1. PART IV: REPRESENTING, EXPLAINING, AND PROCESSING ALIGNMENTS & PART V: CONCLUSIONS Ontology Matching Jerome Euzenat and Pavel Shvaiko

2. Overview  Alignments  Representing alignments Formants Frameworks Editors  Explaining alignments Justifications Explanations Arguments  Processing alignments  Conclusions 2

3. Representing Alignments  MAFRA Semantic bridge ontology (SBO)  Provides a Semantic Bridge Ontology Entities to be mapped are identified within the ontology (instances) through a path Mapping = Bridges + Constraints + Information on Ontologies  Example Alignment formats 3

4. Representing Alignments  OWL  Language for expressing correspondences between ontologies  Example Alignment formats 4

5. Representing Alignments  Contextualized OWL (C-OWL)  Extension of OWL to express mappings between heterogeneous ontologies Bridge rules are oriented correspondences, from a source to a target ontology  Example Alignment formats 5

6. Representing Alignments  SWRL (Semantic Web Rule Language)  Extension of OWL with an explicit notion of rules Rules are interpreted as first order Horn clauses  Example Alignment formats “Whenever the conditions in the body hold, then the conditions in the head must also hold” 6

7. Representing Alignments  Alignment format  Simple alignment representation that handles complex alignment definitions  Example Alignment formats Correspondence Strength Relation type Level Type 7

8. Representing Alignments  SEKT mapping language  The alignments can be expressed in a human-readable language and with the help of an RDF vocabulary  Example Alignment formats Equivalence Equivalence + Constraint 8

9. Representing Alignments  SKOS (Simple Knowledge Organization System)  Use to express relationships between lightweight ontologies, e.g., folksonomies or thesauri Its goal is to be a layer on top of other formalisms able to express the links between entities in these formalisms It is currently under development  Example Alignment formats 9

10. Representing Alignments  Comparison Alignment formats- Summary + means that the system can be extended; Transf stands for transformation. The relations for the formats are subclass (sc), subproperty (sp), implication between formulas (imp). The terms concerned by the alignments can be classes (C), properties (P) or individuals (I). 10

11. Representing Alignments  There is no universal format for expressing alignments  The choice of a format depends on the characteristics of the application  To pick alignment formats consider 1. The expressiveness required for the alignments 2. The need to exchange with other applications Especially if the applications involve different ontology languages Alignment formats - Summary 11

12. Representing Alignments  Model management  Provides metadata manipulation infrastructure to reduce the amount of programming required to build metadata driven applications  Considers Models, which are information structures, e.g., XML schema, or relational database schema Mappings are, which are oriented alignments from one model into another  Example Alignment frameworks 12

13. Representing Alignments  COMA++ (University of Leipzig)  Schema matching infrastructure built on top of COMA  Provides an extensible library of matching algorithms, a framework for combining obtained results, and a platform for the evaluation of the effectiveness of the different matchers Alignment frameworks 13

14. Representing Alignments  MAFRA  Interactive, incremental and dynamic framework for mapping distributed ontologies  Alignment API  A Java API is available for manipulating alignments in the Alignment format Defines a set of interfaces and a set of functions that they can perform  FOAM  Tool for processing similarity-based ontology matching Alignment frameworks 14

15. Representing Alignments  Ontology editors  Edition environments which support matching and importing ontologies  Available editors Chimaera: Browser-based environment for editing, merging and testing large ontologies The Protégé Prompt Suite Interactive framework for comparing, matching, merging, maintaining versions, and translating between different knowledge representation formalisms KAON2 WSMX editor Editors 15

16. Explaining Alignments  Matching systems may produce effective alignments that may not be intuitively obvious to human users  For users to trust (and use) the alignments, they need information about them E.g., users need access to the sources used to determine semantic correspondences between ontology entities Justifications 16

17. Explaining Alignments  Justifications  Each correspondence can be assigned one or several justifications that support or infirm the correspondence Goal: explain why a correspondence should hold o not  Information included in a justification Basic matchers Users need to understand where the information comes from, with different levels of detail E.g.. external knowledge source (WordNet), reliability of the source Process traces Users may want to see a trace of the performed manipulations to yield the final alignment E.g.. trace of rules or strategies applied Justifications 17

