1. Towards a Standard for Heterogeneous Ontology Integration and Interoperability Oliver Kutz & Christoph Lange Research Center on Spatial Cognition (SFB/TR 8), University of Bremen, Germany & Jacobs University Bremen, Germany Joint work with Till Mossakowski (DFKI)- Christian Galinski (Infoterm) Seoul, South Korea - LaRC, June 2011

2. Ontology Interoperability Critical issues are Semantic Heterogeneity Syntactic Heterogeneity Plurality of structuring & modularity concepts Plurality of documentation techniques Plurality of tools, editors, reasoners, etc. Plurality of (kinds of) services, devices, etc.

3. Overview Motivating Examples for the use of the hyperontology framework Structured Ontology Design Matching in networks of ontologies Relations between ontologies: Refinements, Blending, etc. Universal logic addresses (onto)-logical pluralism and semantic heterogeneity Hyperontologies = structured and heterogeneous (networks of) ontologies A Sketch of a future standard: DOL: Distributed Ontology Language

4. Structured Ontologies Dolce’s structuringin CASL, showing the import structure, i.e. the modular re-use

5. Matching Across Repositories Ontology Repositories, e.g. BioPortal, Orate, Colore, Tones: collections of ontologies for different purposes and in various ontology languages. create new ones out of existing ones by finding synonyms, extracting modules, and merging them together. Meaning shift and “chinese whispers”. problem of heterogeneity & scalability problem of “information overflow”

6. Heterogeneous Refinement of Dolce Different version of Dolce are available, e.g. in DL and FOL: What is their logical relationship? Core Projection Approximation heterogeneous refinement definitional extension connection through bridge theory P(x) Q(x,y) P(x) Q(x,y) R(x) R(x,t) R(x,t) ∼ R(x) (forget temporal dimension) S(x,y,z) U(x,y) V(z)... Dolce-LITE Dolce-FOL

7. Ontological Blending Selectively combining two ontologies whilst preserving common structure (theory). Motivation: Conceptual Blending and metaphor: House + Boat = Houseboat Boat + House = Boatshouse

8. Pluralism in Ontologies NCI Thesaurus about 34.000 concepts arranged in 20 taxonomic trees, reference terminology for cancer research, sub-Boolean description logic EL. Galen medical domain ontology, relatively large, but also relatively complex axiomatisation in a more expressive DL, namely OWL-DL. Dolce, BFO, GUM, GFO Foundational ontologies, first-order, higher-order, first-order modal logic being used. Complex axiomatisations.

9. Universal Logic Signatures: (non-logical symbols) propositions; predicates; functions, constants, terms. Grammar: (logical symbols) variables and quantifiers; modalities; identity symbol; substitution. Models: possible world; domains of discourse; accessibility (counterpart relations) ; object (individual) Satisfaction: vary the truth conditions for quantifiers; Booleans; Modalities; vary conditions for identity statements, etc. Items that can be varied according to universal logic: Benefits: Borrowing and combination of logics and reasoners, structuring, etc.

10. Heterogeneous Ontologies In order to systematically link and combine ontological modules formulated in different formalisms we need to: fix a logic graph give logic translations (institution co-morphisms)

11. Onto-Logical Translation Graph

12. Hyperontology example Heterogeneous specification of Mereology A hyperontology is a heterogeneously interlinked network of heterogeneous ontology modules.

13. Hyperontologies via Matching 5 participating ontologies, all connected via matchings. matching results in a single synset identifying all matched concepts, and inconsistency. removal of the Graphics ontology can cut synset into 2 distinct ones, can restore consistency. following more than one orange arrow means playing chinese whispers. O1O1 O3O3 O2O2 O4O4 O5O5

14. The Problem of Module Extraction JRAO is constructed using fragments of NCI and Galen NCI, Galen are too large to be imported completely Import only interesting ‘modules’ Conservativity:Ensu re that the ‘module’ is large enough to cover all relevant information (coverage)Ensure that no new information is added (safety)Add only relevant axioms (minimality)

15. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

16. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

17. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

18. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

19. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

20. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

21. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

22. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit

23. Workflow & Tool Interoperability Ontology Repository Hyperontology Graph select matching configuration Matching Configuration Falcon Hets Pellet Alignment Specificatio n produce formal specification Modules Merged Ontology consistenc y check User yes no extract modules match pairwise compute colimit + O

24. Hets - The Heterogeneous Tool Set structured representations (such as V-alignments), reuse/independent development of modules library of logics/formalisms supported, incl. OWL-DL various provers connected: incl. for OWL-DL, first- order, higher-order, model checker, etc computation of colimits checking for conservativities

25. DOL - Distributed Ontology Language general purpose framework for ontology interoperabilitylibrary of logics/formalisms supported, incl. most ontology languages well-defined formal semanticspairs of languages have common target ontology languageApplication T(O) of translation to ontology part of DOL syntax DIF: XML- and RDF-based interchange formats Mapping two ontology languages into a third

26. DOL - Distributed Ontology Language Mapping two ontology languages into a third support for various module languages as well as one universal lingua francaexplicit module extractioninternalise ontology mappings (first class citizens)make ontology translations available in the language distributed ontologies in terms of both different internet locations and different ontology languages.

27. Embedded Ontology Documentation … but also for human users of an ontology (make ontologies comprehensible) Knowledge Engineers and Service Developers – reuse! End Users – when services expose ontology documentation (“labels” and more) as online help Ontological Structuring and Modularity is not only for machines …

28. Documentation State of the Art SKOS (Simple Knowledge Organization System): an OWL ontology with some non-OWL axioms “documented” in HTML manual, and unstructured source comments

29. Language Documentation Support

30. Documentation Features Unsupported so far Informal subsets of an ontology (not yet explicitly modularized) Subterms of complex axioms Literate Programming: natural language and formal expressions freely interwoven ⇒ generate ontology and manual from same source

31. Documentation in DOL Use existing annotation facilities where possible In non-XML ontology languages, can't embed documentation ⇒ “special” comments, or external, non-intrusive RDF standoff markup Reuse existing documentation vocabularies (e.g. OMV = Ontology Metadata Vocabulary) How to identify subjects? E.g. “the first three axioms”? How to do that in text-oriented ontology languages? – Use XPointer!

32. Conclusions Ontologies are widely used to enable interoperability Currently no unified framework for ontology interoperability. Apply the state of the art in modularity, structuring and documentation, as developed e.g. in software engineering Enable synchronisation and orchestration of interoperable services OntoIOp (Ontology Integration and Interoperability) is being proposed in ISO/TC 37/SC 3 in order to fill this gap.