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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 - PowerPoint PPT Presentation
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PART IV:REPRESENTING, EXPLAINING,
AND PROCESSING ALIGNMENTS&
PART V:CONCLUSIONS
Ontology MatchingJerome Euzenat and Pavel Shvaiko
2
Overview Alignments
Representing alignments Formants Frameworks Editors
Explaining alignments Justifications Explanations Arguments
Processing alignments Conclusions
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
4
Representing Alignments OWL
Language for expressing correspondences between ontologies
Example
Alignment formats
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
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”
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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
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).
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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
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
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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
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
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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
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
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
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
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’?
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Explaining Alignments Explaining basic matchers using S-Match
Explanations
Sources of background knowledge used to determine the correspondence
22
Explaining Alignments Explaining the matching process using iMAP
Explanations
Creation and flow for the correspondence month-posted = monthly-fee-rate
23
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
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
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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
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
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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
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
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
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