Ontology alignment representation

Slideshow Transcript

1. Slide 1: Ontology Alignment Representation Fran¸ois Scharffe c Semantic Technology Institute (STI) University of Innsbruck, Austria April 14, 2008 Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 1 / 34
2. Slide 2: Outline Introduction Ontology mediation Example Actual limitations of the approach Three levels of knowledge abstraction SPARQL for instance transformation The Alignment Format and Ontology Correspondence Patterns Patterns Pattern template Pattern library Database mapping to ontologies patterns Conclusion Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 2 / 34
3. Slide 3: Introduction Ontology mediation Situation Many ontologies overlap Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 3 / 34
4. Slide 4: Introduction Ontology mediation Situation Many ontologies overlap Need to exchange data between applications/services/agents Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 3 / 34
5. Slide 5: Introduction Ontology mediation Situation Many ontologies overlap Need to exchange data between applications/services/agents Ontology mediation is the set of techniques making this data exchange possible Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 3 / 34
6. Slide 6: Introduction Ontology mediation Two phases ontology mediation Two phases can be distiguished in ontology mediation: Constructing an alignment (matching, graphical tool). Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 4 / 34
7. Slide 7: Introduction Ontology mediation Two phases ontology mediation Two phases can be distiguished in ontology mediation: Constructing an alignment (matching, graphical tool). Processing the alignment for a mediation task (data translation, ontology merging, query rewriting) Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 4 / 34
8. Slide 8: Introduction Ontology mediation Ontology Alignment Definition (Alignment, correspondence) Given two ontologies o and o , an alignment between o and o is a set of correspondences (i.e., 4-uples): e, e , r , n with e ∈ o and e ∈ o being the two matched entities, r being a relationship holding between e and e , and n expressing the level of confidence [0..1] in this correspondence. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 5 / 34
9. Slide 9: Introduction Example Example 1: wines from Bordeaux A BordeauxWine is a wine produced in the Bordeaux region. Class wine:BordeauxWine vin:Vin http://.../Château-Marguaux http://.../Château-Margaux Correspondence vin:terroir vin:terroir Attribute value geo:Location geo:Bordelais restriction Attribute value restriction pattern Figure: Bordeaux wines Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 6 / 34
10. Slide 10: Actual limitations of the approach Problem while many matching algorithms, many graphical tools are out there, there is not something such as a common format that would allow to exchange alignments they output. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 7 / 34
11. Slide 11: Actual limitations of the approach Problem while many matching algorithms, many graphical tools are out there, there is not something such as a common format that would allow to exchange alignments they output. while the correspondence such as the one in the precedent example occurs frequently, no algorithm is able to automatically detect it. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 7 / 34
12. Slide 12: Actual limitations of the approach Problem while many matching algorithms, many graphical tools are out there, there is not something such as a common format that would allow to exchange alignments they output. while the correspondence such as the one in the precedent example occurs frequently, no algorithm is able to automatically detect it. We cope with these issues in the following way Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 7 / 34
13. Slide 13: Actual limitations of the approach Problem while many matching algorithms, many graphical tools are out there, there is not something such as a common format that would allow to exchange alignments they output. while the correspondence such as the one in the precedent example occurs frequently, no algorithm is able to automatically detect it. We cope with these issues in the following way We provide an alignment representation formalism allowing exchange of alignments through their lifecycle Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 7 / 34
14. Slide 14: Actual limitations of the approach Problem while many matching algorithms, many graphical tools are out there, there is not something such as a common format that would allow to exchange alignments they output. while the correspondence such as the one in the precedent example occurs frequently, no algorithm is able to automatically detect it. We cope with these issues in the following way We provide an alignment representation formalism allowing exchange of alignments through their lifecycle We formalize aspects of recurring correspondences and extract patterns that will provide support for constructing alignments. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 7 / 34
15. Slide 15: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation We implement this framework on the three levels. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
16. Slide 16: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation at the ground level: mediation rules or grounded correspondences (expressed in OWL, COWL, SWRL, WSML variants, SPARQL++, etc.). We implement this framework on the three levels. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
17. Slide 17: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation at the ground level: mediation rules or grounded correspondences (expressed in OWL, COWL, SWRL, WSML variants, SPARQL++, etc.). at the intermediate level: alignment (expressed in a particular rule or object model of a tool/algorithm) We implement this framework on the three levels. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
