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Opportunistic Reasoning for the Semantic Web: Adapting Reasoning to the Environment

Opportunistic Reasoning for the Semantic Web: Adapting Reasoning to the Environment. Carlos Pedrinaci Tim Smithers and Amaia Bernaras. The Semantic Web. After 10 years research on the Semantic Web has already produced a considerable amount of technologies. IRS. OWL. WSMX. DBin. OWL-S.

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Opportunistic Reasoning for the Semantic Web: Adapting Reasoning to the Environment

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  1. Opportunistic Reasoning for the Semantic Web:Adapting Reasoning to the Environment Carlos Pedrinaci Tim Smithers and Amaia Bernaras

  2. The Semantic Web • After 10 years research on the Semantic Web has already produced a considerable amount of technologies IRS OWL WSMX DBin OWL-S Jena Flink eMerges KAON Aqualog Kowari YARS Pellet WSMO RDF Sesame

  3. So Far, So Good But… • The main focus is essentially on the development of tools that generate data represented in Semantic Web languages • Applications are mainly limited to query engines and information aggregation

  4. So Far, So Good But… • Where is the killer application? • Which are the distinguishing features with respect to Web 2.0? • Why are companies somehow reluctant to embracing the Semantic Web? • Indeed, the difficulties are not just technical but we need to get these right!

  5. Some Technical Issues • Scalability • The Web is huge (and is growing) • Reasoning is expensive • Need for further expressivity which makes things worse • Knowledge Engineering is particularly challenging

  6. Some Technical Issues • Completeness • Not possible within such a dynamic environment • We need to reason in an opportunistic and incremental manner • Consistency & Correctness • Not realistic for the Web • We need non-monotonic reasoning and truth-maintenance mechanisms

  7. Some Technical Issues • The Web is essentially dynamic • The previous problems just get worse • Worst of all, a Semantic Web application should deal with all these issues, plus the typical Engineering challenges!

  8. Let’s Shift the Focus! • Let’s view the Semantic Web as a phenomenon emerging from the interaction of intelligent applications over the Web and not as an entity in itself • In this scenario Scalability, Expressivity, Completeness, Consistency, Trustworthyness more manageable issues

  9. Opportunistic Reasoning “Ability of a system to exploit its best data and most promising methods” Erman et al. 1988

  10. Blackboard Model

  11. Blackboard Characteristics • “Divide and conquer” - Problem-solving expertise partitioning • Simplifies Knowledge Modelling • Promotes reuse • Applicability of diverse representation and reasoning techniques • Collaborative and concurrent reasoning • Event-based reasoning

  12. Blackboard Applicability Criteria • A large solution space • Noisy or unreliable problem data • A continuous data flow • The need to integrate diverse and heterogeneous data • The need to integrate different sources of knowledge

  13. Blackboard Applicability Criteria • The need to apply several reasoning methods • The need to develop various lines of reasoning • The need for incremental reasoning • The need for an opportunistic control of the reasoning process

  14. Blackboard Applicability Criteria • The need for an event-based activation of the reasoning • High complexity of the task • The need for a mixed initiative where computer and users can interchangeably take the initiative • Meta-reasoning or conscious reasoning • Drive & Explain the reasoning process

  15. General Applicability

  16. General Applicability

  17. General Applicability

  18. General Applicability

  19. Applicability to the Web • Particularly well-suited for the Web • Opportunistic Reasoning • Adapted to the dynamism of the Web • Flexible and versatile • Wide applicability, seamless integration of diverse reasoning engines, languages, and tools • Modular • Maintainable, extensible • Distributable • Computation distribution • Adapted to the Web (Ontologies, URIs, Web Services)

  20. An Infrastructure…

  21. Several Applications… Web-based Events Design Support System Music Rights Clearing Organization

  22. Conclusion • Considering the Semantic Web as an emerging phenomenon has important pragmatic consequences • Opportunistic Reasoning seems particularly appropriate for reasoning over the Web • Appealing characteristics from an Engineering perspective that make it a good candidate for supporting Semantic Web applications

  23. Thanks Thank you for your attention

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