.w3.org/2001/XMLSchema#anyURI
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http://data.semanticuniverse.com/resource/denisa-popescu http://www.w3.org/2001/vcard-rdf/3.0#org World Bank Group, Enterprise Architecture
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http://data.semanticuniverse.com/resource/semtech-2010-2876 http://www.w3.org/2000/01/rdf-schema#label Using SKOS and Semantic Technologies to support smart, sustainable growth in Europe
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http://data.semanticuniverse.com/resource/semtech-2010-2876 http://purl.org/dc/elements/1.1/abstract Europe has multilingual thesauruses and taxonomies to categorize documents of many different types (research papers, law, CV, study, comments, ?). Objective of this presentation is to explain the value, vision and importance of semantic technology for storing, publishing and using these metadata.
http://data.semanticuniverse.com/resource/semtech-2010-2876 http://purl.org/dc/elements/1.1/description Europe has multilingual thesauruses and taxonomies to categorize documents of many different types (research papers, law, CV, study). We will explain the value, vision and importance of semantic technology for storing, publishing and using these metadata, addressing the following topics: <P> Presentation of contents and goal of some important multilingual thesauruses and taxonomies Explanation on how these thesauruses and taxonomies are stored with semantic technology and what the advantages are Proposal for a multi-thesaurus and multi-taxonomy Europe to distribute the effort and investments in this valuable contents TenForce is a supplier of Thesaurus/Taxonomy Management Systems to the European Commission. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2876 http://purl.org/dc/elements/1.1/title Using SKOS and Semantic Technologies to support smart, sustainable growth in Europe
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http://data.semanticuniverse.com/resource/semtech-2010-2876 http://swrc.ontoware.org/ontology#keywords thesaurus
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http://data.semanticuniverse.com/resource/jerry-sheehan http://www.w3.org/2001/vcard-rdf/3.0#org California Institute for Telecommunications and Information Technology
http://data.semanticuniverse.com/resource/semtech-2010-3100 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-2010-3100 http://swrc.ontoware.org/ontology#keywords venture-capital
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http://data.semanticuniverse.com/resource/semtech-2010-3100 http://purl.org/dc/elements/1.1/title Pitch Slam
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http://data.semanticuniverse.com/resource/semtech-2010-3100 http://purl.org/dc/elements/1.1/description Innovate!2010 is a global competition to identify top technology, media and communications startups from around the world, and the Pitch Slam is the mechanism by which these startups join the competition. <P> The Pitch Slam is a fast-paced, 5-minute format designed to quickly tease out a company?s market opportunity, unique differentiation, and execution against plans. Judges evaluate the startups using the Guidewire G/score methodology. <P> A group of semantic semi-finalists will compete at SemTech for a chance to become a finalist in the Innovate!100 (http://www.innovate100.com/). These semi-finalists are: <P> <ul> <li><a href="http://www.semantifi.com" target="_blank">Semantifi</a></li> <li><a href="http://www.playence.com" target="_blank">Playence</a></li> <li><a href="http://www.hypios.com" target="_blank">Hypios</a></li> <li><a href="http://www.salsadev.com" target="_blank">Salsa Dev</a></li> <li><a href="http://www.feeltiptop.com" target="_blank">Tip Top Technologies</a></li> <li><a href="http://www.smartlogic.com" target="_blank">SmartLogic</a></li> <li><a href="http://www.zagile.com" target="_blank">zAgile</a></li> <li><a href="http://www.gnowsis.com" target="_blank">Gnowsis</a></li> <P> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3100 http://swrc.ontoware.org/ontology#keywords entrepreneur
http://data.semanticuniverse.com/resource/semtech-2010-3100 http://purl.org/dc/elements/1.1/abstract The Pitch Slam is a fast-paced, 5-minute format designed to quickly tease out a company?s market opportunity, unique differentiation, and execution against plans. Judges evaluate the startups using the Guidewire G/score methodology.
http://data.semanticuniverse.com/resource/semtech-2010-3100 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/golden-gate-3-4
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http://data.semanticuniverse.com/resource/semtech-2010-2844 http://www.w3.org/2000/01/rdf-schema#label Semantic Technologies to Enable the Knowledge-powered Enterprise: The ACTIVE Approach
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http://data.semanticuniverse.com/resource/semtech-2010-2844 http://purl.org/dc/elements/1.1/abstract The presentation describes the use of semantic technology for: ? better knowledge sharing; ? context-based information delivery; ? improved process management. Also presented is an implementation within a major telco.
http://data.semanticuniverse.com/resource/semtech-2010-2844 http://swrc.ontoware.org/ontology#keywords ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-2844 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2010-2844 http://purl.org/dc/elements/1.1/title Semantic Technologies to Enable the Knowledge-powered Enterprise: The ACTIVE Approach
http://data.semanticuniverse.com/resource/semtech-2010-2844 http://swrc.ontoware.org/ontology#keywords process-optimization
http://data.semanticuniverse.com/resource/semtech-2010-2844 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/john-davies
http://data.semanticuniverse.com/resource/semtech-2010-2844 http://purl.org/dc/elements/1.1/description This presentation will describe the results of the ACTIVE project (www.active-project.eu), using semantic technology to make knowledge-intensive work in organizations more efficient and effective, including a case study (within BT) where ACTIVE technology is being used by technical and sales consultants, in particular to improve the way they respond to customers. We will also demonstrate several tools being developed in the project. <P> Topics include: <ul> <li>Brief overview of the project</li> <li>Utilization of semantic technology within the project</li> <li>What ACTIVE offers</li> <li>Using ACTIVE technology in a real-life scenario</li> </ul> <P>
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http://data.semanticuniverse.com/resource/lars-hard http://xmlns.com/foaf/0.1/name Lars Hard
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http://data.semanticuniverse.com/resource/semtech-2010-3044 http://purl.org/dc/elements/1.1/audience Non-Technical
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http://data.semanticuniverse.com/resource/semtech-2010-3044 http://purl.org/dc/elements/1.1/abstract Semantic systems are based on shared models, but these models are the constructs of real people. This talk examines the formation of semantic communities and how they become sustainably interconnected.
http://data.semanticuniverse.com/resource/semtech-2010-3044 http://swrc.ontoware.org/ontology#keywords community
http://data.semanticuniverse.com/resource/semtech-2010-3044 http://purl.org/dc/elements/1.1/description Semantics develop when a community uses a common vocabulary to describe the things that matter to them. This talk examines how semantic vocabularies develop, how they are used, how they evolve, and what makes a semantic community sustainable. <P> We will dissect both formal and informal communities: from the emergent semantics of Twitter and the powerful, lightweight semantics of Wikipedia to the more formal semantics of Freebase schema. These communities represent a diversity of members, continuous evolution, and a wide spectrum of use. This talk will discuss how these factors contribute to the sustainability of the community and the longevity of their semantic practice. The implications for the growth of other semantic communities and the larger Semantic Web will be discussed. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3044 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jamie-taylor
http://data.semanticuniverse.com/resource/semtech-2010-3044 http://purl.org/dc/elements/1.1/title The Social Fabric of Semantics
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http://data.semanticuniverse.com/resource/semtech-2010-3044 http://www.w3.org/2000/01/rdf-schema#label The Social Fabric of Semantics
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http://data.semanticuniverse.com/resource/todd-schneider http://www.w3.org/2001/vcard-rdf/3.0#title Principal Engineer
http://data.semanticuniverse.com/resource/todd-schneider http://www.w3.org/2001/vcard-rdf/3.0#org Raytheon
http://data.semanticuniverse.com/resource/semtech-2010-3219 http://purl.org/net/biblio#presentedAt http://data.semanticuniverse.com/resource/semtech-2010
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http://data.semanticuniverse.com/resource/semtech-2010-3219 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2010-3219 http://swrc.ontoware.org/ontology#keywords open-graph
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http://data.semanticuniverse.com/resource/semtech-2010-3219 http://www.w3.org/2000/01/rdf-schema#label Facebook's Open Graph
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http://data.semanticuniverse.com/resource/semtech-2010-3219 http://purl.org/dc/elements/1.1/description The Open Graph protocol enables any web page to become a rich object in a social graph. It was created by Facebook but designed to be generally useful to anyone and as simple as copy and paste. This talk will explore the design decisions which went into the Open Graph protocol and ultimately why we chose to use RDFa. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3219 http://purl.org/dc/elements/1.1/abstract This presentation discusses the design principles and objectives of the Open Graph protocol.
http://data.semanticuniverse.com/resource/semtech-2010-3219 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-social-networks-and-collaboration
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http://data.semanticuniverse.com/resource/semtech-2010-3219 http://purl.org/dc/elements/1.1/title Facebook's Open Graph
http://data.semanticuniverse.com/resource/semtech-2010-2788 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2010-2788 http://www.w3.org/2000/01/rdf-schema#label The Research Intelligence Project
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http://data.semanticuniverse.com/resource/semtech-2010-2788 http://purl.org/dc/elements/1.1/abstract Briefly describe and demonstrate the Calit2 Research Intelligence portal for semantically identifying federal funding opportunities and research strengths of UCSD faculty.
http://data.semanticuniverse.com/resource/semtech-2010-2788 http://purl.org/dc/elements/1.1/description The California Institute for Telecommunications and Information Technology (Calit2) has developed the Research Intelligence tool set to help semantically identify federal funding opportunities and research strengths of University of California, San Diego faculty. <P> Relying on various open Semantic APIs (Open Calais, Yahoo Term Extraction, Open Amplify, KEA, and Alchemy) the tools allow for near real-time data mining of new research opportunities. <P> Join us for this session and hear about lessons learned in the two year old project and opportunities for others to join the newly established RI Consortium. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2788 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jerry-sheehan
http://data.semanticuniverse.com/resource/semtech-2010-2788 http://swrc.ontoware.org/ontology#keywords federal-funding
http://data.semanticuniverse.com/resource/semtech-2010-2788 http://purl.org/dc/elements/1.1/title The Research Intelligence Project
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http://data.semanticuniverse.com/resource/jones-dilworth-inc http://www.w3.org/2000/01/rdf-schema#label Jones-Dilworth, Inc.