18. Slide 18: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation at the ground level: mediation rules or grounded correspondences (expressed in OWL, COWL, SWRL, WSML variants, SPARQL++, etc.). at the intermediate level: alignment (expressed in a particular rule or object model of a tool/algorithm) at the top level of abstraction: correspondence patterns (new concept) We implement this framework on the three levels. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
19. Slide 19: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation at the ground level: mediation rules or grounded correspondences (expressed in OWL, COWL, SWRL, WSML variants, SPARQL++, etc.). at the intermediate level: alignment (expressed in a particular rule or object model of a tool/algorithm) at the top level of abstraction: correspondence patterns (new concept) We implement this framework on the three levels. at the ground level: a SPARQL extension for data transformation Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
20. Slide 20: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation at the ground level: mediation rules or grounded correspondences (expressed in OWL, COWL, SWRL, WSML variants, SPARQL++, etc.). at the intermediate level: alignment (expressed in a particular rule or object model of a tool/algorithm) at the top level of abstraction: correspondence patterns (new concept) We implement this framework on the three levels. at the ground level: a SPARQL extension for data transformation at the intermediate level: the Alignment format and the Alignment Ontology Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
21. Slide 21: Three levels of knowledge abstraction three levels of abstraction for ontology alignment representation at the ground level: mediation rules or grounded correspondences (expressed in OWL, COWL, SWRL, WSML variants, SPARQL++, etc.). at the intermediate level: alignment (expressed in a particular rule or object model of a tool/algorithm) at the top level of abstraction: correspondence patterns (new concept) We implement this framework on the three levels. at the ground level: a SPARQL extension for data transformation at the intermediate level: the Alignment format and the Alignment Ontology at the top level: a library of recurring correspondence patterns Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 8 / 34
22. Slide 22: Three levels of knowledge abstraction SPARQL for instance transformation SPARQL++ for instance transformation We propose to use SPARQL as a convenient data translation language for RDF. it allows to query data Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 9 / 34
23. Slide 23: Three levels of knowledge abstraction SPARQL for instance transformation SPARQL++ for instance transformation We propose to use SPARQL as a convenient data translation language for RDF. it allows to query data its CONSTRUCT statement allows to translate graphs fragments Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 9 / 34
24. Slide 24: Three levels of knowledge abstraction SPARQL for instance transformation SPARQL++ for instance transformation We propose to use SPARQL as a convenient data translation language for RDF. it allows to query data its CONSTRUCT statement allows to translate graphs fragments It’s a W3C recommendation and is already supported by numerous tools Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 9 / 34
25. Slide 25: Three levels of knowledge abstraction SPARQL for instance transformation SPARQL++ for instance transformation We propose to use SPARQL as a convenient data translation language for RDF. it allows to query data its CONSTRUCT statement allows to translate graphs fragments It’s a W3C recommendation and is already supported by numerous tools However, features of SPARQL are not mature enough to express complex mappings: we thus propose an extension:SPARQL++ Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 9 / 34
26. Slide 26: Three levels of knowledge abstraction SPARQL for instance transformation Simple example (Translate from VCard to FOAF) vCard FOAF VCard:FN foaf:name CONSTRUCT { ?X foaf:name ?Y } WHERE { ?X VCard:FN ?Y } Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 10 / 34
27. Slide 27: Three levels of knowledge abstraction SPARQL for instance transformation Simple example (Translate from VCard to FOAF) vCard FOAF VCard:FN foaf:name CONSTRUCT { ?X foaf:name ?Y } WHERE { ?X VCard:FN ?Y } Easy! Supported by standard SPARQL Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 10 / 34
28. Slide 28: Three levels of knowledge abstraction SPARQL for instance transformation Built-in functions and value generation vCard FOAF foaf:name VCard:Given VCard:Family CONSTRUCT { ?X foaf:name fn:concat(?N,\" \",?F } WHERE { ?X VCard:Given ?N. ?X VCard:Family ?F } Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 11 / 34
29. Slide 29: Three levels of knowledge abstraction SPARQL for instance transformation Built-in functions and value generation vCard FOAF foaf:name VCard:Given VCard:Family CONSTRUCT { ?X foaf:name fn:concat(?N,\" \",?F } WHERE { ?X VCard:Given ?N. ?X VCard:Family ?F } This is not possible in standard SPARQL Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 11 / 34
30. Slide 30: Three levels of knowledge abstraction SPARQL for instance transformation Example: Aggregates Translate from DOAP to RDF Open Source Software Vocabulary Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 12 / 34
31. Slide 31: Three levels of knowledge abstraction SPARQL for instance transformation Example: Aggregates Translate from DOAP to RDF Open Source Software Vocabulary CONSTRUCT { ?P os:latestRelease MAX(?V : ?P doap:release ?R. ?R doap:revision ?V) } WHERE { ?P rdf:type doap:Project . } Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 12 / 34
