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Information Flow based Ontology Mapping - 2002


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how information flow theory can be applied to enable ontology mapping

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Information Flow based Ontology Mapping - 2002

  1. 1. Yannis Kalfoglou IAM Dept. of Electronics and Computer Science University of Southampton Ontology Mapping Marco Schorlemmer CISA Division of Informatics University of Edinburgh Information Flow based ontology mapping
  2. 2. The Big Picture Local ontology Reference ontology Ontology mappings A theory and a method for Ontology mapping Information Flow based Ontology Mapping
  3. 3. <ul><li>the need for mapping ontologies: </li></ul><ul><ul><li>ontology mapping is imminent and necessary; </li></ul></ul><ul><ul><li>hence, a plethora of related work; </li></ul></ul><ul><ul><li>but still an ad-hoc process. </li></ul></ul><ul><li>a theory for ontology mapping: </li></ul><ul><ul><li>based on a mathematical theory of information flow; </li></ul></ul><ul><ul><li>applies channel-theory techniques: classifications and infomorphisms. </li></ul></ul><ul><li>a method for applying IF-Map: </li></ul><ul><ul><li>includes customised translators; </li></ul></ul><ul><ul><li>project ontology mappings in XMLified RDF; </li></ul></ul><ul><ul><li>a Test case: AKT Reference to Soton/Edin Local ontologies. </li></ul></ul><ul><li>extensions: </li></ul><ul><ul><li>evolution of ontology maps over time and across organisations; </li></ul></ul><ul><ul><li>IF-based merging. </li></ul></ul>Overview
  4. 4. <ul><li>Ontologies nowadays are: </li></ul><ul><ul><li>Originating from disparate systems often modelling the same domain; </li></ul></ul><ul><ul><li>Distributed across organisational boundaries; </li></ul></ul><ul><ul><li>Developed in a variety of knowledge representation formalisms. </li></ul></ul><ul><li>The advent of the Semantic Web boosted ontologies development: </li></ul><ul><ul><li>seen as its semantic backbone; </li></ul></ul><ul><li>That resulted in an ever growing number of ontologies which need to communicate meaning; </li></ul><ul><li>Which makes mapping imminent to ensure that a concept described in a different manner by two different ontologies has the same semantics; </li></ul><ul><li>Incidentally, early ontology use suggested that they could be used as as a means to improve interoperability of disparate systems; </li></ul><ul><li>Today, we have to worry for technologies to improve interoperability of ontologies themselves! </li></ul>Ontology mapping is needed…
  5. 5. and the community has responded… <ul><li>These challenges aren’t new: in the past 5-6 years many researchers have contributed: </li></ul><ul><ul><li>Tools: embedded in ontology editors (PROMPT/SMART, Chimeara); </li></ul></ul><ul><ul><li>Methods: ONIONS, FCA-Merge; </li></ul></ul><ul><ul><li>Translation systems (OntoMorph), portals (OntoMap), frameworks (MAFRA); </li></ul></ul><ul><ul><li>Dedicated mechanisms embedded in projects (PhysSys, SKC); </li></ul></ul><ul><ul><li>Algorithms and heuristics (OntoMediation, PROMPT/SMART, FCA-Merge); </li></ul></ul><ul><ul><li>Machine learning techniques used in Web systems (CAIMAN, GLUE); </li></ul></ul><ul><ul><li>Research literature surveys (Visser, Pinto, Uschold; </li></ul></ul><ul><ul><li>Schema integration techniques borrowed from database community; </li></ul></ul><ul><ul><li>Links with the Formal Concepts Analysis work (concept lattices, intensions and extensions of concepts) and database schema integration (Schmitt & Saake). </li></ul></ul>
  6. 6. but ontology mapping is still ad hoc… <ul><li>We observe that most approaches are </li></ul><ul><ul><li>ad hoc (systems built for another purpose, mapping as a side-effect); </li></ul></ul><ul><ul><li>translation not mapping tools; </li></ul></ul><ul><ul><li>use syntactic clues and heuristics (but no semantics); </li></ul></ul><ul><ul><li>lack a theoretical background; </li></ul></ul><ul><ul><li>embedded in ontology editors; </li></ul></ul><ul><ul><li>attached to a specific formalism (often ignore translation caveat); </li></ul></ul><ul><ul><li>manual and labour intensive (need continuous user feedback – oracle). </li></ul></ul><ul><li>The situation could be tackled with: </li></ul><ul><ul><li>A theory of what constitutes ontology mapping; </li></ul></ul><ul><ul><li>A logic representation of ontology mapping principles; </li></ul></ul><ul><ul><li>A systematic approach in ontology mapping which should be: </li></ul></ul><ul><ul><ul><li>Tool and language independent by providing translators to/from imported formats; </li></ul></ul></ul><ul><ul><ul><li>Easily implemented and deployed on the Semantic Web; </li></ul></ul></ul><ul><ul><ul><li>Being fully automatic. </li></ul></ul></ul>
  7. 7. A theory for ontology mapping… <ul><li>Based on channel theory - a mathematical theory of (semantic) information </li></ul><ul><li>local logics – regularities of components of distributed systems </li></ul><ul><li>infomorphisms – connections between components: information flow </li></ul><ul><li>Ontologies are modelled as local logics , represented as classifications: </li></ul>├─ thing thing ├─ building,car building ├─ thing vehicle ├─ thing car ├─ vehicle building,vehicle ├─ building vehicle car thing thing building vehicle car a 1 1 0 0 b 1 0 1 0 c 1 0 1 1 ontology local logic classification