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http://data.semanticuniverse.com/resource/semtech-2010-3090 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-linked-data
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http://data.semanticuniverse.com/resource/semtech-2010-3090 http://purl.org/dc/elements/1.1/audience Introductory
http://data.semanticuniverse.com/resource/semtech-2010-3090 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-2010-3090 http://www.w3.org/2000/01/rdf-schema#label Linked Enterprise Data
http://data.semanticuniverse.com/resource/semtech-2010-3090 http://purl.org/dc/elements/1.1/title Linked Enterprise Data
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http://data.semanticuniverse.com/resource/semtech-2010-3090 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/bernadette-hyland
http://data.semanticuniverse.com/resource/semtech-2010-3090 http://purl.org/dc/elements/1.1/description Linked Data (or Linked Open Data) is an emerging set of concepts and technologies for combining and integrating data. This tutorial will explain Linked Data principles and technologies, then demonstrate how they work through case studies and real-world examples. Applying the Web's architectural principles (versus using the public Web directly) for enterprise problems, it shows how to effectively address the current and future enterprise information glut. It will also discuss challenges, such as how the use of Web architecture requires enterprises to give up the central control and planning traditionally applied by IT departments. <P>
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http://data.semanticuniverse.com/resource/david-booth http://www.w3.org/2001/vcard-rdf/3.0#title Software Architect
http://data.semanticuniverse.com/resource/david-booth http://www.w3.org/2001/vcard-rdf/3.0#org Cleveland Clinic
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http://data.semanticuniverse.com/resource/semtech-2010-2756 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-2010-2756 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://swrc.ontoware.org/ontology#keywords linked-data
http://data.semanticuniverse.com/resource/semtech-2010-2756 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-2010-2756 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-22T08:30:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-semantic-web
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http://data.semanticuniverse.com/resource/semtech-2010-2756 http://purl.org/dc/elements/1.1/abstract Give an overall introductory tutorial of the basic and standard Semantic Web technologies, ie, RDF, OWL, SKOS, RDFa, etc.
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http://data.semanticuniverse.com/resource/semtech-2010-2756 http://purl.org/dc/elements/1.1/title Introduction to Semantic Web Technologies
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http://data.semanticuniverse.com/resource/semtech-2010-2756 http://purl.org/dc/elements/1.1/description This tutorial gives an overview of the basic Semantic Web Technologies developed at W3C. Using practical examples, the fundamentals of the Resource Description Framework RDF) are presented, followed by an overview of RDF Schemas (a.k.a. RDF Vocabulary Description Language), the standard Query language (SPARQL), the Web Ontology Language (OWL), and RDF in Attributes (RDFa), etc. During the presentation, examples of practical usage coming from industrial or governmental applications are also provided, as well as a brief overview of the current technical issues that the community is working on. <P> Participants are not expected to have a prior knowledge of Semantic Web technologies. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://swrc.ontoware.org/ontology#keywords web-ontology-language
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://swrc.ontoware.org/ontology#keywords resource-description-framework-(rdf)
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://data.semanticweb.org/ns/swc/ontology#hasLocation http://data.semanticuniverse.com/resource/grand-a
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://swrc.ontoware.org/ontology#keywords semantic-web
http://data.semanticuniverse.com/resource/semtech-2010-2756 http://www.w3.org/2000/01/rdf-schema#label Introduction to Semantic Web Technologies
http://data.semanticuniverse.com/resource/semtech-2010-3233 http://purl.org/dc/elements/1.1/abstract The presentation will address the relationship between large scale computing platforms and semantic technology. Specifically addressed are applications and semantic use cases that can be linked to the migration towards Cloud computing.
http://data.semanticuniverse.com/resource/semtech-2010-3233 http://purl.org/dc/elements/1.1/description The presentation will address the relationship between large scale computing platforms and semantic technology. Specifically addressed are applications and semantic use cases that can be linked to the migration towards Cloud computing. Early semantic technology enabled information integration platforms showed the value of properly harvesting rich semantics from unstructured and structured data. However, significant limitations exist associated with our ability to manipulate and exploit the large graphs that can be generated from semantic technology based information platforms. To fully realize Web 3.0 concepts will most likely require the migration towards large scale computing platforms. The session will present: Importance of Ontologies and concepts like Data Efficacy in a Cloud Computing Environment A notional representation between the encoding of logic and the computational resources required to support logic and reasoning Specific use cases for Cloud Computing beyond the Cloud business model (predictive modeling, social graph analysis, etc.) <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3233 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/steve-hamby
http://data.semanticuniverse.com/resource/semtech-2010-3233 http://purl.org/dc/elements/1.1/title Real World Use Cases of Semantic Technology in the Cloud
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http://data.semanticuniverse.com/resource/anthony-defilippo http://www.w3.org/2000/01/rdf-schema#label Anthony DeFilippo
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http://data.semanticuniverse.com/resource/anthony-defilippo http://www.w3.org/2001/vcard-rdf/3.0#org Hypios Inc.
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http://data.semanticuniverse.com/resource/semtech-2010-3201 http://www.w3.org/2000/01/rdf-schema#label Oracle Database Semantic Technologies: Understanding How to Install, Load, Query and Inference
http://data.semanticuniverse.com/resource/semtech-2010-3201 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.
http://data.semanticuniverse.com/resource/semtech-2010-3201 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. 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>
http://data.semanticuniverse.com/resource/semtech-2010-3201 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-semantics-for-enterprise-data
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http://data.semanticuniverse.com/resource/semtech-2010-3201 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-2010-3201 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/vladimir-kolovski
http://data.semanticuniverse.com/resource/semtech-2010-3201 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/matthew-perry
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http://data.semanticuniverse.com/resource/semtech-2010-2945 http://www.w3.org/2000/01/rdf-schema#label The Enterprise Data Management Council Semantics Repository Case Study
http://data.semanticuniverse.com/resource/semtech-2010-2945 http://purl.org/dc/elements/1.1/title The Enterprise Data Management Council Semantics Repository Case Study
http://data.semanticuniverse.com/resource/semtech-2010-2945 http://purl.org/dc/elements/1.1/description This presentation documents a case study of the EDM Council Semantics Repository for the financial services industry. We show how the requirements for the semantics repository were met using the Ontology Definition metamodel (ODM) standard with some adaptations and additions for presentation to business subject matter experts, and summarize the relationship with other standards, both within financial services and more widely. Ongoing "Proof of Concept" activities illustrate how the Semantics Repository can be used to solve real data problems within the securities industry. <P> Topics include: <ul> <li>Aims and requirements of the Semantics Repository</li> <li>Relation to other standards (ISO 20022, FpML, XBRL etc.)</li> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2945 http://purl.org/dc/elements/1.1/abstract This case study describes the development of the EDM Council financial industry semantics repository including modeling framework, ontology extensions, relation to other standards and ongoing proof of concept projects.
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http://data.semanticuniverse.com/resource/semtech-2010-3177 http://purl.org/dc/elements/1.1/description <ul> 6:00: Evening Session Intro and Recap of today<P> 6:15: General Audience Q&A<P> 6:25: Authoring Rules on the Semantic Web: RoadMap by Paul Haley<P> 6:45: Rule Authoring Standards: Introduction to SBVR - Case Studies, Demos<P> 7:15: General Audience Q&A and Discussion<P> 7:30: Open Networking<P> 8:00: Close<BR> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3145 http://www.w3.org/2000/01/rdf-schema#label True Semantic Reasoning: Self-Constructing Ontologies
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http://data.semanticuniverse.com/resource/semtech-2010-3145 http://purl.org/dc/elements/1.1/abstract The fuel of the semantic web is ontologies, used to develop a deep understanding with a standard set of tools to access and manipulate. But do we need to wait until the ontology and schema are standardized?
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http://data.semanticuniverse.com/resource/semtech-2010-3145 http://purl.org/dc/elements/1.1/description The semantic web promises to lend meaning and definition of information and services, making it possible to "understand" and satisfy the requests of people and machines to use content. The fuel of the semantic web is ontologies, leveraged to develop a deep understanding with a standard set of tools to access and manipulate data. <P> But the pervasive linked data and ontologies of the semantic web aren?t here yet and the world is changing. Why wait until the ontologies and schemas exist? <P> This session will explore the topics of spatial tagging, managing multiple identities, and cognitive computation in an effort to define true semantic reasoning without the formal structures leveraged in current approaches to semantic understanding. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2889 http://www.w3.org/2000/01/rdf-schema#label How to Build Linked Data Sites with Drupal 7 and RDFa
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http://data.semanticuniverse.com/resource/semtech-2010-2889 http://purl.org/dc/elements/1.1/abstract Participants will learn how to build fully functional websites in line with the Linked Data standards and with RDFa markup automatically generated on each page.
