An Extensible Approach for Modeling Ontologies in RDF(S)

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An Extensible Approach for Modeling Ontologies in
RDF(S)

• Steffen Staab, Michael Erdmann, Alexander
  Mädche, Stefan DeckerResearch Group Knowledge
  Management
• Institute AIFB, University of Karlsruhe,
• DB Group, Stanford UniversityLisbon,
  September 21, 2000

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What is an Ontology?

• Light-weight Ontology
• concepts, atomic types
• is-a hierarchy among concepts
• associations between concepts
• Heavy-weight Ontology
• cardinality constraints
• taxonomy of relations
• reified statements
• Axioms / semantic entailments of various tastes
• expressiveness (DL, propositional, horn, or first
  order logic, higher order)
• inferences

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Tools for Ontologies

• Light-weight
• uncontroversial
• all Tools support light-weight
• Protege, Stanford
• OntoEdit, Karlsruhe
• UML-Tools, several
• Heavy-weight
• no consensus yet
• layering seems appropriate/necessary

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Concepts, Relations, ....
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Modeling

• Ideal Modeling (WYMIWYG)
• Modeling not constrained by any language
• All appropriate epistemological primitives and
  modeling styles should be usable
• Real Modeling
• A particular language always restricts allowed
  primitives (modeling language)
• A particular language is needed in
  applications(application language)
• gt distinguish modeling language from final
  application language

translate automatically
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Axioms

• For Semantic Web and DAML more than light-weight
  is needed!
• Axioms
• Framework for conceptual modeling of axioms
• Ontology of axiom patterns
• language specific axiom-schemata can work with
  that knowledge
• Interoperability is an issue
• RDF / RDFS seem appropriate

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Axiom Patterns

• 1. Axioms for a relational algebra
• (a) Reflexivity of relations
• (b) Symmetry of relations
• (c) Asymmetry of relations
• (d) Transitivity of relations
• (e) Inverse relations
• (f) Irreflexivity of relations
• (g) Antisymmetry of relations
• 2. Composition of relations
• 3. (Exhaustive) Partitions of Concepts

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Axiom Patterns

• 4. Axioms for subrelation relationships
• 5. Axioms for part-whole reasoning Winston 87
  Chaffin 92
• PhysicalPartOf
• MemberOf
• PortionOf
• PhaseOf
• FeatureOf
• SubRegionOf
• 6. Nonmonotonicity
• 7. Axioms for temporal and modal contexts
• 8. (General axioms (application specific, ad hoc))

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Example of Composition of Relations
ltoComposition rdfID"FatherInLawComp"gt
ltocomposee rdfResource"fatherInLawOf"/gt
ltofirstComponent rdfResource"fatherOf"/gt
ltosecondComponent rdfResource"marriedWith"/gt lt/
oCompositiongt
rdfsProperty
rdfClass
oComposition
oRelation
Composition(fatherInLawOf, fatherOf, marriedWith).
oIrreflexiveRel
forall R,Q,S,X,Y,Z XR -gtgt Z lt- Composition(R,
Q, S) and XQ -gtgt Y and YS -gtgt Z.
osecondComponent
ocomposee
applmarriedWith
ofirstComponent
forall X,Y,Z XfatherInLawOf -gtgt Z
lt- XfatherOf -gtgt Y and YmarriedWith -gtgt Z.
applfatherOf
applfatherInLawOf
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OntoEdit supports Axiom Classification
fatherInLawOf
fatherOf
marriedWith
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Ontology Engineering using OntoEdit

• Interaction with the user on a conceptual level
• Multiple views for concepts, relations and axioms
• Multilinguality
• Linkable to NLP domain lexicon
• Exports ontology (incl. axioms) into several
  formats
• F-Logic (main language)
• RDF/RDFS
• DTDs (as far as possible)
• ORDB-Schema (as far as possible)
• OIL (partially and in RDF)
• UML/XMI (planned)
• the DAML language (when specified -)

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Ontoedit
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Frame-Logic Inference Engine Access
Automatically Derived from Axiom views
Pure F-Logic
Debugging Instances Rule Debugging
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FaCT DL Engine Interface

1. Generate FaCT LISP KB (future OIL)
2. Call FaCT Client, transform ontology on FaCT
   server
3. Ask server

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Flexible Epistemological Level
XRDF
OIL
DAML
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Conclusion

• No Method fits all
• Different applications need
• different representation languages
• with their underlying reasoning services
• Ontology development must be aware of this
• conceptual modeling
• mechanisms to access/integrate several ontologies
• distributed on the web
• identified by (XML-) namespaces

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Thank You!