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(2017-06-06)



Manel Achichi, Michelle Cheatham, Zlatan Dragisic, Jérôme Euzenat, Daniel Faria, Alfio Ferrara, Giorgos Flouris, Irini Fundulaki, Ian Harrow, Valentina Ivanova, Ernesto Jiménez-Ruiz, Elena Kuss, Patrick Lambrix, Henrik Leopold, Huanyu Li, Christian Meilicke, Stefano Montanelli, Catia Pesquita, Tzanina Saveta, Pavel Shvaiko, Andrea Splendiani, Heiner Stuckenschmidt, Konstantin Todorov, Cássia Trojahn dos Santos, Ondřej Zamazal, Results of the Ontology Alignment Evaluation Initiative 2016, in: Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, Ryutaro Ichise (eds), Proc. 11th ISWC workshop on ontology matching (OM), Kobe (JP), pp73-129, 2016
BibTeX
http://ceur-ws.org/Vol-1766/oaei16_paper0.pdf
http://oaei.ontologymatching.org/2016/results/oaei2016.pdf
https://exmo.inria.fr/files/publications/achichi2016a.pdf
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation, or consensus. OAEI 2016 offered 9 tracks with 22 test cases, and was attended by 21 participants. This paper is an overall presentation of the OAEI 2016 campaign.
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation, Data interlinking/Liage de données


Michelle Cheatham, Zlatan Dragisic, Jérôme Euzenat, Daniel Faria, Alfio Ferrara, Giorgos Flouris, Irini Fundulaki, Roger Granada, Valentina Ivanova, Ernesto Jiménez-Ruiz, Patrick Lambrix, Stefano Montanelli, Catia Pesquita, Tzanina Saveta, Pavel Shvaiko, Alessandro Solimando, Cássia Trojahn dos Santos, Ondřej Zamazal, Results of the Ontology Alignment Evaluation Initiative 2015, in: Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh (eds), Proc. 10th ISWC workshop on ontology matching (OM), Bethlehem (PA US), pp60-115, 2016
BibTeX
http://ceur-ws.org/Vol-1545/oaei15_paper0.pdf
http://oaei.ontologymatching.org/2015/results/oaei2015.pdf
https://exmo.inria.fr/files/publications/cheatham2016a.pdf
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2015 offered 8 tracks with 15 test cases followed by 22 participants. Since 2011, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2015 campaign.
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation, Data interlinking/Liage de données


Olga Kovalenko, Jérôme Euzenat, Semantic matching of engineering data structures, in: Stefan Biffl, Marta Sabou (eds), Semantic web technologies for intelligent engineering applications, Springer, Heidelberg (DE), 2016, pp137-157
[DOI: 10.1007/978-3-319-41490-4_6]BibTeX
http://link.springer.com/chapter/10.1007%2F978-3-319-41490-4_6
https://exmo.inria.fr/files/publications/kovalenko2016a.pdf
An important element of implementing a data integration solution in multi-disciplinary engineering settings, consists in identifying and defining relations between the different engineering data models and data sets that need to be integrated. The ontology matching field investigates methods and tools for discovering relations between semantic data sources and representing them. In this chapter, we look at ontology matching issues in the context of integrating engineering knowledge. We first discuss what types of relations typically occur between engineering objects in multi-disciplinary engineering environments taking a use case in the power plant engineering domain as a running example. We then overview available technologies for mappings definition between ontologies, focusing on those currently most widely used in practice and briefly discuss their capabilities for mapping representation and potential processing. Finally, we illustrate how mappings in the sample project in power plant engineering domain can be generated from the definitions in the Expressive and Declarative Ontology Alignment Language (EDOAL).
Ontology matching, Correspondence, Alignment, Mapping, Ontology integration, Data transformation, Complex correspondences, Ontology mapping languages, Procedural and declarative languages, EDOAL
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, Jérôme David, Angela Locoro, Armen Inants, Context-based ontology matching and data interlinking, Deliverable 3.1, Lindicle, 21p., July 2015
BibTeX
https://exmo.inria.fr/files/reports/lindicle-31.pdf
Context-based matching finds correspondences between entities from two ontologies by relating them to other resources. A general view of context-based matching is designed by analysing existing such matchers. This view is instantiated in a path-driven approach that (a) anchors the ontologies to external ontologies, (b) finds sequences of entities (path) that relate entities to match within and across these resources, and (c) uses algebras of relations for combining the relations obtained along these paths. Parameters governing such a system are identified and made explicit. We discuss the extension of this approach to data interlinking and its benefit to cross-lingual data interlinking. First, this extension would require an hybrid algebra of relation that combines relations between individual and classes. However, such an algebra may not be particularly useful in practice as only in a few restricted case it could conclude that two individuals are the same. But it can be used for finding mistakes in link sets.
Context-based data interlinking>, Multilingual data interlinking, Context-based ontology matching, Algebras of relations, Semantic web
Linked data/Web des données, Semantic web/Web sémantique