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http://data.semanticuniverse.com/resource/semtech-2010-2889 http://purl.org/dc/elements/1.1/description Building a semantically enriched site used to be something you had to hire a developer to do for you. But now, with the inclusion of RDF in Drupal core, anyone who understands the basics of the RDF data model can create a Web 3.0 site in a few hours. <P> Drupal is an open source Content Management System currently powering more than 200,000 sites. It is well known for its flexibility and is used to power every kind of site from intranets and community portals to social networking sites to e-commerce applications. Starting with the release of Drupal 7 earlier this year, every new Drupal site is by default RDF-enabled with its content exposed as RDFa (RDF in HTML attributes) using well-known vocabularies such as FOAF, SIOC, SKOC, etc. <P> This hands-on tutorial will show you how Drupal's RDF functionality work and how to extend it to connect your information to the Web of Data, and in particular to the Linking Open Data cloud. The following topics will be covered: <ul> <li>Starting from scratch: installing and configuring Drupal 7</li> <li>Overview of the default RDF mappings in Drupal 7, and description of each related vocabulary</li> <li>Choosing the right additional modules and structuring your Drupal site according to your needs</li> <li>Finding, extending and reusing existing vocabularies to map your content model to RDF</li> <li>Leveraging the amount of Linked Data openly available on the Web using the power of SPARQL</li> <li>Integrating your site in the Linked Open Data eco-system</li> <li>Creating new Drupal modules with RDF mappings to provide more Linked Data</li> </ul> We assume that the audience will have some basic knowledge of the Semantic Web, especially RDFa and Linked Data. We will however start the tutorial with a few slides introducing the topic. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3191 http://purl.org/dc/elements/1.1/description <h4>PART I | The Semantic Web?s Answer to Real-Time Dynamic Data Collection for Regional H1N1 Preparedness and Planning</h4> <P> Ram Vedam, Senior Scientific Programmer, University of Texas at Houston - Health Sciences Center Matthew Vagnoni, Scientific Programmer II / Ph.D. Student, University of Texas at Houston, Health Sciences Center <P> Departments of public health have long been famous for being overwhelmed with emergencies and local and federal mandates that all require customized and sophisticated information collection and processing tools, but no budget and no time to plan and to develop them. <P> International H1N1 outbreaks in the past year are examples of how an unprecedented event can overwhelm a health system, no matter big or small it is. The difference is that today the Semantic Web technologies can be leveraged to encompass requirements of real-time and just-in time data collection, integration and interpretation in a way that existing infrastructures can be dynamically reconfigured and reused to adapt to novel requirements and unforeseen use-cases with no cost, as opposed to costly and inefficient practice and investment in developing, and maintaining redundant tools, and information silos, each being very specialized to a given problem. <P> The Survey on Demand System (SODS) developed at the UT-Houston School of Health Information Sciences allows ordinary users with minimal computer experience to design, and deploy advanced data collection instruments complete with all work-flow management, team-working, audit and control, data protection, and security features of any custom built application. <P> This includes: <ul> <li>Model Driven Design, and Human Computer Interactions</li> <li>Versioning and Support of Longitudinal Change and Tracking</li> <li>Variable level transaction logging and rollback</li> <li>Asynchronous (occasionally connected) Information Exchange and Synchronization</li> <li>Automated within and between project data integration</li> <li>Support of standard vocabularies or local data dictionaries</li> <li>Services Oriented Architecture</li> </ul> <P> <hr width="10%" /> <P> <h4>PART II | TrialX: Enabling patients find clinical trails by bringing Semantic Web, Personal Health Records and Web 2.0 together</h4> <P> Karthik Gomadam, Problem Solver, Applied Informatics Inc. Chintan Patel, Co-founder / Problem Solver, Applied Informatics Inc. Vivek Gard, Co-founder / Problem Solver, Applied Informatics Inc. <P> TrialX?s award-winning technology has been designed to help patients, sponsors, hospitals and investigators in the clinical trials process. It allows patients to easily enter their own personal information or securely integrate with consumer-centric personal health record platforms offered by Microsoft HealthVault and Google Health, and then use that information to offer services that significantly reduce the effort expended by consumers and investigators to find each other. TrailX seamlessly integrates multiple data sources using rich semantic technologies, leveraging on existing and open semantic models, such as UMLS. TrialX was the winner of the ISWC Semantic Web Challenge (Open Track) in 2009 as well as the winner of the NYENT 2009. TrialX has been featured prominently in press (http://trialx.com/press/). Recently, TrialX has launched in the UK, Canada, and India. We are also testing our healthcare integration middlware with some of the big hospitals in the US. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3191 http://purl.org/dc/elements/1.1/title Semantic Health Solutions for Clinical Trials and Real-time Public Health Monitoring
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http://data.semanticuniverse.com/resource/semtech-2010-2857 http://swrc.ontoware.org/ontology#keywords data-integration
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http://data.semanticuniverse.com/resource/semtech-2010-2857 http://purl.org/dc/elements/1.1/description In late 2009, Pfizer Global R&D engaged in a pilot project to link data stored in multiple repositories using imprecise connections. High ROI use cases were identified that served to test challenging data integration requirements, under a project timeline that would be difficult or impossible to meet with traditional relational or object-oriented technologies. Based on the data integration requirements, initial estimates for the pilot timeline were in the 4-6 month range. By applying semantic technology to integrate datasets ?on the fly?, the pilot was completed within a 6-week timeframe. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2857 http://purl.org/dc/elements/1.1/abstract This presentation will discuss a pilot project at Pfizer that applied semantic technologies to solve several tough data integration challenges and meet high-ROI use cases under a short timeline.
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http://data.semanticuniverse.com/resource/semtech-2010-2857 http://purl.org/dc/elements/1.1/title Knowledge Sharing Using Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2010-3334 http://purl.org/dc/elements/1.1/title The Next Generation Consumer Business ? Semantic Real Time Intelligent Decision Automation
http://data.semanticuniverse.com/resource/semtech-2010-3334 http://purl.org/dc/elements/1.1/description In today?s connected online world, to optimize a customer oriented businesses requires real time contextual customer knowledge across all business channels and relevant social and competitive forces. This knowledge must be used to control the intended outcome of each business transaction. In complex, heavily customer-centric businesses such as Telecommunications, Health Care, and Financial Services, the optimal business must understand how each action of the business and the individual customer relates to the profitability of the business and customer satisfaction. This is possible if systems holistically see what is going on in real time, determine the meaning of these activities, and in-stream decide and take the optimal action which maximizes profit and customer stickiness. Every business function should be coordinated and driven through a complete awareness of the business theatre. <P> The systems to accomplish this are proactive, they are predictive, they are personalized, and they learn to optimize their behavior for each individual customer. Today, Telecommunications and other large businesses can require the real time harmonization of 10 billion activities a day. We show a means to accomplish this with real time 24*7 semantic technology, capable of directly driving the largest businesses in the world. The results if this type of system can be amazing, including massive cost reductions in customer care, write-offs, retention, and improvements in customer satisfaction, 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-2010-2825 http://purl.org/dc/elements/1.1/abstract Demonstrating how the work of a publisher is improved by an integrated semantic tool within a CMS system for example with automatic annotations and meaningful recommendations.
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http://data.semanticuniverse.com/resource/semtech-2010-2825 http://purl.org/dc/elements/1.1/description An editor needs to aggregate all relevant sources, retrieve meaningful content, and get proper recommendations when writing an article. Down the value chain when publishing the article the publisher wants to keep his visitor longer on the web page and guide him along the own portal, always keeping in mind that the user will be guided by the content of interest. <P> Current technologies are not enough to handle such challenging tasks. This session will demonstrate how an existing publisher has realized a successful implementation and what new services have been created: <ul> <li>Semantic Factory connected with Drupal CMS</li> <li>Recommendation Plug-In for the editor</li> <li>Semantic Annotation Service</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2825 http://purl.org/dc/elements/1.1/title Applying Semantic Extensions and New Services to Drupal
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http://data.semanticuniverse.com/resource/semtech-2010-3246 http://purl.org/dc/elements/1.1/description <p><b>9:00 - 10:00</b> Identity</p> <p>A Survey of Identifiers and Labels in OWL Ontologies (0:35)<br> <i>Nor Azlinayati Abdul Manaf, Sean Bechhofer and Robert Stevens</i></p> <p>Developing Identity in Linked Data (0:35)<br> <i>James P. McCusker and Deborah L. McGuinness</i></p> <p><b>10:00 - 10:30</b> Break</p> <p><b>10:30 - 11:00</b> Open Discussion </p> <p><b>11:00 - 12:15</b> Syntax and Transformations</p> <p>Terp: Syntax for OWL-friendly SPARQL queries (0:20)<br> <i>Evren Sirin, Blazej Bulka and Michael Smith</i></p> <p>M2: A Language for Mapping Spreadsheets to OWL (0:35)<br> <i>Martin O'Connor, Christian Halaschek-Wiener and Mark Musen</i></p> <p>OWLGrEd: a UML Style Graphical Notation and Editor for OWL 2 (0:20)<br> <i>Janis Barzdin?, Guntis Barzdin?, Karlis Cerans, Renars Liepin? and Arturs Sprogis</i></p> <p><b>12:15 - 13:15</b> Lunch Break</p> <p><b>13:15 - 15:00</b> Ontology Modeling</p> <p>Representing Social Reality in OWL 2 (0:35)<br> <i>Rinke Hoekstra</i></p> <p>The Justificatory Structure of OWL Ontologies (0:35)<br> <i>Samantha Bail, Bijan Parsia and Ulrike Sattler</i></p> <p>Constructions for Modeling Product Structure (0:35)<br> <i>Henson Graves</i></p> <p><b>15:00 - 15:30</b> Break</p> <p><b>15:30 - 16:10</b> Miscellanous Applications</p> <p>Experiences Integrating Temporal Metadata in a Domain Ontology (0:20)<br> <i>Eric Rozell, Patrick West and Peter Fox</i></p> <p>Leverage of OWL-DL axioms in a Contact Centre for Technical Product Support (0:20)<br> <i>Alexandre Kouznetsov, Bradley Shoebottom, Rene Witte and Christopher JO Baker</i></p> <p><b>16:10 - 16:45</b> OWLED Business Meeting</P> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2737 http://www.w3.org/2000/01/rdf-schema#label Semantics for the Rest of Us
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http://data.semanticuniverse.com/resource/semtech-2010-2737 http://purl.org/dc/elements/1.1/description What is Web 3.0/Semantic Web and why is it important? What's the value? What are all these acronyms: RDF, OWL, SPARQL? What's a "triple" and why should you care? Does this have anything to do with "linked data"? Or perhaps you know the answers, but not how to convey them to others. <P> In this session, we'll address some of these core questions in an easy-to-understand way, even if you have never seen a line of computer code. Attendees will learn the basics of core semantic technologies and how the technologies are being used today, as well as helpful ways to simply and clearly explain semantic technologies. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2737 http://purl.org/dc/elements/1.1/abstract Eric Franzon of Semantic Universe will provide an introduction to semantic technologies to be followed by Q&A. Folks new to the space will find this to be an essential primer for the week's events, and others will find it to be a helpful review.
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http://data.semanticuniverse.com/resource/semtech-2010-3172 http://purl.org/dc/elements/1.1/description The first semantic solutions exist primarily for contextual advertising and search. Varied new semantic-powered applications are coming to market, or in beta, which will generate a flood of new data and metrics for marketers: services for sentiment analysis, real-time web monitoring, market research and the measurement of online behavior. These services, in conjunction with powerful Linked Data applications, will then drive the evolution to "Marketing with Data." <P> Topics include: <ul> <li>What is Web 3.0?</li> <li>Contextual advertising</li> <li>Search, RDFa and SEO</li> <li>Linked Data</li> <li>Real-time data and sentiment analysis</li> <li>Web commerce</li> <li>Personalization</li> <li>Privacy</li> <li>Social network analysis</li> <li>Marketing with data</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3172 http://www.w3.org/2000/01/rdf-schema#label How Will Semantics Impact Marketing and Advertising?
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http://data.semanticuniverse.com/resource/semtech-2010-3172 http://purl.org/dc/elements/1.1/title How Will Semantics Impact Marketing and Advertising?
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http://data.semanticuniverse.com/resource/semtech-2010-3172 http://purl.org/dc/elements/1.1/abstract This session will lay out the topics we will discuss during the next two days of the conference, and provide some higher-level context for why these topics are so important.
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http://data.semanticuniverse.com/resource/semtech-2010-2838 http://purl.org/dc/elements/1.1/abstract This session overviews current metadata approaches and explores the integration of semantic vocabularies with auto-tagging applications.
http://data.semanticuniverse.com/resource/semtech-2010-2838 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/seth-maislin
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http://data.semanticuniverse.com/resource/semtech-2010-2838 http://purl.org/dc/elements/1.1/description Knowledgeable human beings are undisputedly the best source for authoring high-quality metadata, but the information machine is too fast for our bodies. Thankfully, we have performance enhancements, tools that leverage what we know and we've done already without succumbing to the cloud. This presentation briefly introduces the statistical and rules-based metadata application approaches in today's market, and then focuses in on their practical applications and limitations in business and research. We'll explore the roles of taxonomy and ontology within auto-tagging, whether you should build or buy a taxonomy, and when you need to "break the rules" to make your systems work together better. Auto-tagging and autoclassification aren't magic bullets either; learn the important distinction between assisted and automatic techniques, and how to balance the appeal of an out-of-the-box solution with your real-life needs for long-term maintenance and change management <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2852 http://www.w3.org/2000/01/rdf-schema#label Linking Data: The Legal Implications
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http://data.semanticuniverse.com/resource/semtech-2010-2852 http://purl.org/dc/elements/1.1/abstract A presentation outlining the potential legal pitfalls of linking data, a survey of activities in this area and an assessment of proposed solutions.
