PART IV:REPRESENTING, EXPLAINING,

AND PROCESSING ALIGNMENTS&

PART V:CONCLUSIONS

Ontology MatchingJerome Euzenat and Pavel Shvaiko

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Overview Alignments

Representing alignments Formants Frameworks Editors

Explaining alignments Justifications Explanations Arguments

Processing alignments Conclusions

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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

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Representing Alignments OWL

Language for expressing correspondences between ontologies

Example

Alignment formats

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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

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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”

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Representing Alignments Alignment format

Simple alignment representation that handles complex alignment definitions

Example

Alignment formats

Correspondence

Strength

Relation type

LevelType

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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

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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

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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).

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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 alignments2. The need to exchange with other applications

Especially if the applications involve different ontology languages

Alignment formats - Summary

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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

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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

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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

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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

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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

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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

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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

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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

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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’?

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Explaining Alignments Explaining basic matchers using S-Match

Explanations

Sources of background knowledge used to determine the correspondence

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Explaining Alignments Explaining the matching process using iMAP

Explanations

Creation and flow for the correspondence month-posted = monthly-fee-rate

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Explaining Alignments Arguing about correspondences

Give arguments in favor/against the correspondences1. Negotiating an alignment between two agents2. 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;

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Processing Alignments Processing alignment according to

application needs Goal: determine how the alignments can be

specifically used by the applications

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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

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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

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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

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Processing Alignments Mediation

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

Mediation

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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

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Trends in the field Increase awareness of the existing

matching efforts across the relevant communities and facilitate the cross-fertilization between them

Conclusion

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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

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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

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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