32. Slide 32: Three levels of knowledge abstraction SPARQL for instance transformation Example: regular path expressions (pSPARQL) o1 o2 + o1:parentOf o2:ancestorOf Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 13 / 34
33. Slide 33: Three levels of knowledge abstraction SPARQL for instance transformation Example: regular path expressions (pSPARQL) o1 o2 + o1:parentOf o2:ancestorOf CONSTRUCTs with regular path expressions can cater for that, this is possible in pSPARQL: Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 13 / 34
34. Slide 34: Three levels of knowledge abstraction SPARQL for instance transformation Example: regular path expressions (pSPARQL) o1 o2 + o1:parentOf o2:ancestorOf CONSTRUCTs with regular path expressions can cater for that, this is possible in pSPARQL: CONSTRUCT { ?X o2:ancestor ?Y } WHERE { ?X o1:parentOf+ ?Y . } Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 13 / 34
35. Slide 35: Three levels of knowledge abstraction SPARQL for instance transformation Example: regular path expressions (pSPARQL) o1 o2 + o1:parentOf o2:ancestorOf CONSTRUCTs with regular path expressions can cater for that, this is possible in pSPARQL: CONSTRUCT { ?X o2:ancestor ?Y } WHERE { ?X o1:parentOf+ ?Y . } pSPARQL offers even more: full regular expressions over paths conditions over paths, etc. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 13 / 34
36. Slide 36: Three levels of knowledge abstraction SPARQL for instance transformation SPARQL++ was published at OTM 2007. The paper contains details of the extension, semantics, and implementation details. pSPARQL integration in our alignment framework was published at OnAv 2008. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 14 / 34
37. Slide 37: Three levels of knowledge abstraction The Alignment Format and Ontology Motivation and requirements considering the alignment as a first-class citizen Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 15 / 34
38. Slide 38: Three levels of knowledge abstraction The Alignment Format and Ontology Motivation and requirements considering the alignment as a first-class citizen being independent from the ontology formalism Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 15 / 34
39. Slide 39: Three levels of knowledge abstraction The Alignment Format and Ontology Motivation and requirements considering the alignment as a first-class citizen being independent from the ontology formalism being able to represent correspondences between ontological entities Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 15 / 34
40. Slide 40: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
41. Slide 41: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
42. Slide 42: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities One to one, many to many, using set operators on the entities Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
43. Slide 43: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities One to one, many to many, using set operators on the entities Heterogeneous correspondences Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
44. Slide 44: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities One to one, many to many, using set operators on the entities Heterogeneous correspondences Conditions can restrict entities scope Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
45. Slide 45: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities One to one, many to many, using set operators on the entities Heterogeneous correspondences Conditions can restrict entities scope Transformations of attributes values Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
46. Slide 46: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities One to one, many to many, using set operators on the entities Heterogeneous correspondences Conditions can restrict entities scope Transformations of attributes values Paths Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
47. Slide 47: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Ontology Models the ontology alignment domain Classes, Attributes, Relations and Instances for the entities One to one, many to many, using set operators on the entities Heterogeneous correspondences Conditions can restrict entities scope Transformations of attributes values Paths Model theoretic based semantics Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 16 / 34
48. Slide 48: Three levels of knowledge abstraction The Alignment Format and Ontology The Alignment Format Example serialization of Cell instances (RDF/XML): FOAF persons based in Innsbruck have a particular VCard phone extension: <Cell> <entity1> <Class rdf:about=\"&foaf;Person\"> <attributeValueCondition> <Restriction> <onProperty rdf:resource=\"&foaf;based_near\"/> <comparator rdf:datatype=\"&xsd;string\">xsd:equals</comparator> <value rdf:datatype=\"&xsd;string\">Fortaleza</value> </Restriction> </attributeValueCondition> </Class> </entity1> Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 17 / 34
49. Slide 49: Three levels of knowledge abstraction The Alignment Format and Ontology The alignment format as an exchange format (2) <entity2> <Class rdf:about=\"&v;VCard\"> <attributeValueCondition> <Restriction> <onProperty rdf:resource=\"&v;workTel\"/> <comparator rdf:datatype=\"&xsd;string\">xsd:startsWith</comparat <value rdf:datatype=\"&xsd;string\">+0043512</value> </Restriction> </attributeValueCondition> </Class> </entity2> <measure RDF:datatype=’&BSD;float’>1.0</measure> <relation>equivalence</relation> </Cell> Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 18 / 34
50. Slide 50: Three levels of knowledge abstraction The Alignment Format and Ontology Alignments semantics Based on [Zimmermann 2006] and largely compliant with description logics. Syntax level o o Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 19 / 34