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http://data.semanticuniverse.com/resource/semtech-2010-2852 http://purl.org/dc/elements/1.1/description To date most of the focus on the Semantic Web has, quite rightly, been focused on the enabling technologies. However, as the technologies are becoming more mainstream, and as ever increasing volumes of Linked Data is produced, the implications of linking this data becomes more of an issue. This presentation highlights some of the current thinking as to the possible legal implications of linking data while discussing some solutions that are emerging. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2852 http://purl.org/dc/elements/1.1/title Linking Data: The Legal Implications
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http://data.semanticuniverse.com/resource/semtech-2010-3052 http://purl.org/dc/elements/1.1/title Visual Tools for the Web of Data
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http://data.semanticuniverse.com/resource/semtech-2010-3052 http://www.w3.org/2000/01/rdf-schema#label Visual Tools for the Web of Data
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http://data.semanticuniverse.com/resource/semtech-2010-3052 http://purl.org/dc/elements/1.1/description Datao is a software platform for the Semantic Web. With Datao, both experts and non-technical people can consume the Web of Data in an easy, natural way. Its fully visual interface provides an intuitive environment for: Discovery and aggregation of data sources SPARQL authoring Templating query results to HTML Creating browsing scenarios for the Web of Data <P> Datao also includes a Semantic Web Browser. Based on Java and Firefox, it is a web browser enhanced with semantic middleware. With this Semantic Web Browser end users can browse the Web of Data as easily as they browse the World Wide Web. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3052 http://purl.org/dc/elements/1.1/abstract A visual Integrated Development Environment for the Semantic Web. Including a Semantic Web Browser to browse the Web of Data.
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http://data.semanticuniverse.com/resource/semtech-2010-3052 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-3227 http://purl.org/dc/elements/1.1/description The charter of government is to be responsive to the people. As such, government information belongs in the hands of the governed. Semantic Web technologies provide an unparalleled capability for making public data genuinely available to the general populace. Common practice in the past has been to publish data in idiosyncratic, disconnected forms. With new policies for information sharing in place, there is a wide appreciation of the need for sharable, connectible government information. This tutorial draws on information sharing projects such as the Federal Enterprise Architecture and the resources at open government web sites like oegov.org to provide attendees with a taste of real semantic web applications and the promise this approach holds for open, shared government. Attendees will learn the basics of the Semantic Web, as well as proven methods for accessing and combining existing information sources (e.g., spreadsheets, XML feeds and databases). Furthermore, we will use hands-on exercises to illustrate how to create applications using government information published as linked data on sites like oegov.org and dbpedia.org. <P> This half-day tutorial will include lectures and exercises on the following topics: <ul> <li>Integrating existing data ? spreadsheets and databases, RSS, Email, XML (half hour)</li> <li>Introduction to government semantic resources, probably including FEA and OEGOV(one hour)</li> <li>Hands-on exercise: Creating a simple integrated application</li></ul> <P> PREREQUISITES<br> The tutorial assumes familiarity with basics of RDF, RDFS and SPARQL, but does not assume in-depth knowledge. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3227 http://www.w3.org/2000/01/rdf-schema#label Workshop: Building Semantic Web Applications for Government -- Using TopBraid Suite
http://data.semanticuniverse.com/resource/semtech-2010-3227 http://purl.org/dc/elements/1.1/title Workshop: Building Semantic Web Applications for Government -- Using TopBraid Suite
http://data.semanticuniverse.com/resource/semtech-2010-3227 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/dean-allemang
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http://data.semanticuniverse.com/resource/semtech-2010-3273 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3273 http://www.w3.org/2000/01/rdf-schema#label Leveraging Unstructured Data in Business Intelligence with xPatterns
http://data.semanticuniverse.com/resource/semtech-2010-3273 http://purl.org/dc/elements/1.1/title Leveraging Unstructured Data in Business Intelligence with xPatterns
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http://data.semanticuniverse.com/resource/semtech-2010-3273 http://purl.org/dc/elements/1.1/description Atigeo's xPatterns is a platform that facilitates the intelligent discovery of knowledge from large, disparate sources of unstructured data. Underlying the product is novel technology that allows the automated creation and dynamic maintenance of semantic ontologies. This presentation will provide an overview of how xPatterns can be leveraged to: <ul> <li>Provide a mechanism for leveraging unstructured enterprise data into present business intelligence data flow and processes.</li> <li>Allow access to external real-time unstructured data sources, including social media, for business intelligence, CRM and marketing.</li> <li>Compliment existing business intelligence, reporting analytics, and data mining solutions while leveraging existing investments to incorporate unstructured data.</li> <li>Improve productivity over conventional text analytics platforms by reducing the time required to create and maintain ontologies for text analytics.</li> <li>Enable businesses to associate findings in structured and unstructured data to provide new dimensions for reporting and attributes to drive predictive modeling and business decision processes. </li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3273 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/patrick-quigley
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http://data.semanticuniverse.com/resource/semtech-2010-3273 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/semtech-2010-3020 http://purl.org/dc/elements/1.1/description A growing number of organizations are looking to incorporate Semantic Web technologies into their business environment and every organization has complex information integration problems to solve. However, without existing in-house expertise, getting Semantic Web enabled applications off the ground can be difficult. <P> Using real-world examples, we will show how existing enterprise data can be integrated into full-featured applications. We will focus on creating RDF from existing data using a "Semantic ETL (Extract, Transform, Load)" toolkit that uses Machine Learning based information integration components to convert legacy data into RDF, while also creating an OWL ontology representing the data. This ontology is used to create a CRUD-style (Create/Read/Update/Delete) web application and RESTful web service(s) for maintaining the data. Finally, the Semantic ETL process also outputs a model file to enable faceted browsing and navigation via SPARQL, which is fully integrated into the web application. The entire process uses a minimum of "hands-on" work and significantly speeds Semantic Web application development. <P> This talk will cover: <ul> <li>Using Pelorus to provide a faceted navigation tool for your data</li> <li>Bootstrapping Semantic Web artifacts such as ontologies from your existing data</li> <li>Transforming your existing enterprise data into RDF via Semantic ETL</li> <li>Creating simple RESTful, CRUD-style web applications from an ontology</li> <li>RDF-Java integration via Empire, a JPA implementation for RDF</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-3020 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-2010-3020 http://purl.org/dc/elements/1.1/abstract Present the Pelorus Platform, a standards-based application development stack geared toward enterprise information integration via RDF, SPARQL, and OWL.
http://data.semanticuniverse.com/resource/semtech-2010-3020 http://www.w3.org/2000/01/rdf-schema#label Pelorus: An Integrated Platform for Building Semantic Web Applications
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http://data.semanticuniverse.com/resource/semtech-2010-3020 http://purl.org/dc/elements/1.1/title Pelorus: An Integrated Platform for Building Semantic Web Applications
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http://data.semanticuniverse.com/resource/semtech-2010-2764 http://purl.org/dc/elements/1.1/title Improving Institutional Portfolio Performance through Better Data Interoperability
http://data.semanticuniverse.com/resource/semtech-2010-2764 http://swrc.ontoware.org/ontology#keywords portfolio-performance
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http://data.semanticuniverse.com/resource/semtech-2010-2764 http://purl.org/dc/elements/1.1/description Data interoperability is central to business operations, yet there are few empirical studies that demonstrate the measurable effects of improvements in information flow. This presentation discusses the results and the implications of a ten-year study (1999-2009) that evaluated the impact of the 'data interoperability burden' on institutional investment performance and portfolio returns. <P> This presentation will highlight the following: <ul> <li>Strategic issues on how portfolio performance can be supported by improving information flow within investment management firms</li> <li>Tactical issues on how much of a portfolio's returns can be attributed to manager skill vs. operational effectiveness</li> <li>Specific examples of data remediation initiatives that did (or did not) yield performance gains for an investment portfolio</li> <li>The technique used to measure the data interoperability burden</li> <li>Building the business case for ROI in support of operational improvements</li> </ul> A tool and technique were developed, including an ontology, some OWL, topic maps, and RDF. This tool allowed us to measure the semantic 'effort' required to programatically bridge disparate transaction data (e.g., what security is being traded; for which client account; under what compliance regimes; etc.) between the front, middle and back 'offices' within an investment firm, and also with their various counterparties (e.g., brokers, banks, institutional clients, fund administrators). Given this tool, we could quantify the data interoperability burden, which we then correlated with the performance shortfalls of an institutional portfolio (e.g., when a fund fails to meet or exceed its benchmark, such as the Russell 1000, FTSE 100, Nikkei 225, etc.) <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2764 http://purl.org/dc/elements/1.1/abstract We present an empirical study that demonstrates the measurable effects of improved data interoperability on the performance of institutional investment portfolios.
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http://data.semanticuniverse.com/resource/semtech-2010-3241 http://purl.org/dc/elements/1.1/title Jena User Group
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http://data.semanticuniverse.com/resource/semtech-2010-3241 http://purl.org/dc/elements/1.1/abstract Kick-off session for Jena User Group meeting.