Zlatan Dragisic, Kai Eckert, Jérôme Euzenat, Daniel Faria, Alfio Ferrara, Roger Granada, Valentina Ivanova, Ernesto Jiménez-Ruiz, Andreas Oskar Kempf, Patrick Lambrix, Stefano Montanelli, Heiko Paulheim, Dominique Ritze, Pavel Shvaiko, Alessandro Solimando, Cássia Trojahn dos Santos, Ondřej Zamazal, Bernardo Cuenca Grau, Results of the Ontology Alignment Evaluation Initiative 2014, in: Pavel Shvaiko, Jérôme Euzenat, Ming Mao, Ernesto Jiménez-Ruiz, Juanzi Li, Axel-Cyrille Ngonga Ngomo (eds), Proc. 9th ISWC workshop on ontology matching (OM), Riva del Garda (IT), pp61-104, 2014
BibTeX
http://ceur-ws.org/Vol-1317/oaei14_paper0.pdf
http://oaei.ontologymatching.org/2014/results/oaei2014.pdf
https://exmo.inria.fr/files/publications/dragisic2014a.pdf
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2014 offered 7 tracks with 9 test cases followed by 14 participants. Since 2010, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2014 campaign.
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


Angela Locoro, Jérôme David, Jérôme Euzenat, Context-based matching: design of a flexible framework and experiment, Journal on data semantics 3(1):25-46, 2014
[DOI: 10.1007/s13740-013-0019-z]BibTeX
https://exmo.inria.fr/files/publications/locoro2014a.pdf
Context-based matching finds correspondences between entities from two ontologies by relating them to other resources. A general view of context-based matching is designed by analysing existing such matchers. This view is instantiated in a path-driven approach that (a) anchors the ontologies to external ontologies, (b) finds sequences of entities (path) that relate entities to match within and across these resources, and (c) uses algebras of relations for combining the relations obtained along these paths. Parameters governing such a system are identified and made explicit. They are used to conduct experiments with different parameter configurations in order to assess their influence. In particular, experiments confirm that restricting the set of ontologies reduces the time taken at the expense of recall and F-measure. Increasing path length within ontologies increases recall and F-measure as well. In addition, algebras of relations allows for a finer analysis, which shows that increasing path length provides more correct or non precise correspondences, but marginally increases incorrect correspondences.
Context-based ontology matching, Knowledge representation and interoperability, Algebras of relations, Semantic web
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Bernardo Cuenca Grau, Zlatan Dragisic, Kai Eckert, Jérôme Euzenat, Alfio Ferrara, Roger Granada, Valentina Ivanova, Ernesto Jiménez-Ruiz, Andreas Oskar Kempf, Patrick Lambrix, Andriy Nikolov, Heiko Paulheim, Dominique Ritze, François Scharffe, Pavel Shvaiko, Cássia Trojahn dos Santos, Ondřej Zamazal, Results of the Ontology Alignment Evaluation Initiative 2013, in: Pavel Shvaiko, Jérôme Euzenat, Kavitha Srinivas, Ming Mao, Ernesto Jiménez-Ruiz (eds), Proc. 8th ISWC workshop on ontology matching (OM), Sydney (NSW AU), pp61-100, 2013
BibTeX
http://ceur-ws.org/Vol-1111/oaei13_paper0.pdf
http://oaei.ontologymatching.org/2013/results/oaei2013.pdf
https://exmo.inria.fr/files/publications/cuencagrau2013a.pdf
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2013 offered 6 tracks with 8 test cases followed by 23 participants. Since 2010, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2013 campaign.
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


