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A Context Information Service using Ontology-Based Queries

Ruaidhr í Power, Dave Lewis, Declan O’Sullivan, Owen Conlan, Vincent Wade Knowledge and Data Engineering Group Department of Computer Science, Trinity College Dublin. A Context Information Service using Ontology-Based Queries. Context Information Service.

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A Context Information Service using Ontology-Based Queries

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  1. Ruaidhrí Power, Dave Lewis, Declan O’Sullivan, Owen Conlan, Vincent Wade Knowledge and Data Engineering GroupDepartment of Computer Science, Trinity College Dublin A Context Information Service using Ontology-Based Queries

  2. Context Information Service • This paper describes the design of a context information service that serves ontology-based context queries • Motivation • Architecture • Query Interface • Query Routing • Scalability

  3. Architecture Motivation • Current approaches advocate predefined, agreed models for context information • Context information cannot be globally standardized • Cannot be certain what information is relevant before constructing the system • Need capability to update models • Must cope well with heterogeneous systems • Translate queries (and responses) into terms in each system’s own ontology

  4. Context Self-Management • Context will be managed by each user’s own systems, rather than centrally • Global view of all context impossible • Privacy and security concerns • Interoperability between heterogeneous context sources • External context information will be merged into each user’s own view of the world, through the use of ontologies

  5. Context Service Node • A Context Service Node (CSN) receives context queries and resolves them by acting as mediator to other context services • Translate query responses into terms in each application’s own ontology • Also accepts registration of ontologies and mappings between ontologies • Ontologies and mappings can be provided separately, and updated as needed

  6. Context Querying • CSN query interface • SQL, XQuery, RDQL, ... • Application poses queries using terms from its own registered ontologies • CSN communicates with other CSNs over the network to resolve query • Query translation and routing are based on ontological information available

  7. Context Service Network Architecture Context Service CSN Network Query(Q1,O1) Resp(R ) Reg(O1,O2) Application seeking context

  8. Context Service Network Architecture MapReq(O1) Ontology Context mapping Service CSN respository Network Map (O1,O3) Query(Q1,O1) Resp(R ) Reg(O1,O2) Application seeking context

  9. Context Service Network Architecture CSN CSN CSN CSN MapReq(O1) Ontology Context mapping Service CSN respository Network Map (O1,O3) Query(Q1,O1) Resp(R ) Reg(O1,O2) Application seeking context

  10. Context Service Network Architecture Context Context info info source source Reg(O3) Resp(O3) Query(Q1,O3) CSN CSN CSN CSN MapReq(O1) Ontology Context mapping Service CSN respository Network Map (O1,O3) Query(Q1,O1) Resp(R ) Reg(O1,O2) Application seeking context

  11. Routing Strategies • Broadcast inefficient except in small networks • Must route queries to nodes that understand them • What if a large number of CSNs understand a query? • Trade off number of nodes vs. processing cost

  12. Content-Based Networking (CBN) • Messages routed based on their content • Content-based routers route messages using function which describes which messages their neighbours are interested in • Persistent ontology-based queries (pub/sub) • CBN systems have shown promising scalability

  13. Conclusion • Domain knowledge of applications encapsulated in an ontology • Ontologies used as the basis for interoperability • System integration performed using mappings, as a separate activity • Intelligent pub/sub (CBN) for query routing • OWL as ontology language, XQuery as query language

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