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http://data.semanticuniverse.com/resource/semtech-2010-3241 http://purl.org/dc/elements/1.1/description This session is a meeting for Java developers using the Jena Semantic Web Framework. In this session, we will introduce applications and examples of Jena in use, discuss best practices and future development directions. It will be organized as several 5- to 30-minute presentations from Jena users and developers while leaving time for informal discussion and idea exchange. This is the first year that Jena is independent of HP labs. The session will start with an overview of the current status of the Jena project including licensing, new web site, community involvement and support. <p> Agenda</p> <p> <b>3:15</b> Kick off</p> <p> <i>Jeremy Carroll</i>: Agenda Overview<br> <i>Andy Seaborne</i>: Jena Team Update</p> <p> <b>3:30</b> <i>Alex Miller</i>: Plaza-rdf Clojure library</p> <p> <b>3:50</b> <i>Jeff Schmitz</i>: Using SPARQL Server Pages</p> <p> <b>4:10</b> Short Talks (5 mins each)</p> <p> <i>Jeremy Carroll</i>: BufferingGraphs<br> <i>Olivier Rossel</i>: GUIs for the Web of Data<br> <i>Andre Rubin</i>: Handling Concurrent Modifications<br></p> <p> <b>4:30</b> <i>Sanjiva Nath</i>: Semantic Enterprise Information Integration</p> <p> <b>4:50</b> <i>Dave Kolas</i>: Spatial & temporal indexing in Parliament </p> <p> <b>5:10</b> <i>Marco Neuman</i> and <i>Break Baldwin</i>: Automatic URI Matching <P>
http://data.semanticuniverse.com/resource/semtech-2010-3241 http://swrc.ontoware.org/ontology#keywords jena-semantic-web-framework
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http://data.semanticuniverse.com/resource/semtech-2010-3139 http://www.w3.org/2000/01/rdf-schema#label Drupal and the Semantic Web: from RDF to Whitehouse.gov
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http://data.semanticuniverse.com/resource/semtech-2010-3139 http://purl.org/dc/elements/1.1/description As we usher in this era of open data in which organizations of all types are taking a queue from the administration's focus on transparency, accountability, and efficiency by making raw data available to the public in platform independent formats, web CMS is rapidly becoming a useful place to showcase semantic web standards. <P> Meanwhile this trend is converging with a dramatic rise in the popularity of the most semantic web friendly open source CMS, Drupal, which features RDF as part of its core architecture. In October 2009, the official site of the President and flagship site for the administration, Whitehouse.gov, re-launched on Drupal and featured some nods to semantic web technology with the addition of RDFa content and heavy use of taxonomies to drive content and search. <P> This session will explore three key semantic technologies in use in the Drupal CMS framework that can fuel the open government movement: <P> 1. Integration of RDF and SPARQL technology into the core CMS in Drupal 7 <P> 2. Specific techniques to tap into openly exposed RDF data resources from the emerging Linked Open Data cloud <P> 3. Use of web services like OpenCalais neatly integrated into Drupal to provide semantic functionality <P> Using practical use cases, we will cover a variety of techniques and technologies that can be used to integrate Linked Open Data and web services to make your site richer and provide depth to your content. This session will satisfy the appetites of anyone interested in seeing how web CMS is adopting semantic web and solving real world content challenges. Technical implementers looking for details on how to achieve integration of Linked Open Data into an existing site or how to architect a new site to use these resources will also find the session technically satisfying. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3139 http://purl.org/dc/elements/1.1/title Drupal and the Semantic Web: from RDF to Whitehouse.gov
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http://data.semanticuniverse.com/resource/semtech-2010-2921 http://purl.org/dc/elements/1.1/abstract OASIS Integrated Collaboration Object Model (ICOM) Technical Committee representatives will present the concomitant representations of ICOM in RDF and UML, influenced by the interplay of RDF and UML modeling methodologies.
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http://data.semanticuniverse.com/resource/semtech-2010-2921 http://purl.org/dc/elements/1.1/description OASIS Integrated Collaboration Object Model (ICOM) Technical Committee (http://wiki.oasis-open.org/icom), formed by Cisco Systems, DERI, EcoSpace, KnowledgeTree, and Oracle Corporation specifies the standards for collaboration objects, along with the classes, attributes, relationships, constraints, and behavior for a broad range of collaboration activities in a complete, integrated, and interoperable collaboration environment. <P> The ICOM specifications will encompass and improve on a range of models which are part of existing standards and technologies to eliminate the impedances, promote seamless transitions between components, and reduce the fragmentation of collaboration tools. Defined from the outset for concomitant representations and transformations between RDF and UML, ICOM forms a bridge between the Semantic Web and object-oriented application development. <P> The work is inspired by Vannevar Bush, Doug Engelbart, and Tim Berners-Lee?s progressive visions towards ?the global network of knowledge to augment the human intellect?. The ICOM standards and technologies can supplement the network of collaboration entities. <P> ICOM is extensible and includes diverse classes of objects for: <ul> <li>Teamwork: shared workspaces, discussion forums, real-time conferences, presence, etc.</li> <li>Communication: e-mail, instant message, telephony, RSS, etc.</li> <li>Content: text and multi-media contents, contextual connections, taxonomies, folksonomies, tags, saved searches, etc.</li> <li>Coordination: address books, calendars, tasks, journals, etc.</li> <li>Social networking: articulated social networks among users, communities, groups, activities, wiki pages, blogs, recommendations, social bookmarking, etc.</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2921 http://purl.org/dc/elements/1.1/title OASIS Integrated Collaboration Object Model (ICOM)
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http://data.semanticuniverse.com/resource/semtech-2010-3185 http://purl.org/dc/elements/1.1/description <h4>PART I | Semantic Content Validation: Learning to Trust Data Sources Again</h4> <P> Andy Hickl, Co-Founder and CEO, Swingly <P> Information consumers now have access to more information than ever, from open data initiatives like data.gov to Web 2.0 communities like Wikipedia. Likewise, a new generation of semantic apps make it possible to automatically extract and update knowledge bases with information across the open Web. Yet data within the real-time Web is in constant flux, so how can we really trust all of this information? <P> In this session, Andy Hickl, CEO of Language Computer Corporation (LCC), will discuss approaches, as well as the challenges and possible solutions, for the next generation of semantic systems that employs dedicated mechanisms to ensure that knowledge acquired from text is valid, justified, consistent, up-to-date, and complete. <P> <hr width="10%" /> <P> <h4>PART II | Security and Privacy for the Semantic Web: A Holistic Approach</h4> <P> Amit Jain, Information Scientist, BeliefNetworks Inc.<br> Ted Tanner, CTO, BeliefNetworks Inc. <P> This session addresses the security problems that arise when sharing data on the Semantic Web. One of the biggest obstacles in achieving the success of Semantic Web systems today has been the lack of security solutions that work in data sharing open environments. Today, Web services modeled to be as semantic aware automated systems process and share a variety of personal and corporate data that needs to be protected from different security threats. For example, the privacy of the data needs to be maintained, giving the data owners the option to define the privacy policies for the provider. At the same time, only authorized persons or agents should have access to their information. With the data being annotated with Semantics, it poses a bigger threat now that anybody with unauthorized access to the data would also have access to the meaning of the data. Hence, it requires additional security mechanisms to deal with the semantic representation standards such as RDF and OWL. <P> In this session, we present the threats posed by semantification of data and services and what direction we need to mold our security tools to deal with them. As a first step, we present a semantic aware authorization system being used for modeling security and privacy policies. Then the future directions are discussed. This presentation will also address the following topics: <ul> <li>Privacy and Security for Semantic Web, why a new approach is needed</li> <li>RDF and OWL Security</li> <li>Policies and the available Standards</li> <li>Trust Modeling for Semantic Web</li> <li>Tools for complementing Semantic Knowledge with the Security Infrastructure</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2819 http://purl.org/dc/elements/1.1/abstract This lightning talk is a live demonstration of Cambridge Semantics's Anzo software. We'll show how Anzo allows Excel to be used as a real-time interface for collaborating on data. We'll also allow the audience to follow along, live, on their laptops.
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http://data.semanticuniverse.com/resource/semtech-2010-2819 http://purl.org/dc/elements/1.1/description Anzo for Excel is Cambridge Semantics' flagship product for leveraging Microsoft Excel as a flexible tool for creating, editing, and viewing semantic data. In this live lightning talk, we'll build a complete application illustrating how: <P> An ontology can be automatically created from spreadsheet data in seconds A normal spreadsheet can be transformed into a data collection form The conference session data can be published on the Web in a way that allows visitors to create their personal, tailored views of SemTech A change to a conference session's details propagates in real-time to all other spreadsheets and Web views that reference the session We encourage audience members to use their Web browser to follow along. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3097 http://purl.org/dc/elements/1.1/title Semantic Search: New Technologies, Ideas and Companies
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http://data.semanticuniverse.com/resource/semtech-2010-3097 http://purl.org/dc/elements/1.1/description Semantics is changing search paradigms more profoundly than most of us yet realize. And it?s just the beginning of the shift. Semantics changes the way we interact with search, and how we experience the process. A great example of this is Siri, the voice search application demonstrated at SemTech last year. <P> This session will cover numerous new ideas, companies and technologies in the semantic search world, including: <ul> <li>Living Search: The convergence of AI, natural language understanding, common sense reasoning and machine learning into a fully contextual, personalized discovery platform</li> <li>Deep Web: That portion of the Web hidden from view that is estimated to have 500 times more content than is findable on current search engines. What is the effect on information usage when search engines can sift through library catalogs, airline reservation systems, phone books and all kinds of scientific databases lying deep inside the Web?</li> <li>Search Appliances: A vision of search driven by millions of community built search applications and widespread public and private data sets, customized for select content. One way to think of this is as community-based versions of Wolfram Alpha</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3019 http://purl.org/dc/elements/1.1/abstract This panel will discuss the current state and future of the upcoming W3C standard RDB2RDF, a standardized language for mapping relational databases to RDF.
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http://data.semanticuniverse.com/resource/semtech-2010-3019 http://purl.org/dc/elements/1.1/description Mapping data from relational databases still involves choosing among numerous customized solutions. The RDB2RDF Working Group is creating a new W3C standard for mapping relational data to RDF based on the best practices of current approaches. This should allow current data in relational databases to be transformed to RDF with minimal effort, creating a standardized mapping language that will allow the market to concentrate on optimization and custom features rather than re-inventing the wheel. However, a number of important issues need to be confronted by the industry and community at the intersection of Linked Data, SPARQL, and SQL. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3065 http://purl.org/dc/elements/1.1/description There is tremendous interest in Representational State Transfer (REST) as an architectural style for building scalable, flexible, information-driven architectures in the Enterprise. However, managers want to understand why they should deviate from the blue prints laid down by the industry leaders. They want to make business-based technology decisions that lay a path to forward progress. <P> This talk will introduce REST and walk through why it is so important and makes such a difference. We will talk about REST API design, security, long-lived systems, content-negotiation, contract enforcement, when REST might not make sense, etc. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2801 http://purl.org/dc/elements/1.1/title Semantic Modeling Notation: Making Ontologies Human-Accessible
http://data.semanticuniverse.com/resource/semtech-2010-2801 http://www.w3.org/2000/01/rdf-schema#label Semantic Modeling Notation: Making Ontologies Human-Accessible
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http://data.semanticuniverse.com/resource/semtech-2010-2801 http://purl.org/dc/elements/1.1/abstract Semantic information for a domain is often modeled in the form of an ontology (e.g., OWL). This is powerful for machine processing, but provides significant challenges in terms of human understanding and socialization. A flexible, standard visualization notation is needed to overcome these challenges.