Jérôme Euzenat, Maria Roşoiu, Cássia Trojahn dos Santos, Ontology matching benchmarks: generation, stability, and discriminability, Journal of web semantics 21:30-48, 2013
[DOI: 10.1016/j.websem.2013.05.002]BibTeX
https://exmo.inria.fr/files/publications/euzenat2013a.pdf
The OAEI Benchmark test set has been used for many years as a main reference to evaluate and compare ontology matching systems. However, this test set has barely varied since 2004 and has become a relatively easy task for matchers. In this paper, we present the design of a flexible test generator based on an extensible set of alterators which may be used programmatically for generating different test sets from different seed ontologies and different alteration modalities. It has been used for reproducing Benchmark both with the original seed ontology and with other ontologies. This highlights the remarkable stability of results over different generations and the preservation of difficulty across seed ontologies, as well as a systematic bias towards the initial Benchmark test set and the inability of such tests to identify an overall winning matcher. These were exactly the properties for which Benchmark had been designed. Furthermore, the generator has been used for providing new test sets aiming at increasing the difficulty and discriminability of Benchmark. Although difficulty may be easily increased with the generator, attempts to increase discriminability proved unfruitful. However, efforts towards this goal raise questions about the very nature of discriminability.
Supplementary material: [dataset]
Ontology matching, Matching evaluation, Test generation, Semantic web
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


José Luis Aguirre, Bernardo Cuenca Grau, Kai Eckert, Jérôme Euzenat, Alfio Ferrara, Willem Robert van Hage, Laura Hollink, Ernesto Jiménez-Ruiz, Christian Meilicke, Andriy Nikolov, Dominique Ritze, François Scharffe, Pavel Shvaiko, Ondřej Sváb-Zamazal, Cássia Trojahn dos Santos, Benjamin Zapilko, Results of the Ontology Alignment Evaluation Initiative 2012, in: Pavel Shvaiko, Jérôme Euzenat, Anastasios Kementsietsidis, Ming Mao, Natalya Noy, Heiner Stuckenschmidt (eds), Proc. 7th ISWC workshop on ontology matching (OM), Boston (MA US), pp73-115, 2012
BibTeX
http://ceur-ws.org/Vol-946/oaei12_paper0.pdf
http://oaei.ontologymatching.org/2012/results/oaei2012.pdf
https://exmo.inria.fr/files/publications/aguirre2012a.pdf
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI 2012 offered 7 tracks with 9 test cases followed by 21 participants. Since 2010, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2012 campaign.
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


