part iv: representing, explaining, and processing alignments & part v: conclusions ontology...
TRANSCRIPT
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PART IV:REPRESENTING, EXPLAINING,
AND PROCESSING ALIGNMENTS&
PART V:CONCLUSIONS
Ontology Matching
Jerome 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
Level
Type
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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 correspondences
1. 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