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http://data.semanticuniverse.com/resource/semtech-2010-2801 http://purl.org/dc/elements/1.1/description One of the difficulties of using semantic technologies for real-world applications is the difficulty of conveying the semantic 'model' to people. This is no small matter, as the ability to understand a new technology is directly related to how well the concepts can be comprehended and used by people to do their jobs. One could argue that a large impetus to the recent success of business processing technologies is the introduction and uptake of the Business Process Modeling Notation (BPMN). <P> This talk describes an analogous notation targeted at semantic domain modeling. We will show how a complex ontology (classes, properties, etc) and ontology instances can be represented in a visual notation, both in static form and for dynamic discovery and navigation. It is the intent of this talk to socialize the idea of a standard ontology modeling notation, with the ultimate goal of unifying the semantic community behind such a standard. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3033 http://www.w3.org/2000/01/rdf-schema#label Using a Controlled Vocabulary for Managing a Digital Library Platform
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http://data.semanticuniverse.com/resource/semtech-2010-3033 http://swrc.ontoware.org/ontology#keywords controlled-vocabulary
http://data.semanticuniverse.com/resource/semtech-2010-3033 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/sean-boisen
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http://data.semanticuniverse.com/resource/semtech-2010-3033 http://purl.org/dc/elements/1.1/description The Libronix Controlled Vocabulary (LCV) organizes parallel but distinct content in the domain of Biblical studies to integrate reference information and support search, discovery, and knowledge management. The LCV captures: Preferred and alternate terminology Inter-term relationships Term hierarchy Linkage to other semantic information <P> The initial version of the LCV (now shipping in the Logos digital library platform) comprises some 11,000 terms and continues to grow as more reference works are added. It also provides the backbone of http://topics.logos.com, a website for user contributions to terminology and content. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3033 http://purl.org/dc/elements/1.1/abstract Provide a practical case study on semantically organizing reference material to support search and navigation, using a controlled vocabulary.
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http://data.semanticuniverse.com/resource/semtech-2010-3033 http://purl.org/dc/elements/1.1/title Using a Controlled Vocabulary for Managing a Digital Library Platform
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http://data.semanticuniverse.com/resource/semtech-2010-2777 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-2010-2777 http://purl.org/dc/elements/1.1/description Databases contain implicit semantics. Tables are composed of rows and columns, with the columns providing the semantic type of the data in the columns and the rows providing the semantic relation between data. Databases are good for preserving the integrity of transactions but are not very easy to search, requiring special languages and vocabularies, or confusing form based interfaces. <P> Search on the other hand is something easy and familiar to the people in the home and workplace. Every can use a search engine to find information. Modern search engines provide not just lists of results but extract information that make search easier: facets, named entities, locations, prices. <P> Here we will show how both databases and search can live side by side, with data saved and locked in the database, but the same data being available almost instantly to end users through familiar search interfaces. A lightweight, agile version of the database can exist in a search index, providing the same semantics as the underlying database. This move frees the data from a restricted caste of IT specialists and places it in the hands of the whole enterprise, while preserving the same semantics and same access rights as in the database. <P> We will show how this transfer is performed, and describe case studies, including tracking and tracing, and customer response management. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2777 http://www.w3.org/2000/01/rdf-schema#label Replicating the semantics of databases using search engine technology
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http://data.semanticuniverse.com/resource/semtech-2010-2777 http://purl.org/dc/elements/1.1/abstract Understanding search based applications
http://data.semanticuniverse.com/resource/semtech-2010-2777 http://purl.org/dc/elements/1.1/title Replicating the semantics of databases using search engine technology
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http://data.semanticuniverse.com/resource/semtech-2010-3254 http://purl.org/dc/elements/1.1/abstract Part I: Pragmatic methods for mapping and integrating(linked data) web sources. Demonstrate how collaborative bottom-up data integration and ontology engineering can benefit the web of data. Part II: Examines what can be done to make government linked data publishing more accessible to the broad mass of web developers whose creativity is the key to deriving value.
http://data.semanticuniverse.com/resource/semtech-2010-3254 http://purl.org/dc/elements/1.1/description <h4>PART I | Integrating the Web of Data</h4> <P> <i>Georgi Kobilarov, Managing Director, Uberblic Labs</i> <P> The Linked Data movement has led to an amazing amount of publicly available data on the web, with rich links between data objects. However, this linkage still mostly exists only on the level of individual instance level objects, leaving the task of integrating data schemas to the users. This talk will give an introduction to pragmatic web data integration, schema mapping and data reconciliation, and demonstrate these methods at the example of uberblic.org. <P> In addition to applying these methods to integrate web data sources, we will also present how the same methods can be used within the enterprise, linking enterprise sources to each other and to the web of data. <P> <hr width="10%" /> <P> <h4>PART II | Information Intermediaries for Government Linked Data</h4> <P> <i>Dave Reynolds, CTO, Epimorphics Ltd.</i> <P> Governments around the world are releasing data, in part to tap the creativity and enthusiasm of web developers to generate a cornucopia of public and commercial valued-added services. Some, notably the UK Government, have been experimenting with a linked-data approach to doing so and see real benefit in seeding a government data web. Yet for many of the developers who wish to engage with the data, the linked-data approach is intimidating. In this talk we will examine ways that an information intermediary could help to bridge this gap. <P> We will explore the following topics: <ul> <li>Survey the growing number of information intermediaries who aim to help developers discover and exploit data</li> <li>Explore the benefits of a linked-data approach and how an intermediary based on this could add real value</li> <li>Examine some of the barriers to uptake seen in the early UK beta site experimentation</li> <li>Discuss ways in which an intermediary could bridge the gap, so as to reduce those barriers to uptake while still delivering on the benefits of the linked data approach</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3254 http://www.w3.org/2000/01/rdf-schema#label Accelerating the Adoption of Linked Data
http://data.semanticuniverse.com/resource/semtech-2010-3254 http://purl.org/dc/elements/1.1/title Accelerating the Adoption of Linked Data
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http://data.semanticuniverse.com/resource/semtech-2010-2745 http://purl.org/dc/elements/1.1/description Google announced "Rich Snippets" just over a year ago in May 2009. If webmasters add structured data markup to their web pages, Google can use that data to show better search result descriptions. <P> In this talk, we'll reflect on what we've been up to in the last year: the adoption rate amongst webmasters, what we've learned, our successes as well as challenges left to be tackled. A particular focus of the talk will be on webmaster participation. What motivates webmasters to add markup? What obstacles do they face? And how do we accelerate the growth of the ecosystem? <P>
http://data.semanticuniverse.com/resource/semtech-2010-2745 http://purl.org/dc/elements/1.1/abstract Discuss Google's Rich Snippets project, what has been done, areas of success and challenges
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http://data.semanticuniverse.com/resource/semtech-2010-2745 http://purl.org/dc/elements/1.1/title Google Rich Snippets
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http://data.semanticuniverse.com/resource/semtech-2010-2966 http://www.w3.org/2000/01/rdf-schema#label Information Access: How Semantic Web Helps Implementing Non-Discrimination
http://data.semanticuniverse.com/resource/semtech-2010-2966 http://swrc.ontoware.org/ontology#keywords fragmentation
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http://data.semanticuniverse.com/resource/semtech-2010-2966 http://purl.org/dc/elements/1.1/abstract Our approach of interfacing semantic information opens new ways of presenting and accessing information and offers a solution to solve the irreconcilability of legally prescribed non-discrimination and practiced restriction.
http://data.semanticuniverse.com/resource/semtech-2010-2966 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/adrian-gschwend
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http://data.semanticuniverse.com/resource/semtech-2010-2966 http://purl.org/dc/elements/1.1/title Information Access: How Semantic Web Helps Implementing Non-Discrimination
http://data.semanticuniverse.com/resource/semtech-2010-2966 http://swrc.ontoware.org/ontology#keywords non-discrimination
http://data.semanticuniverse.com/resource/semtech-2010-2966 http://swrc.ontoware.org/ontology#keywords semantic-interface
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http://data.semanticuniverse.com/resource/semtech-2010-2966 http://purl.org/dc/elements/1.1/description International and national regulations require non-discriminating access to information, especially to public information made available by governments or international organizations like the UNO, EU and WHO. At the same time, however, information becomes more and more fragmented because of the growing predominance of platforms like Facebook and app stores for mobile phones and devices like game consoles. Hence, access to information becomes increasingly restricted. <P> Our approach of interfacing semantic information offers a solution to solve this irreconcilability of legally prescribed non-discrimination and practiced restriction. <P> In our presentation, we discuss three fundamental technical problems that need to be solved and propose our solution based on semantic web technologies. Once implemented, any kind of information cannot only be provided to visually impaired people, but we can also offer information-independent and at the same time device-specific interfaces for optimal integration and presentation. Information can be displayed to anyone anywhere without explicit adaptation. From a business perspective, this results in big cost savings. <P> Topics in this presentation include the following: <ul> <li>Current problems for visually impaired people</li> <li>Fragmentation of the web</li> <li>The technical challenge to solve</li> <li>Where semantic web technologies fit in</li> <li>A new era of interfaces</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2966 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/bart-van-leeuwen
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http://data.semanticuniverse.com/resource/semtech-2010-2934 http://swrc.ontoware.org/ontology#keywords industry-applications
http://data.semanticuniverse.com/resource/semtech-2010-2934 http://www.w3.org/2000/01/rdf-schema#label Auto-Categorization with Linguistic Semantics
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http://data.semanticuniverse.com/resource/semtech-2010-2934 http://purl.org/dc/elements/1.1/audience Introductory
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http://data.semanticuniverse.com/resource/semtech-2010-2934 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-2010-2934 http://purl.org/dc/elements/1.1/abstract The objective is to label or tag documents with a predefined list of categories, or to automatically group documents into concept clusters using linguistic semantic natural language processing methods.