Jérôme Euzenat, Chan Le Duc, Methodological guidelines for matching ontologies, in: Maria Del Carmen Suárez Figueroa, Asunción Gómez Pérez, Enrico Motta, Aldo Gangemi (eds), Ontology engineering in a networked world, Springer, Heidelberg (DE), 2012, pp257-278
[DOI: 10.1007/978-3-642-24794-1_12]BibTeX
http://www.springer.com/computer/ai/book/978-3-642-24793-4
https://exmo.inria.fr/files/publications/euzenat2012a.pdf
Finding alignments between ontologies is a very important operation for ontology engineering. It allows for establishing links between ontologies, either to integrate them in an application or to relate developed ontologies to context. It is even more critical for networked ontologies. Incorrect alignments may lead to unwanted consequences throughout the whole network and incomplete alignments may fail to provide the expected consequences. Yet, there is no well established methodology available for matching ontologies. We propose methodological guidelines that build on previously disconnected results and experiences.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme David, Jérôme Euzenat, François Scharffe, Cássia Trojahn dos Santos, The Alignment API 4.0, Semantic web journal 2(1):3-10, 2011
[DOI: 10.3233/SW-2011-0028]BibTeX
http://www.semantic-web-journal.net/content/new-submission-alignment-api-40
https://exmo.inria.fr/files/publications/david2011a.pdf
Alignments represent correspondences between entities of two ontologies. They are produced from the ontologies by ontology matchers. In order for matchers to exchange alignments and for applications to manipulate matchers and alignments, a minimal agreement is necessary. The Alignment API provides abstractions for the notions of network of ontologies, alignments and correspondences as well as building blocks for manipulating them such as matchers, evaluators, renderers and parsers. We recall the building blocks of this API and present here the version 4 of the Alignment API through some of its new features: ontology proxys, the expressive alignment language EDOAL and evaluation primitives.

Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, Christian Meilicke, Pavel Shvaiko, Heiner Stuckenschmidt, Cássia Trojahn dos Santos, Ontology Alignment Evaluation Initiative: six years of experience, Journal on data semantics XV(6720):158-192, 2011
[DOI: 10.1007/978-3-642-22630-4_6]BibTeX
https://exmo.inria.fr/files/publications/euzenat2011b.pdf
In the area of semantic technologies, benchmarking and systematic evaluation is not yet as established as in other areas of computer science, e.g., information retrieval. In spite of successful attempts, more effort and experience are required in order to achieve such a level of maturity. In this paper, we report results and lessons learned from the Ontology Alignment Evaluation Initiative (OAEI), a benchmarking initiative for ontology matching. The goal of this work is twofold: on the one hand, we document the state of the art in evaluating ontology matching methods and provide potential participants of the initiative with a better understanding of the design and the underlying principles of the OAEI campaigns. On the other hand, we report experiences gained in this particular area of semantic technologies to potential developers of benchmarking for other kinds of systems. For this purpose, we describe the evaluation design used in the OAEI campaigns in terms of datasets, evaluation criteria and workflows, provide a global view on the results of the campaigns carried out from 2005 to 2010 and discuss upcoming trends, both specific to ontology matching and generally relevant for the evaluation of semantic technologies. Finally, we argue that there is a need for a further automation of benchmarking to shorten the feedback cycle for tool developers.
Evaluation, Experimentation, Benchmarking, Ontology matching, Ontology alignment, Schema matching, Semantic technologies
Evaluation/Évaluation, Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, Alfio Ferrara, Willem Robert van Hague, Laura Hollink, Christian Meilicke, Andriy Nikolov, François Scharffe, Pavel Shvaiko, Heiner Stuckenschmidt, Ondřej Sváb-Zamazal, Cássia Trojahn dos Santos, Results of the Ontology Alignment Evaluation Initiative 2011, in: Pavel Shvaiko, Isabel Cruz, Jérôme Euzenat, Tom Heath, Ming Mao, Christoph Quix (eds), Proc. 6th ISWC workshop on ontology matching (OM), Bonn (DE), pp85-110, 2011
BibTeX
http://ceur-ws.org/Vol-814/oaei11_paper0.pdf
http://oaei.ontologymatching.org/2011/results/oaei2011.pdf
https://exmo.inria.fr/files/publications/euzenat2011d.pdf
Ontology matching consists of finding correspondences between entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from simple directories to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2011 builds over previous campaigns by having 4 tracks with 6 test cases followed by 18 participants. Since 2010, the campaign introduces a new evaluation modality in association with the SEALS project. A subset of OAEI test cases is included in this new modality which provides more automation to the evaluation and more direct feedback to the participants. This paper is an overall presentation of the OAEI 2011 campaign.
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


