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Distributed Instance Retrieval over Heterogeneous Ontologies

2 nd Italian Workshop on Semantic Web Applications and Perspectives. Distributed Instance Retrieval over Heterogeneous Ontologies. Andrei Tamilin (1,2) & Luciano Serafini (1) (1) ITC-IRST (2) DIT - University of Trento. Trento, 16 December, 2005. Outline. Motivation and problem

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Distributed Instance Retrieval over Heterogeneous Ontologies

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  1. 2nd Italian Workshop on Semantic Web Applications and Perspectives Distributed Instance Retrieval over Heterogeneous Ontologies Andrei Tamilin(1,2) & Luciano Serafini(1) (1)ITC-IRST (2)DIT - University of Trento Trento, 16 December, 2005

  2. Outline • Motivation and problem • Distributed Description Logics (DDLs) with individuals • Reasoning/Querying patterns in DDLs • Instance retrieval in DDLs • Implementing

  3. Motivation: a step back Where we were: • Steady ontology proliferation • Heterogeneity is inevitable Problem: • How to interoperate? Requirements: • Semantic mappings • Reasoning support Solution: • Distributed Description Logics • Distributed tableaux • DRAGO reasoning system

  4. Motivation: a step forth Where we are: • Ontologies are populated • Populations can be done in heterogeneous domains Problem: • How to query such a system?

  5. Classes, Relations, Axioms PersonContact PersonContact Instances A toy example ODIT OUniTn ? Retrieve all personal contacts andrei.tamilin@unitn.it http://dit.unitn.it/~tamilin • In case of which semantic correspondences • the query propagation should occur? • How the individuals should be transformed? andrei.tamilin@dit.unitn.it tamilin@itc.it …

  6. Requirements / Our proposals Requirements / Our proposals • Formal framework reflecting conceptual and individual heterogeneity • Extend Distributed Description Logics with individuals • Define a suitable query answering procedure • Extend Distributed tableau algorithm • Implement the querying procedure • Extend DRAGO reasoning system

  7. DDLs in a nutshell • Captures the case of multiple ontologies pairwise linked by semantic mappings • Ontologies correspond to DL knowledge bases • Mappings correspond to bridge rules

  8. i:X j:Y (onto-bridge rule) i:X j:Y (into-bridge rule) DDLs syntax • DDL is a family of description logics {DLi}iI • A bridge rule from i to j is an expression of the form: where X and Y are concepts of DLi and DLj. • A distributed T-box (DTB) is a pair {Ti}iI, {Bij}ijI where Bij is a collection of bridge rules from i to j

  9. i:x j:y (individual correspondence) DDLs syntax with individuals • An individual correspondence from i to j is an expression of the form: • where x and y are individuals of Ai and Aj. • A distributed A-box (DAB) is a pair {Ai}iI, {Cij}ijI where Cij is a collection of individual correspondences from i to j • A distributed knowledge base (DKB) is a pair DTB, DAB

  10. DLi DLj Terminologies (T-boxes) Bij Assertions (A-boxes) Cij Domains rij DDLs semantics {DLi}iI + {Bij}ijI {Ti}iI DTB= {Ti}iI, {Bij}ijI  {Ai}iI + {Cij}ijI DTA= {Ai}iI, {Cij}ijI  {Ji}iI + {rij}ijI DI= {Ji}iI, {rij}ijI 

  11. i:X j:Y Into-bridge rule DI rij(xIi)  YIj Ij Ii Y X rij(X) rij

  12. i:X j:Y Onto-bridge rule DI rij(XIi)  YIj rij(X) Ij Ii X rij Y

  13. i:x j:y Individual correspondence DI xIi,yIj rij Ij Ii rij y x

  14. isA DTB Terminological propagation DTB= T1, T2, B12 T1 T2 A G isA H B GI2r12(AI1)  r12(BI1) HI2

  15. DKB Assertion propagation DKB= T1,A1,T2,A2, B12,C12 T1 T2 B H isInstanceOf isInstanceOf A1 A2 b h hI2=r12(bI1)  r12(BI1) HI2

  16. DKB Assertion propagation - II DKB= T1,A1,T2,A2, B12,C12 T1 T2 B H isInstanceOf isInstanceOf fij A1 A2 fij(b) b

  17. Distributed instance retrieval • Instance retrieval: finding all individuals that instantiate a given concept • Both propagation aspects should be taken into account

  18. D1 Local taxonomy D3 D2 Local individuals i2 i1 i3 Retrieve instances of D1 i1, i2

  19. Bridge rules Distributed taxonomy (terminological propagation matters) D1 D3 D2 Local individuals i2 i1 i3 Retrieve instances of D1 i1, i2, i3

  20. Bridge rules Distributed taxonomy (terminological propagation matters) D1 D3 D2 Individual correspondences Local individuals i2 i1 i3 Distributed individuals (transformed via individual correspondences) i’2 Retrieve instances of D1 i1, i2, i3, i’2

  21. Implementation • On top of DRAGO distributed terminological reasoner • DRAGO is a peer-to-peer network of communicating reasoners that handle OWL ontologies coupled with C-OWL mappings • For the instance retrieval the possibility to specify instance transformations has been added

  22. Conclusions and Outlook • We addressed the problem of retrieving individuals over heterogeneous ontologies which are instantiated in semantically related domains • We extended DDLs framework with individual correspondences and discussed how this enables the propagation of assertions over ontologies • Implemented a simple querying prototype on top of DRAGO reasoner

  23. Thank you

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