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Knowledge Integration with SWRL Martin OConnor Stanford Center for Biomedical Informatics Research, Stanford University.

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Presentation on theme: "Knowledge Integration with SWRL Martin OConnor Stanford Center for Biomedical Informatics Research, Stanford University."— Presentation transcript:

1 Knowledge Integration with SWRL Martin OConnor Stanford Center for Biomedical Informatics Research, Stanford University

2 2 Talk Outline Rules and the Semantic Web: OWL + SWRL Knowledge Integration –Querying –XML –Relational (and CSV/Excel) –Ontology integration

3 3 What is SWRL? SWRL is an acronym for Semantic Web Rule Language. SWRL is intended to be the rule language of the Semantic Web. SWRL includes a high-level abstract syntax for Horn-like rules. All rules are expressed in terms of OWL concepts (classes, properties, individuals).

4 4 Example SWRL Rule Person(?p) ^ hasAge(?p,?age) ^ swrlb:greaterThan(?age,17) Adult(?p)

5 5 SWRL Semantics Based on OWL-DL Has a formal semantics Complements OWL and fully semantically compatible More expressive yet at expense of decidability

6 6 SWRLTab: http://protege.cim3.net/cgi-bin/wiki.pl?SWRLTab

7 7 Uses of SWRL for Knowledge Integration Ontology querying Data integration –XML –Relational data (and CSV/Excel) Ontology mapping

8 8 SWRL and Querying: SQWRL SWRL is a rule language, not a query language However, a rule antecedent can be viewed as a pattern matching specification, i.e., a query With built-ins, language compliant query extensions are possible. We have developed a SWRL-based query language called SQWRL

9 9 Example SQWRL Query Person(?p) ^ hasAge(?p,?age) ^ swrlb:greaterThan(?age,17) sqwrl:select(?p, ?age) Return all adults in an ontology :

10 10 Another SQWRL Query Person(?p) ^ hasAge(?p, ?age) ^ swrlb:greaterThan(?age, 17) -> sqwrl:select(?p) ^ sqwrl:orderBy(?age) Return all adults in an ontology ordered by age:

11 11 Use of SWRL as basis for Query Language is Attractive Cleaner semantics than SPARQL OWL-based, not RDF-based Very extensible via built-ins, e.g., temporal queries using temporal built-ins

12 12 XML Mapping Ontology XML Document Application SWRL Mapping Rules Visit_3

13 13 3454-34 43 … 94402 … XML Querying swrlxml:XMLElement(?ep) ^ swrlxml:hasName(?ep,Patent) ^ swrlxml:hasSubElement(?ep,?eAge) ^ swrlxml:hasName(?eAge,Age) ^ swrlxml:hasContent(?eAge,?cAge) ^ swrlxml:convert(?age, ?cAge, xs:Integer) ^ swrlxml:hasSubElement(?ep,?eZIP) ^ swrlxml:hasName(?eZIP,ZIP) ^ swrlxml:hasContent(?eZIP, ?ZIP) -> sqwrl:select(?ZIP) ^ sqwrl:avg(?age) Return the average age of patients per ZIP code:

14 14 Relational Mapping DataMaster: –Imports schema or content of relational databases into Protégé-OWL –Uses JDBC/ODBC so supports: MySQL, SQL Server, Oracle etc. –Also supports Excel files. Dynamic DataMaster: supports dynamic SWRL/SQWRL-driven relational importation

15 15

16 16 Dynamic DataMaster Can query data imported by DataMaster Dynamic querying also supported via DDM One-the-fly querying of relational data Mapping ontology specifies link

17 17 DynamicDataMaster OWL KB Bridge Data Knowledge Rule Engine

18 18 Ontology Mapping for Integration SWRL rules are very good at traversing trees Complex mappings between multiple ontologies convenient in SWRL Knowledge-level mappings to merge or integrate ontologies

19 19 Example Application

20 20 Software Availability Free, open source; download at: protégé.stanford.edu SWRLTab, Datamaster: v3.3.1 SQWRL, XML querying: v3.4 beta Dynamic relational querying: 2-3 months Extensive documentation: http://protege.cim3.net/cgi-bin/wiki.pl?SWRLTab


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