51. Slide 51: Three levels of knowledge abstraction The Alignment Format and Ontology Alignments semantics Based on [Zimmermann 2006] and largely compliant with description logics. Syntax level o o I I Local semantics level D D Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 19 / 34
52. Slide 52: Three levels of knowledge abstraction The Alignment Format and Ontology Alignments semantics Based on [Zimmermann 2006] and largely compliant with description logics. Syntax level o o I I Local semantics level D D Global semantics level D Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 19 / 34
53. Slide 53: Three levels of knowledge abstraction The Alignment Format and Ontology Alignments semantics Based on [Zimmermann 2006] and largely compliant with description logics. A Syntax level o o I I I Local semantics level D D Global semantics level D Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 19 / 34
54. Slide 54: Three levels of knowledge abstraction The Alignment Format and Ontology Entity semantics The semantics of expressions are interpreted within D through: ∀x ∈ QL (o), o I (x) ∈ D Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 20 / 34
55. Slide 55: Three levels of knowledge abstraction The Alignment Format and Ontology Expression semantics The expression semantics is typically the semantics of a description logic: I (c) = o I (c) I (C C ) = I (C ) ∪ I (C ) I (C C ) = I (C ) ∩ I (C ) I (¬C ) = D − I (C ) I (∃K ) = {x ∈ D|∃y ∈ D; x, y ∈ I (K )} Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 21 / 34
56. Slide 56: Three levels of knowledge abstraction The Alignment Format and Ontology Alignment processing The combined alignment API (INRIA) and Mapping API allow to parse alignments and ground them for execution. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 22 / 34
57. Slide 57: Correspondence Patterns Patterns Patterns in the literature Capture recurring knowledge Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 23 / 34
58. Slide 58: Correspondence Patterns Patterns Patterns in the literature Capture recurring knowledge Facilitate the design task by using known structures Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 23 / 34
59. Slide 59: Correspondence Patterns Patterns Patterns in the literature Capture recurring knowledge Facilitate the design task by using known structures Facilitate semi-automatic design Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 23 / 34
60. Slide 60: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
61. Slide 61: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
62. Slide 62: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Problem: A statement describing the intent, goals of the patterns, which entities are involved in the correspondence. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
63. Slide 63: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Problem: A statement describing the intent, goals of the patterns, which entities are involved in the correspondence. Context: refers to the context of usage for the pattern (specific domain, specific application) Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
64. Slide 64: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Problem: A statement describing the intent, goals of the patterns, which entities are involved in the correspondence. Context: refers to the context of usage for the pattern (specific domain, specific application) Solution: describe the result of using the pattern. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
65. Slide 65: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Problem: A statement describing the intent, goals of the patterns, which entities are involved in the correspondence. Context: refers to the context of usage for the pattern (specific domain, specific application) Solution: describe the result of using the pattern. Example: example alignment representing this pattern Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
66. Slide 66: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Problem: A statement describing the intent, goals of the patterns, which entities are involved in the correspondence. Context: refers to the context of usage for the pattern (specific domain, specific application) Solution: describe the result of using the pattern. Example: example alignment representing this pattern Related Patterns: relationships between this pattern and others Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
67. Slide 67: Correspondence Patterns Pattern template Pattern template elements Name: give a meaningful name for the pattern, corresponds to a fragment of the URI associated with the pattern. Alias: alternative name Problem: A statement describing the intent, goals of the patterns, which entities are involved in the correspondence. Context: refers to the context of usage for the pattern (specific domain, specific application) Solution: describe the result of using the pattern. Example: example alignment representing this pattern Related Patterns: relationships between this pattern and others Known uses: URIs of existing alignments using this patterns Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 24 / 34
68. Slide 68: Correspondence Patterns Pattern template Example pattern: Aggregation pattern http://www.ubuntu.org/ os:LatestVersion \"8.04\" os:Software os:LatestVersion String Class Attribute Attribute Value Correspondence Correspondence aggregation (MAX) Aggregation Pattern doap:Project doap:realease doap:Version doap:revision values Warty Warthog doap:revision \"4.10\" http://www.ubuntu.org/ doap:realease Hoary Hedgehog doap:revision \"5.04\" ... ... ... Hardy Heron doap:revision \"8.04\" Figure: Aggregation Pattern Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 25 / 34