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http://data.semanticuniverse.com/resource/semtech-2010-2934 http://purl.org/dc/elements/1.1/title Auto-Categorization with Linguistic Semantics
http://data.semanticuniverse.com/resource/semtech-2010-2934 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-semantics-for-enterprise-data
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http://data.semanticuniverse.com/resource/semtech-2010-2934 http://purl.org/dc/elements/1.1/description The challenges for auto-categorization are understanding the meaning of text and determining which aspects of the meaning represent what topic(s). Auto-categorization can involve either a predetermined categorization scheme of labels or concept clustering. "Aboutness" or "topic" for a given document is hard to discover or agree upon, and documents vary as to focus. That said, we used modified MESH labels as the gold standard for the Cognition Technologies auto-categorization technique. <P> Any automated method of category assignment calculates statistics (such as salience or TF/IDF) of occurrences of words, concepts, or other features in the documents. To the extent that the method can correctly interpret the structure and meaning of documents, the validity of the statistics is improved for enhanced precision and recall in topic assignment. Auto-categorization that operates upon string patterns makes more mistakes, and misses more desired category assignments than linguistically-based auto-categorization. This is because linguistic categorization does the following: <ul> <li>Handles morphological variants such as "bat-bats-batting-batted", "catch-catches-catching-caught" and "baby-babies."</li> <li>Disambiguates words. Incorrect usages are not counted, so "set" in a mathematical sense doesn't count towards a categories "musical set" or "theatrical stage set."</li> <li>Maps synonyms. The same concept expressed differently counts, so "viewer" (meaning TV or computer screen), "screen", "cathode ray tube", "CRT", etc. all count towards a topic of "computer screen."</li> <li>Reasons in ontology. Less specific examples of a more general concept count towards the latter, so "car", "truck" and "ship" (in appropriate meanings) count towards a topic "vehicle."</li> <li>Parses. Incorrect categorizations are avoided when topic concepts are not properly related, so "After his cancer, the doctor treated fewer patients" wouldn't count towards a category "cancer treatment."</li> <li>Recovers formal semantics. Incorrect categorizations in the scope of negation are avoided, as in "no cancer treatment". Correct categorizations requiring the interpretation of pronouns are counted, as in "The President...He called for aid" would count towards a topic of "US aid."</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2934 http://swrc.ontoware.org/ontology#keywords enterprise-applications
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http://data.semanticuniverse.com/resource/semtech-2010-2980 http://www.w3.org/2000/01/rdf-schema#label Commodity Semantic Search: A Case Study of DiscoverEd
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http://data.semanticuniverse.com/resource/semtech-2010-2980 http://purl.org/dc/elements/1.1/title Commodity Semantic Search: A Case Study of DiscoverEd
http://data.semanticuniverse.com/resource/semtech-2010-2980 http://swrc.ontoware.org/ontology#keywords education
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http://data.semanticuniverse.com/resource/semtech-2010-2980 http://purl.org/dc/elements/1.1/abstract This session will describe Creative Commons' experience developing a semantic search prototype using commodity products. Including: our experience using Google CSE, Yahoo! BOSS, and Apache Nutch on commodity hosting. We'll conclude with discussion of future prospects for semantic search with commodity services.
http://data.semanticuniverse.com/resource/semtech-2010-2980 http://swrc.ontoware.org/ontology#keywords cse
http://data.semanticuniverse.com/resource/semtech-2010-2980 http://www.w3.org/2002/12/cal/icaltzd/dtEnd 2010-06-24T16:00:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-2980 http://swrc.ontoware.org/ontology#keywords search
http://data.semanticuniverse.com/resource/semtech-2010-2980 http://purl.org/dc/elements/1.1/description Creative Commons first developed a semantic search prototype in 2004 to demonstrate searching for works by license. Since then, mainstream search engines have implemented this initial semantic feature in their products. <P> In 2008, Creative Commons began developing a second prototype, DiscoverEd, focused on exposing broader semantic information to users and searching using it. This prototype uses open educational resources (OER) as a test domain. <P> This case study will cover our experience developing this prototype using commodity technology. Our experience building on Google CSE, Yahoo! BOSS, and Apache Nutch, will be covered. Finally, we will also explore new developments in these products and how they can help developers get started quickly with semantic search in a low-cost manner. <P> Attendees can expect to learn the following: <ul> <li>How Google CSE and Yahoo! BOSS can enable simple semantic search</li> <li>How Creative Commons developed a semantic search solution using Nutch</li> <li>Current and prospective developments for quickly developing semantic search</li> </ul> <P>
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http://data.semanticuniverse.com/resource/semtech-2010-2980 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/nathan-r-yergler
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http://data.semanticuniverse.com/resource/semtech-2010-2902 http://purl.org/dc/elements/1.1/title Semantic Technology and Healthcare Reform: How to Decrease the Cost of Healthcare with Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2010-2902 http://purl.org/dc/elements/1.1/abstract The purpose of this presentation is to highlight a few ways to leverage Semantic Technologies in order to pave the way for the next generation healthcare systems, now being coined as Health 3.0.
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http://data.semanticuniverse.com/resource/semtech-2010-2902 http://www.w3.org/2000/01/rdf-schema#label Semantic Technology and Healthcare Reform: How to Decrease the Cost of Healthcare with Semantic Technologies
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http://data.semanticuniverse.com/resource/semtech-2010-2902 http://purl.org/dc/elements/1.1/description This presentation will highlight a few ways to leverage Semantic Technologies in order to pave the way for the next generation healthcare systems, now being coined as Health 3.0. We will provide an overview on healthcare reform and how semantic technologies can address key strategic areas in order to decrease the overall cost of healthcare, and present an introduction into the complex world of 'healthcare informatics.' Our goal is to stimulate more dialogue and more collaboration between the semantic community and the healthcare informatics communities toward the ultimate end of reducing the cost and enhancing the overall effectiveness of our healthcare systems. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2902 http://swrc.ontoware.org/ontology#keywords health-reform
http://data.semanticuniverse.com/resource/semtech-2010-2902 http://swrc.ontoware.org/ontology#keywords health-3.0
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http://data.semanticuniverse.com/resource/harry-ellis http://xmlns.com/foaf/0.1/name Harry Ellis
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http://data.semanticuniverse.com/resource/harry-ellis http://www.w3.org/2001/vcard-rdf/3.0#title CEO
http://data.semanticuniverse.com/resource/harry-ellis http://www.w3.org/2001/vcard-rdf/3.0#org Babel-Ease Ltd.
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http://data.semanticuniverse.com/resource/semtech-2010-3309 http://purl.org/dc/elements/1.1/description It has taken a while since the first publication of "Limits to Growth", but it is now widely accepted that we are in danger of damaging the environment on which we depend for life and that this may not be such a good idea. We all need to take into account the sustainability implications of the decisions we make. Good decisions are informed decisions and so we need to get good sustainability information to purchasers when they are making their purchasing decisions. Lifecycle Assessment(LCA) is a well established and evolving discipline for estimating the environmental and more recently social impacts of the provision of a good or service. Basically it involves adding up all the resources consumed and emissions produced throughout a supply chain, attributable to the provision of a good or service and then estimating the effects of those emissions on outcomes such as resource depletion or human health. <P> This is an information rich domain where the information itself has significant value. There are a number of for fee databases of reference data that are essential to carrying out a life cycle assessment. There is also a lot of codified knowledge, such as just how much does a kilogram of methane released into the atmosphere contribute to global warming and how much methane is released in the growing of a kilogram of North American filet mignon. <P> It is a domain which is rapidly evolving. As it gets more scientific attention, our understanding of the factors which affect environmental and social impacts is deepening, and the information which is relevant to estimating these impacts keeps changing. It is also a domain in which linking is important. Perhaps an impact assessment on that kilograph of filet mignon reveals that use of a particular pesticide is having a significant negative effect on the numbers. Being able to link to a pesticide database that links pesticides to their target organisms would be useful for suggesting alternatives. <P> The Earthster project is taking a Linked information about goods and services on the web. It is developing ECO, a core domain ontology for representing LCA information. It is developing reference data using the ECO vocabulary for publishing a shared vocabulary of concept instances and codified information about them. It is developing a client application to support LCA which will publish LCA data to an LOD server and can find and consume data from such servers. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3014 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/stuart-macmillan
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http://data.semanticuniverse.com/resource/semtech-2010-3014 http://purl.org/dc/elements/1.1/abstract This session shares real-world experiences in applying semantic web informatics and community-based best practices for organizing and sharing open information vital to meeting world energy challenges.
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http://data.semanticuniverse.com/resource/semtech-2010-3014 http://www.w3.org/2000/01/rdf-schema#label The Clean Energy Commons: Using Semantic Technologies to Share the World's Energy Information
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http://data.semanticuniverse.com/resource/semtech-2010-3014 http://purl.org/dc/elements/1.1/description The Clean Energy Commons is a content sharing and collaboration community focused on accelerating our transition to clean energy systems. Open Energy Information (OpenEI) is the platform used by the community to share energy data, tools, models and knowledge. By facilitating the efficient and widespread sharing of energy-related content, we believe that OpenEI can help accelerate innovation, development and deployment of clean energy systems. In this session, we will share our experiences in designing and implementing OpenEI using standards-based semantic technologies. <P> Specific topics include: <ul> <li>Managing one of the world's largest semantic wiki instances (with over 40,000 content pages; 1,500 contributors; and 250,000 individual page edits)</li> <li>Processing large bulk data sets using distributed programming techniques such as MapReduce</li> <li>Building and managing a community with many constituencies (most having no up-front knowledge of semantic technologies)</li> <li>Supporting open government initiatives</li></ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-3014 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3014 http://purl.org/dc/elements/1.1/title The Clean Energy Commons: Using Semantic Technologies to Share the World's Energy Information
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http://data.semanticuniverse.com/resource/semtech-2010-2758 http://purl.org/dc/elements/1.1/abstract Focuses on using Boeing developed SPARQL Server Pages and SPARQLFlow technologies to create a web application, using an implementation of a RBAC and CM system as an example.
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http://data.semanticuniverse.com/resource/semtech-2010-2758 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/jeffrey-a-schmitz
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http://data.semanticuniverse.com/resource/semtech-2010-2758 http://purl.org/dc/elements/1.1/description SPARQL Server Pages and SPARQLFlow are Boeing-developed technologies that allow web applications to be built using only static HTML/Javascript, SPARQL and OWL. While last year's presentation dug down into the implementation internals of these technologies, this presentation will focus strictly on how this technology is used by web developers. As an example we will step through the implementation of a RBAC and Configuration Management system implemented as part of the Boeing IVHM Model Integration Framework to manage access control and check in/check out of (what else) OWL models. <P> The following will be highlighted: <ul> <li>Dynamic HTML Generation with SPARQL by using the SSP Tag Library, including If and Looping constructs</li> <li>Implementing complex state logic, including GUI components, using only SPARQL and OWL</li> <li>Using SPARQLFlow Language to chain together SPARQL Queries for execution, including looping and if/then/else constructs</li> <li>Possibility of auto generation of linked data tags within web 3.0 sites (if time permits)</li> <li>Implementing a "maintenance free" model navigation interface(if time permits)</li> </ul> <P>
http://data.semanticuniverse.com/resource/semtech-2010-2758 http://swrc.ontoware.org/ontology#keywords owl
http://data.semanticuniverse.com/resource/semtech-2010-2758 http://swrc.ontoware.org/ontology#keywords sparql
http://data.semanticuniverse.com/resource/semtech-2010-2758 http://purl.org/dc/elements/1.1/title Using SPARQL Server Pages
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http://data.semanticuniverse.com/resource/semtech-2010-2758 http://swrc.ontoware.org/ontology#keywords jena
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http://data.semanticuniverse.com/resource/semtech-2010-3060 http://purl.org/dc/elements/1.1/title Case Study: Using Ontologies for Opportunistic Systems Integration
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http://data.semanticuniverse.com/resource/semtech-2010-3060 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/elisa-kendall
http://data.semanticuniverse.com/resource/semtech-2010-3060 http://purl.org/dc/elements/1.1/abstract This presentation describes an environment, ontologies, and methodology supporting integration and test of large scale systems under less than ideal conditions, where candidate components must be evaluated on the fly as stand-ins for missing production elements.