Maria Roşoiu, Cássia Trojahn dos Santos, Jérôme Euzenat, Ontology matching benchmarks: generation and evaluation, in: Pavel Shvaiko, Isabel Cruz, Jérôme Euzenat, Tom Heath, Ming Mao, Christoph Quix (eds), Proc. 6th ISWC workshop on ontology matching (OM), Bonn (DE), pp73-84, 2011
BibTeX
http://ceur-ws.org/Vol-814/om2011_Tpaper7.pdf
https://exmo.inria.fr/files/publications/rosoiu2011a.pdf
The OAEI Benchmark data set has been used as a main reference to evaluate and compare matching systems. It requires matching an ontology with systematically modified versions of itself. However, it has two main drawbacks: it has not varied since 2004 and it has become a relatively easy task for matchers. In this paper, we present the design of a modular test generator that overcomes these drawbacks. Using this generator, we have reproduced Benchmark both with the original seed ontology and with other ontologies. Evaluating different matchers on these generated tests, we have observed that (a) the difficulties encountered by a matcher at a test are preserved across the seed ontology, (b) contrary to our expectations, we found no systematic positive bias towards the original data set which has been available for developers to test their systems, and (c) the generated data sets have consistent results across matchers and across seed ontologies. However, the discriminant power of the generated tests is still too low and more tests would be necessary to draw definitive conclusions.
Ontology matching, Matching evaluation, Test generation, Semantic web
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


Jérôme David, Jérôme Euzenat, Ondřej Sváb-Zamazal, Ontology similarity in the alignment space, in: Proc. 9th international semantic web conference (ISWC), Shanghai (CN), ( Peter Patel-Schneider, Yue Pan, Pascal Hitzler, Peter Mika, Lei Zhang, Jeff Pan, Ian Horrocks, Birte Glimm (eds), The semantic web, Lecture notes in computer science 6496, 2010), pp129-144, 2010
[DOI: 10.1007/978-3-642-17746-0_9]BibTeX
https://exmo.inria.fr/files/publications/david2010b.pdf
Measuring similarity between ontologies can be very useful for different purposes, e.g., finding an ontology to replace another, or finding an ontology in which queries can be translated. Classical measures compute similarities or distances in an ontology space by directly comparing the content of ontologies. We introduce a new family of ontology measures computed in an alignment space: they evaluate the similarity between two ontologies with regard to the available alignments between them. We define two sets of such measures relying on the existence of a path between ontologies or on the ontology entities that are preserved by the alignments. The former accounts for known relations between ontologies, while the latter reflects the possibility to perform actions such as instance import or query translation. All these measures have been implemented in the OntoSim library, that has been used in experiments which showed that entity preserving measures are comparable to the best ontology space measures. Moreover, they showed a robust behaviour with respect to the alteration of the alignment space.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies, Ontology distances/Distances entre ontologies


