Part IV: Representing, explaining, and processing alignments & Part V: Conclusions

Part IV:Representing, explaining, and processing alignments&Part V:Conclusions Ontology Matching Jerome Euzenat and Pavel Shvaiko

Overview • Alignments • Representing alignments • Formants • Frameworks • Editors • Explaining alignments • Justifications • Explanations • Arguments • Processing alignments • Conclusions

Representing Alignments Alignment formats • 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

Representing Alignments Alignment formats • OWL • Language for expressing correspondences between ontologies • Example

Representing Alignments Alignment formats • 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

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

Representing Alignments Alignment formats • Alignment format • Simple alignment representation that handles complex alignment definitions • Example Level Type Correspondence Strength Relation type

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

Representing Alignments Alignment formats • 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

Representing Alignments Alignment formats- Summary • Comparison +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).

Representing Alignments Alignment formats - Summary • 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 • The expressiveness required for the alignments • The need to exchange with other applications • Especially if the applications involve different ontology languages

Representing Alignments Alignment frameworks • 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

Representing Alignments Alignment frameworks • 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

Representing Alignments Alignment frameworks • 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

Representing Alignments Editors • 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

Explaining Alignments Justifications • 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

Explaining Alignments Justifications • 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

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

Explaining Alignments Explanations • 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

Explaining Alignments Explanations • A default explanation using S-Match 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’?

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

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

Explaining Alignments Arguments • Arguing about correspondences • Give arguments in favor/against the correspondences • Negotiating an alignment between two agents • Achieving an alignment through matching, i.e., treat alignments negotiation as an aggregation technique between two alignments • Example 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;

Processing Alignments • Processing alignment according to application needs • Goal: determine how the alignments can be specifically used by the applications

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

Processing Alignments Operations performed from 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

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

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

Alignment Service 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

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

Future Challenges Conclusion • 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

Future Challenges Conclusion • 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. Explanationis thus an important challenge for ontology matching as well as user interfaces in general • Processing alignments

Final Words Conclusion • For finding the correspondences between concepts, it is necessary to understand their meaning • The ultimate meaningof 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 communicationin its dynamics

Part IV: Representing, explaining, and processing alignments & Part V: Conclusions