  8. 8. which uses classifications and yields infomorphisms Maps of ontologies… thing building vehicle car a 1 1 0 0 b 1 0 1 0 c 1 0 1 1 … are modelled as infomorphisms ,… … and represented as classifications : entity house cottage automobile x 1 0 0 1 y 1 1 0 0 z 1 1 1 0 1 0 1 1 1 1 0 0 1 1 0 0 thing building vehicle car entity automobile cottage house a b c x y z
  9. 9. How to apply the theory… <ul><li>Number of infomorphisms grows exponentially with the number of concepts; </li></ul><ul><li>Need to kick-start and constrain the mapping process: </li></ul><ul><li>Option A: </li></ul><ul><li>look for matching relation names between local and reference ontologies; </li></ul><ul><li>traversal of concept hierarchies in order to match their argument types; </li></ul><ul><li>fix partial map of concept/relation names. </li></ul><ul><li>Option B: </li></ul><ul><li>select representative instances of local concepts; </li></ul><ul><li>classify these instances to reference concepts; </li></ul><ul><li>fix partial map of instances. </li></ul><ul><li>Need for: </li></ul><ul><li>fragmenting reference and local ontologies; </li></ul><ul><li>monotonic, incremental generation of maps of ontologies. </li></ul>
  10. 10. … a methodology <ul><li>We have built a stepwise process which consists of: </li></ul><ul><ul><li>Ontology harvesting (acquire ontologies); </li></ul></ul><ul><ul><li>Translation; </li></ul></ul><ul><ul><li>IF-Map (generating infomorphisms); </li></ul></ul><ul><ul><li>Project mapping (provide XMLified RDF output) </li></ul></ul><ul><li>Ontology acquisition includes a variety of technologies ranging from web harvesters to ontology libraries and editors; </li></ul><ul><li>Translation is customised for the purposes of IF-Map method. Currently, we translate to horn logic clauses from RDF, Protégé, Ontolingua, KIF; </li></ul><ul><li>IF-Map implements the infomorphisms generation; </li></ul><ul><li>Finally, we project mappings in XMLified RDF format which can be accessed on the Web. </li></ul>
  11. 11. the methodology diagrammatically
  12. 12. Test case: AKT Ref/Soton/Edin ontologies <ul><li>We applied IF-Map to map the AKT Refererence ( ref ) ontology to Southampton’s and Edinburgh’s ontologies ( soton and edin ): </li></ul><ul><li>Ref is encoded in OCML and Ontolingua, soton is in edited in Protégé and edin in Prolog (among other); </li></ul><ul><li>We used our translators to convert them in Prolog; </li></ul><ul><li>Soton and edin are populated with instances, ref is not; </li></ul><ul><li>We mapped fragments of ref to soton and vice versa, and fragments of ref to edin and vice versa; </li></ul><ul><li>We produce XMLified RDF output showing the generated infomorphisms for concepts and relations. </li></ul>
  13. 13. <ul><li>Example ref to soton infomorphisms: </li></ul><ul><li>ref concept document is mapped onto soton concept publication ; </li></ul><ul><li>ref concept appellation is mapped onto soton concept string ; </li></ul><ul><li>ref relation publishedby is mapped onto soton relation authoredby ; </li></ul><ul><li>ref relation hasappellation is mapped onto soton relation title </li></ul>Test case: AKT Ref/Soton/Edin ontologies
  14. 14. <ul><li>So far, we have experimented with the following mapping scenario: </li></ul><ul><ul><li>Reference mapped to/from local ontology </li></ul></ul><ul><li>We also consider trying to: </li></ul><ul><ul><li>Map a Reference ontology (e.g. AKT-Ref) to another Reference ontology (e.g., IEEE SUO); </li></ul></ul><ul><ul><li>Map local ontologies when there is no such a thing as a Reference ontology. </li></ul></ul>Mapping scenarios
  15. 15. Extensions: ontology merging IF-Merge: a method for ontology merging/alignment <ul><li>Scenario: </li></ul><ul><li>local ontologies and reference ontology(ies); </li></ul><ul><li>local ontologies “conform” to reference ontology: infomorphisms (IF-Map). </li></ul><ul><li>Ontology merging: </li></ul><ul><li>explicit computation of the global ontology ( pushout construction); </li></ul><ul><li>sharing of knowledge via the reference ontology (virtual ontology). </li></ul>
  16. 16. Extensions: ontology evolution <ul><li>IF-Merge is sensitive to the way local communities classify their instances </li></ul><ul><li>infomorphisms: map of concepts + map of instances; </li></ul><ul><li>global ontology: determined by the interconnection of infomorphisms. </li></ul><ul><li>A service of automated ontology merging/alignment based on IF-Merge </li></ul><ul><li>could, thus: </li></ul><ul><li>automatically update the ontology merging process; </li></ul><ul><li>refine global ontologies in a way that reflect how local communities </li></ul><ul><li>classify their instances when using the local ontologies; </li></ul><ul><li>capture the evolution of ontologies as they are deployed in different contexts. </li></ul>
  17. 17. <ul><li>IF-Map overcomes some of the problems faced by existing add-hoc ontology mapping efforts: </li></ul><ul><ul><li>It is purely designed for ontology mapping, merging and aligning; </li></ul></ul><ul><ul><li>It is based on a sound theoretical foundation: channel theory; </li></ul></ul><ul><ul><li>It is language and tool independent; </li></ul></ul><ul><ul><li>It uses translators to accommodate popular ontology formats and produces web accessible XMLified RDF; </li></ul></ul><ul><li>Future work in three areas: </li></ul><ul><ul><li>Theory: situating and comparing IF based approach with others (classical logic, FCA, etc.); </li></ul></ul><ul><ul><li>Methodology: exploring heuristics for kick-starting and constraining the IF-Map/Merge method; </li></ul></ul><ul><ul><li>Implementation: Moving from a prototype to a full-fledge ontology mapping/merging service deployed on the AKT Bus. </li></ul></ul>Conclusions