Jérôme Euzenat, Alfio Ferrara, Christian Meilicke, Andriy Nikolov, Juan Pane, François Scharffe, Pavel Shvaiko, Heiner Stuckenschmidt, Ondřej Sváb-Zamazal, Vojtech Svátek, Cássia Trojahn dos Santos, Results of the Ontology Alignment Evaluation Initiative 2010, in: Pavel Shvaiko, Jérôme Euzenat, Fausto Giunchiglia, Heiner Stuckenschmidt, Ming Mao, Isabel Cruz (eds), Proc. 5th ISWC workshop on ontology matching (OM), Shanghai (CN), pp85-117, 2010
BibTeX
http://ceur-ws.org/Vol-689/oaei10_paper0.pdf
http://oaei.ontologymatching.org/2010/results/oaei2010.pdf
https://exmo.inria.fr/files/publications/euzenat2010b.pdf
Ontology matching consists of finding correspondences between entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from simple directories to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2010 builds over previous campaigns by having 4 tracks with 6 test cases followed by 15 participants. This year, the OAEI campaign introduces a new evaluation modality in association with the SEALS project. A subset of OAEI test cases is included in this new modality which provides more automation to the evaluation and more direct feedback to the participants. This paper is an overall presentation of the OAEI 2010 campaign.
Evaluation/Évaluation, Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, Christian Meilicke, Heiner Stuckenschmidt, Cássia Trojahn dos Santos, A web-based evaluation service for ontology matching, in: Proc. 9th demonstration track on international semantic web conference (ISWC), Shanghai (CN), pp93-96, 2010
BibTeX
http://ceur-ws.org/Vol-658/paper468.pdf
https://exmo.inria.fr/files/publications/euzenat2010c.pdf
Evaluation of semantic web technologies at large scale, including ontology matching, is an important topic of semantic web research. This paper presents a web-based evaluation service for automatically executing the evaluation of ontology matching systems. This service is based on the use of a web service interface wrapping the functionality of a matching tool to be evaluated and allows developers to launch evaluations of their tool at any time on their own. Furthermore, the service can be used to visualise and manipulate the evaluation results. The approach allows the execution of the tool on the machine of the tool developer without the need for a runtime environment.
Evaluation/Évaluation, Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Cássia Trojahn dos Santos, Jérôme Euzenat, Consistency-driven argumentation for alignment agreement, in: Pavel Shvaiko, Jérôme Euzenat, Fausto Giunchiglia, Heiner Stuckenschmidt, Ming Mao, Isabel Cruz (eds), Proc. 5th ISWC workshop on ontology matching (OM), Shanghai (CN), pp37-48, 2010
BibTeX
http://ceur-ws.org/Vol-689/om2010_Tpaper4.pdf
https://exmo.inria.fr/files/publications/trojahn2010b.pdf
Ontology alignment agreement aims at overcoming the problem that arises when different parties need to conciliate their conflicting views on ontology alignments. Argumentation has been applied as a way for supporting the creation and exchange of arguments, followed by the reasoning on their acceptability. Here we use arguments as positions that support or reject correspondences. Applying only argumentation to select correspondences may lead to alignments which relates ontologies in an inconsistent way. In order to address this problem, we define maximal consistent sub-consolidations which generate consistent and argumentation-grounded alignments. We propose a strategy for computing them involving both argumentation and logical inconsistency detection. It removes correspondences that introduce inconsistencies into the resulting alignment and allows for maintaining the consistency within an argumentation system. We present experiments comparing the different approaches. The (partial) experiments suggest that applying consistency checking and argumentation independently significantly improves results, while using them together does not bring so much. The features of consistency checking and argumentation leading to this result are analysed.
Ontology matching/Alignement d'ontologies, Argumentation/Argumentation


Cássia Trojahn dos Santos, Christian Meilicke, Jérôme Euzenat, Heiner Stuckenschmidt, Automating OAEI Campaigns (First Report), in: Asunción Gómez Pérez, Fabio Ciravegna, Frank van Harmelen, Jeff Heflin (eds), Proc. 1st ISWC international workshop on evaluation of semantic technologies (iWEST), Shanghai (CN), 2010
BibTeX
http://ceur-ws.org/Vol-666/paper13.pdf
https://exmo.inria.fr/files/publications/trojahn2010c.pdf
This paper reports the first effort into integrating OAEI and SEALS evaluation campaigns. The SEALS project aims at providing standardized resources (software components, data sets, etc.) for automatically executing evaluations of typical semantic web tools, including ontology matching tools. A first version of the software infrastructure is based on the use of a web service interface wrapping the functionality of a matching tool to be evaluated. In this setting, the evaluation results can visualized and manipulated immediately in a direct feedback cycle. We describe how parts of the OAEI 2010 evaluation campaign have been integrated into this software infrastructure. In particular, we discuss technical and organizational aspects related to the use of the new technology for both participants and organizers of the OAEI.
ontology matching, evaluation workflows, evaluation criteria, automating evaluation
Ontology matching/Alignement d'ontologies, Evaluation/Évaluation