69. Slide 69: Correspondence Patterns Pattern template Example pattern: RCA-A pattern http://.../francois vc:VCard foaf:Person http://.../francois Attribute Relation vc:name vc:name Correspondence Class Attribute _:bn01 foaf:name foaf:name vc:N Correspondence \"Scharffe\" vc:family-name Value \"François\" Transformation value vc:given-name \"François Vincent Concatenation Alfred Scharffe\" \"Vincent Alfred\" vc:additional-name RCA-A concat Pattern Figure: Relation Class Attribute to Attribute Pattern Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 26 / 34
70. Slide 70: Correspondence Patterns Pattern library Pattern library Implemented as an ontology extending the Alignment Ontology with specific patterns properties. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 27 / 34
71. Slide 71: Correspondence Patterns Pattern library Pattern library Implemented as an ontology extending the Alignment Ontology with specific patterns properties. Sets of placeholders entities to be replaced during patterns instantiation. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 27 / 34
72. Slide 72: Correspondence Patterns Pattern library Pattern library Implemented as an ontology extending the Alignment Ontology with specific patterns properties. Sets of placeholders entities to be replaced during patterns instantiation. Around 40 patterns available. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 27 / 34
73. Slide 73: Correspondence Patterns Pattern library Pattern library(2) Figure: Overview of the patterns library Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 28 / 34
74. Slide 74: Correspondence Patterns Database mapping to ontologies patterns Database mapping to ontologies Direct Mapping A table in the database directly corresponds to a concept in the ontology. There is a one-to-one correspondence between records in the table and instances of the concept. This pattern is modeled on the basis of the Class equivalence correspondence pattern. Join/Union A set of database tables corresponds to a concept in the ontology when they are joined. There is a one-to-one correspondence between join records of the joined tables and instances of an ontology concept. This pattern is modeled on the Class Union pattern. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 29 / 34
75. Slide 75: Correspondence Patterns Database mapping to ontologies patterns Database mapping to ontologies (2) Projection A subset of the columns of a database table are needed to map a concept in the ontology. This pattern is modeled on the basis of the Class By Attribute Type pattern, where the scope of the class (the table) is restricted to the specific attributes (columns). Selection A subset of the rows of a database table map a concept in the ontology. This pattern is modeled on the basis of the Class By Attribute Value, rrestrictingthe scope of the class (the table) to only those instances (the table rows) having a given value for the specified aattributes(columns). Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 30 / 34
76. Slide 76: Correspondence Patterns Database mapping to ontologies patterns Database mapping to ontologies (3) Value transformation A column in an table corresponds to an attribute in the ontology after transformation of its value using a transformation function. This pattern is modeled on the basis of the Attribute Transformation pattern. Combinations Combinations of the aforementioned patterns are also possible. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 31 / 34
77. Slide 77: Conclusion Conclusion This thesis Introduces a new three layered framework reflecting the ontology mediation landscape: Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 32 / 34
78. Slide 78: Conclusion Conclusion This thesis Introduces a new three layered framework reflecting the ontology mediation landscape: 1. Mediation rules with the introduction of a SPARQL extension for instance transformation. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 32 / 34
79. Slide 79: Conclusion Conclusion This thesis Introduces a new three layered framework reflecting the ontology mediation landscape: 1. Mediation rules with the introduction of a SPARQL extension for instance transformation. 2. Ontology Alignment with the introduction of a alignment representation formalism: language and ontology. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 32 / 34
80. Slide 80: Conclusion Conclusion This thesis Introduces a new three layered framework reflecting the ontology mediation landscape: 1. Mediation rules with the introduction of a SPARQL extension for instance transformation. 2. Ontology Alignment with the introduction of a alignment representation formalism: language and ontology. 3. Correspondence patterns introduced, formalized, reference patterns library. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 32 / 34
81. Slide 81: Conclusion Ongoing and Future works Write the thesis ! Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 33 / 34
82. Slide 82: Conclusion Ongoing and Future works Write the thesis ! Groundings to SPARQL++ Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 33 / 34
83. Slide 83: Conclusion Ongoing and Future works Write the thesis ! Groundings to SPARQL++ Extend the pattern library with domain and application specific patterns. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 33 / 34
84. Slide 84: Conclusion Ongoing and Future works Write the thesis ! Groundings to SPARQL++ Extend the pattern library with domain and application specific patterns. Study how patterns can assist matching algorithms to discover complex matches. Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 33 / 34
85. Slide 85: Conclusion Thank you for your attention ! Questions ? Fran¸ois Scharffe (STI Innsbruck) c Ontology Alignment Representation April 14, 2008 34 / 34