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Semantic Annotation of Deep Web Resources

Semantic Annotation of Deep Web Resources. Eric Rozell, Tetherless World Constellation. Outline. Introduction Research Question Use Cases Approach Research Plan. Introduction. Deep-Web vs. Surface-Web Deep-web resources of interest Semantic Web Services

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Semantic Annotation of Deep Web Resources

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  1. Semantic Annotation of Deep Web Resources Eric Rozell, Tetherless World Constellation

  2. Outline • Introduction • Research Question • Use Cases • Approach • Research Plan

  3. Introduction • Deep-Web vs. Surface-Web • Deep-web resources of interest • Semantic Web Services • SPARQL Protocol and RDF Query Language

  4. Research Question • How can Semantic Web Services and SPARQL be used/extended to annotate deep-web resources?

  5. Use Cases • Web Service Composition for Scientific Applications • Ontology Modularization Alternative

  6. Web Service Composition • Current approaches focused only on semantic description of web services • e.g., OWL-S [1], METEOR-S [2], WMSO [3] • Business Applications vs. Scientific Applications

  7. Ontology Modularization • Ontology Modularization Intent: • To provide subsets of axioms that retain original meaning and reasoning properties • Ontology Modularization Approaches • Partitioning [4]: divide an ontology into many modules s.t. all entailments are retained • Extraction [5]: determine a module for a specific set of axioms that retains some set of reasoning properties

  8. Ontology Modularization Alternative • What if… • No algorithm for a modularization use case? • Can’t find tools to execute modularization? • Many ontologies are stored with knowledge base in persistent triplestore • SPARQL can be used to retrieve virtually any subset of triples • Write SPARQL queries to identify ontology modules as in [6]

  9. Approach • Develop RDFS/OWL ontology that incorporates Semantic Web Service ontologies and SPARQL constructs to identify specific collections of resources in the deep-web

  10. Research Plan • Investigate Semantic Web Service literature • Search for research on RDF-encodings of SPARQL queries/rules • Design ontology and implement prototype for indexing/searching deep-web annotations

  11. References • [1] D. Martin, M. Paolucci, S. McIlraith, M. Burstein, D. McDermott, D. McGuinness, B. Parsia, T. Payne, M. Sabou, M. Solanki, N. Srini- vasan, and K. Sycara, “Bringing semantics to web services: The OWL-S approach,” presented at the First Int. Workshop on Semantic Web Services and Web Process Composition (SWSWPC 2004), San Diego, CA, 2004. • [2] Kaarthik Sivashanmugam, John A. Miller, Amit P. Sheth, Kunal Verma. Framework for Semantic Web Process Composition. Technical Report 03-008, LSDIS Lab, Dept of Computer Science, UGA. June 2003 • [3] D. Roman, U. Keller, H. Lausen, J. de Bruijn, R. Lara, M. Stollberg, A. Polleres, C. Feier, C. Bussler, and D. Fensel. Web Service Modeling Ontology. Applied Ontology 1(1):77–106, 2005. • [4] B. C. Grau, B. Parsia, E. Sirin, and A. Kalyanpur. Modularity and Web Ontologies. In Proc. KR-2006, pages 198–209, 2006. • [5] B. C. Grau, B. Parsia, E. Sirin, and A. Kalyanpur. Automatic Partitioning of OWL Ontologies Using E-Connections. In International Workshop on Description Logics, 2005. • [6] Doran, P., Palmisano, I. and Tamma, V., SOMET: Algorithm and Tool for SPARQL Based Ontology Module Extraction, In Proceedings of the 2008 ESWCInternational Workshop on Ontologies: Reasoning and Modularity (WORM-08), Tenerife, Spain, 2008.

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