18. Explaining Alignments  Explanation approaches  Transform “justifications” into an understandable explanation for each of the correspondences Goal: represent explanations in a simple and clear way Transformation requires: Explanations 18

19. Explaining Alignments  Approaches  Proof presentation approach Displays and explains proofs usually generated by semantic matchers  Strategic flow approach Explains to users the decision flow that capture why some results are favored over other when a matcher is composed of other matchers  Argumentation approach Considers the justifications/arguments in favor/against specific correspondences and explains which ones will hold Explanations 19

20. Explaining Alignments  A default explanation using S-Match Explanations Why S-Match suggested a set of documents stored under the node with label Europe in o as the result to the query – ‘find European pictures’? 20

21. Explaining Alignments  Explaining basic matchers using S-Match Explanations Sources of background knowledge used to determine the correspondence 21

22. Explaining Alignments  Explaining the matching process using iMAP Explanations Creation and flow for the correspondence month-posted = monthly-fee-rate 22

23. Explaining Alignments  Arguing about correspondences  Give arguments in favor/against the correspondences 1. Negotiating an alignment between two agents 2. Achieving an alignment through matching, i.e., treat alignments negotiation as an aggregation technique between two alignments  Example Arguments A1) all the known Company on the one side are Firm on the other side and vice versa; A2) the two names Company and Firm are synonyms in WordNet; 23

24. Processing Alignments  Processing alignment according to application needs  Goal: determine how the alignments can be specifically used by the applications 24

25. Processing Alignments  Ontology merging  Goal: obtaining a new ontology o’’ from two matched ontologies o and o’ so that the matched entities in o and o’ are related as prescribed by the alignment Operations performed from alignments 25

26. Processing Alignments  Ontology transformation  Goal: generating a new ontology o’’ expressing the entities of o with respect to those of o’ according to the correspondences in the alignment A  Not well supported by tools.  It is useful when one wants to express one ontology with regard to another one Operations performed from alignments 26

27. Processing Alignments  Data translation  Goal: translating instances from entities of ontology o into instances of connected entities of matched ontology o’ Operations performed from alignments 27

28. Processing Alignments  Mediation  Mediator as an independent software component that is introduced between two other components in order to help them interoperate Mediation 28

29. Alignment Service  Applications using ontology matching could benefit from sharing ontology matching techniques and results  It is useful to provide an alignment service able to store, retrieve and manipulate existing alignments as well as to generate new alignments on-the-fly  Such a service Would be shared by the applications using ontologies on the semantic web Would require a standardization support, such as the choice of an alignment format or at least of metadata format Service 29

30. Trends in the field  Increase awareness of the existing matching efforts across the relevant communities and facilitate the cross-fertilization between them Conclusion 30

31. Future Challenges  Applications  Basic techniques  Matching strategies  Matching systems  Evaluation of matching systems  Pursue current efforts on extensive evaluation of ontology matching systems using benchmark datasets  Exploit evaluation results to help users in choosing the appropriate matching or combining multiple matchers for their tasks Conclusion 31

32. Future Challenges  Representing alignments  Establish one/two standard alignment formats for exchanging the alignments  Scalable alignment visualization techniques should also be developed  Explaining alignments  In order for matching systems to gain a wider acceptance, it will be necessary that they can provide arguments for their results to users or to other programs that use them. Explanation is thus an important challenge for ontology matching as well as user interfaces in general  Processing alignments Conclusion 32

33. Final Words  For finding the correspondences between concepts, it is necessary to understand their meaning  The ultimate meaning of concepts is in the head of the people who developed those concepts and we cannot program a computer to learn it  Communication can be viewed as a continuous task of negotiating the relations between concepts, i.e., arguing about alignments, building new ones, questioning them, etc.  Matching ontologies is an on-going work and further substantial progress in the field can be made by considering communication in its dynamics Conclusion 33