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Semantic Web Applications

Semantic Web Applications. Graham Klyne Nine by Nine http://www.ninebynine.net/ 26 February 2004. Nine by Nine Who am I?. Scientific, engineering and networked software systems architecture Motion capture, mechanism design, IP address translation, MIMEsweeper Internet and Web standards

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Semantic Web Applications

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  1. Semantic Web Applications Graham Klyne Nine by Nine http://www.ninebynine.net/ 26 February 2004

  2. Nine by NineWho am I? • Scientific, engineering and networked software systems architecture • Motion capture, mechanism design, IP address translation, MIMEsweeper • Internet and Web standards • Internet fax, email, instant messaging, content negotiation • Most recently, Semantic Web (RDF) • I believe this technology is set to have a big impact on computer application development Semantic Web Applications

  3. Data – Knowledge – Meaning Deep philosophical territory: not going here Meaning? Knowledge Data Physical In the limited sense of KR semantics RDF Applications structure character raw XML Unicode Bits, Octets Semantic Web Applications

  4. Open Building BlocksStanding on the shoulders of giants • Much recent progress in Internet software is built upon open standards and open building blocks • Open infrastructure is not hostage to proprietary systems vendors • There's a freedom about the Internet: As long as we accept the rules of sending packets around, we can send packets containing anything to anywhere.- Tim Berners-Lee • Semantic Web technology follows this pattern . . . SOAP XML HTML HTTP MIME SMTP TCP/IP . PHP MySQL Apache Perl libwww Linux Sendmail BSD Semantic Web Applications

  5. Evolving Use of Information • Consider computer applications that should be sharing common information • Typically, data is not readily shared • Data must be re-entered or converted, which is expensive and error-prone Semantic Web Applications

  6. Example • Employee information distributed across disparate IT systems Employees Payees HR Finance Users Security Semantic Web Applications

  7. Collect, Process, Extract Semantic Web TechnologiesProposed benefits • Re-use information designs • Use open building blocks to process common information • Integrate data sources: new uses for existing data Semantic Web Applications

  8. The Semantic WebEvolving the Web • Evolution of the Web to a network of application-usable information • open standards from W3C • open software from many sources • An open-ended framework for combining and exploiting information from a wide range of sources Semantic Web Applications

  9. Semantic Web Building Blocks • Resource Description Framework (RDF) • An XML-based standard knowledge representation format for exchanging arbitrary information • Web Ontology Language (OWL) • A standard for describing classes of objects and enabling inference • RDF Query, RDF Rules, Access, and more • Pre-standardization, software components Semantic Web Applications

  10. (Detour: example data) • Example from network configuration, describes features of a user and a computer system • RDF/XML (link) • Notation 3 (link) • Graph (link:PNG) Semantic Web Applications

  11. What kinds of application? • Diverse, semi-structured information • Open-ended: evolving functions and data • Examples: • Personal information management (Chandler) • Social networking (FOAF) • Information syndication (RSS,PRISM) • Library/museum data (Dublin Core, Harmony) • Network security and configuration (SWAD-E) Semantic Web Applications

  12. Generic software functions RDF Aggregation, Inference, Query Results RDF Input data What can be Achieved? • Integration of diverse data sources • Focus on information needs • Generate new knowledge Semantic Web Applications

  13. Aggregation + Inference = New Knowledge • Building on the success of XML • Common syntactic framework for data representation, supporting use of common tools • But, lacking semantics, provides no basis for automatic aggregation of diverse sources • RDF: a semantic framework • Automatic aggregation (graph merging) • Inference from aggregated data sources generates new knowledge • Domain knowledge from ontologies and inference rules Semantic Web Applications

  14. Aggregation + Inference: Example • Consider three datasets, describing: • vehicles’ passenger capacities • the capacity of some roads • the effect of policy options on vehicle usage • Aggregation and inference may yield: • passenger transportation capacity of a given road in response to various policy options • using existing open software building blocks • [Example (link:TBD)] Semantic Web Applications

  15. What needs to be done? • Information design • Data-use strategies and inference rules • Mechanisms for acquisition of existing data sources • Mechanisms for presentation or utilization of the resulting information Semantic Web Applications

  16. Benefits • Greater use of off-the-shelf software • reduced development cost and risk • Re-use of information designs • reduced application design costs; better information sharing between applications • Flexibility • systems can adapt as requirements evolve • Open access to information making possible new applications Semantic Web Applications

  17. Recommendation:Low risk approach • Focus on information requirements • this is unlikely to be wasted effort • Start with a limited goal, progress by steps • adapting to evolving requirements is an advantage of SW technology; if it can do this for large projects it certainly must be able to do so for early experimental projects • Use existing open building blocks Semantic Web Applications

  18. Proposed evaluation steps • Decide if this can help your application • Identify a well-defined, constrained sub-goal • Design an initial information model • Prototype data and inference rules • Explore some variations • Develop simple mechanisms to present existing data as RDF • Start with a simple sub-problem, scoped to just a few days work Semantic Web Applications

  19. Where are we now? • Semantic Web is new technology • about 10 years after the original WWW • Many applications are experimental • The goals may be inevitable... • Applications working together with users’ information, not owning it • drawing background knowledge from the Web • less dependence on hand-coded bespoke software • … but the particular technology is not Semantic Web Applications

  20. Conclusion:Semantic Web Technology Today • World Wide Web incremental advance • Evolvable approach to information • Leverages open software building blocks • Builds on diversity • creating new knowledge • enabling new applications • Low-risk adoption strategy • by incremental, re-usable steps Semantic Web Applications

  21. End • Contact information: • info@ninebynine.net • http://www.ninebynine.net/ • References: • http://www.ninebynine.net/Papers/SemanticWebApplications.ppt ~.pdf • http://www.w3.org/2001/sw/ • http://www.scientificamerican.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21&catID=2 • http://www.w3.org/rdf Semantic Web Applications

  22. Nine by NineWhat can we offer? • We have participated actively in development of RDF core standard • Developed open source software for inference and proof-checking in RDF data • Design RDF applications • including CC/PP, a W3C recommendation • Offer help with Semantic Web information design and technology evaluation Semantic Web Applications

  23. Data - Information - Knowledge Semantic Web Applications

  24. End ? Semantic Web Applications

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