Knowledge Integration with SWRL

Martin O’ConnorStanford Center for Biomedical Informatics Research,

Stanford University

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Talk Outline

• Rules and the Semantic Web: OWL + SWRL

• Knowledge Integration–Querying–XML–Relational (and CSV/Excel)–Ontology integration

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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).

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Example SWRL Rule

Person(?p) ^ hasAge(?p,?age) ^ swrlb:greaterThan(?age,17)

→ Adult(?p)

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SWRL Semantics

• Based on OWL-DL

• Has a formal semantics

• Complements OWL and fully semantically compatible

• More expressive yet at expense of decidability

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

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Uses of SWRL for Knowledge Integration

• Ontology querying• Data integration

– XML– Relational data (and CSV/Excel)

• Ontology mapping

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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

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Example SQWRL Query

Person(?p) ^ hasAge(?p,?age) ^ swrlb:greaterThan(?age,17)

→ sqwrl:select(?p, ?age)

Return all adults in an ontology :

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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:

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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

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XML Mapping

Ontology

XML Document

Application

SWRLMappingRules

Visit_3

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<Patients> <Patient> <PID>3454-34</PID> <Age>43</Age> … <ZIP>94402</ZIP> </Patient>…<Patents>

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:

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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

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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

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DynamicDataMaster

OWLKB Bridge

Data

Knowledge

Rule Engine

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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

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Example Application

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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