http://data.semanticuniverse.com/resource/semtech-2010-3060 http://www.w3.org/2000/01/rdf-schema#label Case Study: Using Ontologies for Opportunistic Systems Integration
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http://data.semanticuniverse.com/resource/semtech-2010-3060 http://purl.org/dc/elements/1.1/audience Intermediate
http://data.semanticuniverse.com/resource/semtech-2010-3060 http://swrc.ontoware.org/ontology#keywords interoperability
http://data.semanticuniverse.com/resource/semtech-2010-3060 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-2010-3060 http://purl.org/dc/elements/1.1/description Over the past several years, SRI has led a number of key US Department of Defense programs where opportunistic systems integration is essential. Integration and test environments for large scale systems may not always have the exact resources used in production or deployment. Frequently, improvisation is necessary in order to simulate the anticipated environment. Identifying the requirements of the environment, capabilities of the available resources, and whether or not interoperability is feasible among candidates is non-trivial, time consuming, and in large, complex systems, very difficult for people to accomplish without automated support. <P> In this case study, we will introduce the problem and describe our novel approach, which leverages a combination of OWL ontologies and SWRL rules implemented in an XSB Prolog based plug-in to Protégé. We will then motivate the need for a graphical notation for ontology development, and discuss how we have used Protégé and ODM (Ontology Definition Metamodel) compliant UML tools together to address this need. We will show several of our ontologies in the UML environment, describe the utility of the diagrams from an ontology development and customer understanding perspective, and demonstrate the visualization and analysis tools to show how it all comes together to meet customer requirements. Finally, we will close with a summary of where we are on the project, lessons learned, and next steps, as well as some thoughts on generalizing this framework to other government and commercial domains. <P>
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http://data.semanticuniverse.com/resource/semtech-2010-3060 http://purl.org/dc/elements/1.1/audience Technical
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http://data.semanticuniverse.com/resource/booz-allen-hamilton-nist http://xmlns.com/foaf/0.1/name Booz Allen Hamilton / NIST
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http://data.semanticuniverse.com/resource/booz-allen-hamilton-nist http://www.w3.org/2000/01/rdf-schema#label Booz Allen Hamilton / NIST
http://data.semanticuniverse.com/resource/semtech-2010-3235 http://purl.org/dc/elements/1.1/title Enterprise Requirements for Graph Databases ? Your Best NoSQL Choices
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http://data.semanticuniverse.com/resource/semtech-2010-3235 http://purl.org/dc/elements/1.1/description Initially Semantic Web databases were primarily used for analytics. Users would dump data in their RDF database and then perform interesting analytics with rules, reasoners, and query languages like SPARQL. Nowadays enterprises are starting to consider NoSQL database options for RDF in their primary processes and they are rightfully worried about transactionality, recoverability, automatic backup, replication, automatic failover, concurrency, and more. Even more important, for many applications they need a steady stream of intermixed additions, updates, deletes and queries. In this presentation I will cover strategies to manage these issues, some discussion around NoSQL- RDF, and conclude with a proposal for measuring the dynamism of a RDF databases. <P>
http://data.semanticuniverse.com/resource/semtech-2010-3235 http://purl.org/dc/elements/1.1/abstract Enterprises are considering NoSQL database options for RDF in their primary processes. This presentations discusses strategies around NoSQL- RDF and a methodology to measure the dynamism of RDF databases.
http://data.semanticuniverse.com/resource/semtech-2010-3235 http://www.w3.org/2000/01/rdf-schema#label Enterprise Requirements for Graph Databases ? Your Best NoSQL Choices
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http://data.semanticuniverse.com/resource/semtech-2010-2979 http://swrc.ontoware.org/ontology#keywords cambridge-semantics
http://data.semanticuniverse.com/resource/semtech-2010-2979 http://swrc.ontoware.org/ontology#keywords enterprise
http://data.semanticuniverse.com/resource/semtech-2010-2979 http://www.w3.org/2000/01/rdf-schema#label Leveraging a Single Semantic Fabric to Drive Efficiencies from Accounting to Research and Everything in Between
http://data.semanticuniverse.com/resource/semtech-2010-2979 http://purl.org/dc/elements/1.1/description Today, semantic web technologies are gaining traction and are beginning to make their way into the mainstream. This discussion will cover how Biogen-Idec is actively investigating how they can bring value to their businesses. <P> Biogen-Idec, a global biopharmaceutical company, and Cambridge Semantics, a pioneer in semantic business transformations, are using semantic technology to: <ul> <li>Combine and analyze data from research partners</li> <li>Improve internal data collection for accounting and budgeting</li> <li>Build dashboards of manufacturing deviations</li> <li>Eliminate error-prone manual processes in IT maintenance schedules</li> </ul> William Hayes from Biogen-Idec will talk about these initial proofs-of-concept and future plans to allow knowledge workers to focus on higher value tasks. He will discuss the benefits and challenges Biogen-Idec sees in deploying semantic technologies. <P>
http://data.semanticuniverse.com/resource/semtech-2010-2979 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/william-hayes
http://data.semanticuniverse.com/resource/semtech-2010-2979 http://purl.org/dc/elements/1.1/abstract Innovators in Bio-pharma are applying semantic technology to solve data collection and collaboration issues in a fraction of the time that traditional technologies would allow.
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http://data.semanticuniverse.com/resource/semtech-2010-2979 http://purl.org/dc/elements/1.1/title Leveraging a Single Semantic Fabric to Drive Efficiencies from Accounting to Research and Everything in Between
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http://data.semanticuniverse.com/resource/semtech-2010-3179 http://swrc.ontoware.org/ontology#keywords linked-data
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http://data.semanticuniverse.com/resource/semtech-2010-3179 http://purl.org/dc/elements/1.1/abstract Provide an overview of the features and capabilities of Talis Platform, a SaaS product for publishing and using Linked Data. The presentation will also include some case studies of projects and clients that are currently using the Platform.
http://data.semanticuniverse.com/resource/semtech-2010-3179 http://purl.org/dc/elements/1.1/audience Non-Technical
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http://data.semanticuniverse.com/resource/semtech-2010-3179 http://purl.org/dc/elements/1.1/title The Talis Platform: A Linked Data Engine
http://data.semanticuniverse.com/resource/semtech-2010-3179 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T10:15:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
http://data.semanticuniverse.com/resource/semtech-2010-3179 http://www.w3.org/2000/01/rdf-schema#label The Talis Platform: A Linked Data Engine
http://data.semanticuniverse.com/resource/semtech-2010-3179 http://purl.org/dc/elements/1.1/audience Business
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http://data.semanticuniverse.com/resource/semtech-2010-3179 http://purl.org/dc/elements/1.1/description The Talis Platform is the first commercially available Software as a Service product supporting the publishing and consumption of Linked Data. Talis, a software company with 40 years of experience in software development, metadata management and collaborative sharing of data, has been using the Platform to power its own applications for several years. The Platform is now available for use by enterprises wishing to explore the benefits of semantic web technologies to their products. <P>
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http://data.semanticuniverse.com/resource/stuart-macmillan http://xmlns.com/foaf/0.1/depiction http://wmb.skyworld.com^^http://www.w3.org/2001/XMLSchema#anyURI
http://data.semanticuniverse.com/resource/stuart-macmillan http://www.w3.org/2001/vcard-rdf/3.0#title Chief Scientist, NREL
http://data.semanticuniverse.com/resource/stuart-macmillan http://www.w3.org/2001/vcard-rdf/3.0#org Consulting Professor Stanford University
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http://data.semanticuniverse.com/resource/semtech-2010-semantic-software-development http://www.w3.org/2000/01/rdf-schema#label Semantic Software Development
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http://data.semanticuniverse.com/resource/semtech-2010-2961 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-2010-2961 http://purl.org/dc/elements/1.1/description MIKE2.0 (Method for an Integrated Knowledge Environment) is an open source methodology for enterprise information management that is coupled with a collaborative framework for information development. It is oriented around a variety of solution "offerings", ranging from the comprehensive and the composite to specific practices and technologies. In this Face-to-Face session, experts and desirous practitioners will join together to discuss the use of MIKE2.0 for the Semantic Enterprise. <P> The Semantic Enterprise is a cross-cutting offering that touches upon virtually all aspects of the MIKE2.0 methodology and templates. These open source frameworks can be leveraged by new users to "take the best and leave the rest" while adopting the methods for their own needs and circumstances. In these discussions, all participants will learn and discover: <ul> <li>The basic structure and framework of MIKE2.0</li> <li>Its unique guidance for how to transition to a Semantic Enterprise</li> <li>The 5 phases of assessment, adoption and deployment</li> <li>Specific activities and tasks needed and useful to the Semantic Enterprise</li> <li>Supporting assets and other related resources</li> </ul> More than just dry methodology and guidelines, MIKE2.0 is an open source documentation and implementation framework that you can install in a wiki and modify locally to guide your developers and users into a Semantic Enterprise solution unique to your circumstances. Welcome! <P>
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://purl.org/dc/elements/1.1/audience Business
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://www.w3.org/2000/01/rdf-schema#label MIKE2.0 for the Semantic Enterprise
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://data.semanticweb.org/ns/swc/ontology#isPartOf http://data.semanticuniverse.com/resource/semtech-2010-enterprise-semantics
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://purl.org/dc/elements/1.1/creator http://data.semanticuniverse.com/resource/michael-k-bergman
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://swrc.ontoware.org/ontology#keywords methodology
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://swrc.ontoware.org/ontology#keywords open-seas
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://www.w3.org/2002/12/cal/icaltzd/dtStart 2010-06-24T16:45:00-07:00^^http://www.w3.org/2001/XMLSchema#dateTime
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http://data.semanticuniverse.com/resource/semtech-2010-2961 http://purl.org/dc/elements/1.1/abstract This introductory discussion will explain the basis, process and benefits of the Method for an Integrated Knowledge Environment (MIKE2.0)
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://swrc.ontoware.org/ontology#keywords adoption
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://purl.org/dc/elements/1.1/audience Non-Technical
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://swrc.ontoware.org/ontology#keywords semantic-enterprise
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://swrc.ontoware.org/ontology#keywords mike2.0
http://data.semanticuniverse.com/resource/semtech-2010-2961 http://purl.org/dc/elements/1.1/title MIKE2.0 for the Semantic Enterprise
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