Mathieu d'Aquin, Jérôme Euzenat, Chan Le Duc, Holger Lewen, Sharing and reusing aligned ontologies with cupboard, in: Proc. K-Cap poster session , Redondo Beach (CA US), pp179-180, 2009
[DOI: 10.1145/1597735.1597771]BibTeX
https://exmo.inria.fr/files/publications/daquin2009a.pdf
This demo presents the Cupboard online system for sharing and reusing ontologies linked together with alignments, and that are attached to rich metadata and reviews.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies, Ontology distances/Distances entre ontologies


Jérôme Euzenat, Alfio Ferrara, Laura Hollink, Antoine Isaac, Cliff Joslyn, Véronique Malaisé, Christian Meilicke, Andriy Nikolov, Juan Pane, Marta Sabou, François Scharffe, Pavel Shvaiko, Vassilis Spiliopoulos, Heiner Stuckenschmidt, Ondřej Sváb-Zamazal, Vojtech Svátek, Cássia Trojahn dos Santos, George Vouros, Shenghui Wang, Results of the Ontology Alignment Evaluation Initiative 2009, in: Pavel Shvaiko, Jérôme Euzenat, Fausto Giunchiglia, Heiner Stuckenschmidt, Natalya Noy, Arnon Rosenthal (eds), Proc. 4th ISWC workshop on ontology matching (OM), Chantilly (VA US), pp73-126, 2009
BibTeX
http://ceur-ws.org/Vol-551/oaei09_paper0.pdf
http://oaei.ontologymatching.org/2009/results/oaei2009.pdf
https://exmo.inria.fr/files/publications/euzenat2009c.pdf
Ontology matching consists of finding correspondences between ontology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2009 builds over previous campaigns by having 5 tracks with 11 test cases followed by 16 participants. This paper is an overall presentation of the OAEI 2009 campaign.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Pavel Shvaiko, Jérôme Euzenat, Fausto Giunchiglia, Heiner Stuckenschmidt, Natalya Noy, Arnon Rosenthal (eds), Proc. 4th ISWC workshop on ontology matching (OM), Chantilly (VA US), 271p., 2009
BibTeX
http://ceur-ws.org/Vol-551/
https://exmo.inria.fr/files/reports/ISWC2009-OM-ws.pdf
Semantic web/Web sémantiqueSemantic web/Web sémantique, Ontology matching/Alignement d'ontologies, Ontology matching/Alignement d'ontologies


Jérôme David, Jérôme Euzenat, Comparison between ontology distances (preliminary results), in: Proc. 7th international semantic web conference (ISWC), Karlsruhe (DE), ( Amit Sheth, Steffen Staab, Mike Dean, Massimo Paolucci, Diana Maynard, Timothy Finin, Krishnaprasad Thirunarayan (eds), The semantic web, Lecture notes in computer science 5318, 2008), pp245-260, 2008
[DOI: 10.1007/978-3-540-88564-1_16]BibTeX
https://exmo.inria.fr/files/publications/david2008a.pdf
There are many reasons for measuring a distance between ontologies. In particular, it is useful to know quickly if two ontologies are close or remote before deciding to match them. To that extent, a distance between ontologies must be quickly computable. We present constraints applying to such measures and several possible ontology distances. Then we evaluate experimentally some of them in order to assess their accuracy and speed.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies, Ontology distances/Distances entre ontologies


Caterina Caraciolo, Jérôme Euzenat, Laura Hollink, Ryutaro Ichise, Antoine Isaac, Véronique Malaisé, Christian Meilicke, Juan Pane, Pavel Shvaiko, Heiner Stuckenschmidt, Ondřej Sváb, Vojtech Svátek, Results of the Ontology Alignment Evaluation Initiative 2008, in: Pavel Shvaiko, Jérôme Euzenat, Fausto Giunchiglia, Heiner Stuckenschmidt (eds), Proc. 3rd ISWC workshop on ontology matching (OM), Karlsruhe (DE), pp73-119, 2008
BibTeX
http://ceur-ws.org/Vol-431/oaei08_paper0.pdf
http://oaei.ontologymatching.org/2008/results/oaei2008.pdf
https://exmo.inria.fr/files/publications/caraciolo2008a.pdf
Ontology matching consists of finding correspondences between ontology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test sets. Test sets can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2008 builds over previous campaigns by having 4 tracks with 8 test sets followed by 13 participants. Following the trend of previous years, more participants reach the forefront. The official results of the campaign are those published on the OAEI web site.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, François Scharffe, Axel Polleres, Processing ontology alignments with SPARQL (Position paper), in: Proc. IEEE international workshop on Ontology alignment and visualization (OAaV), Barcelona (ES), pp913-917, 2008
[DOI: 10.1109/CISIS.2008.126]BibTeX
https://exmo.inria.fr/files/publications/euzenat2008d.pdf
Solving problems raised by heterogeneous ontologies can be achieved by matching the ontologies and processing the resulting alignments. This is typical of data mediation in which the data must be translated from one knowledge source to another. We propose to solve the data translation problem, i.e. the processing part, using the SPARQL query language. Indeed, such a language is particularly adequate for extracting data from one ontology and, through its CONSTRUCT statement, for generating new data. We present examples of such transformations, but we also present a set of example correspondences illustrating the needs for particular representation constructs, such as aggregates, value-generating built-in functions and paths, which are missing from SPARQL. Hence, we advocate the use of two SPARQL extensions providing these missing features.
ontology alignment, semantic web, SPARQL, alignment grounding, alignment language, mapping language
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, Algebras of ontology alignment relations, in: Proc. 7th international semantic web conference (ISWC), Karlsruhe (DE), ( Amit Sheth, Steffen Staab, Mike Dean, Massimo Paolucci, Diana Maynard, Timothy Finin, Krishnaprasad Thirunarayan (eds), The semantic web, Lecture notes in computer science 5318, 2008), pp387-402, 2008
[DOI: 10.1007/978-3-540-88564-1_25]BibTeX
https://exmo.inria.fr/files/publications/euzenat2008e.pdf
Correspondences in ontology alignments relate two ontology entities with a relation. Typical relations are equivalence or subsumption. However, different systems may need different kinds of relations. We propose to use the concepts of algebra of relations in order to express the relations between ontology entities in a general way. We show the benefits in doing so in expressing disjunctive relations, merging alignments in different ways, amalgamating alignments with relations of different granularity, and composing alignments.
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies, Granularity/Granularité


Jérôme Euzenat, François Scharffe, Axel Polleres, SPARQL Extensions for processing alignments, IEEE Intelligent systems 23(6):82-84, 2008
[DOI: 10.1109/MIS.2008.108]BibTeX
https://exmo.inria.fr/files/publications/euzenat2008g.pdf
Semantic web/Web sémantique, Ontology matching/Alignement d'ontologies


Jérôme Euzenat, An API for ontology alignment, in: Proc. 3rd international semantic web conference (ISWC), Hiroshima (JP), ( Frank van Harmelen, Sheila McIlraith, Dimitris Plexousakis (eds), The semantic web, Lecture notes in computer science 3298, 2004), pp698-712, 2004
[DOI: 10.1007/978-3-540-30475-3_48]BibTeX
https://exmo.inria.fr/files/publications/euzenat2004f.pdf
Ontologies are seen as the solution to data heterogeneity on the web. However, the available ontologies are themselves source of heterogeneity. This can be overcome by aligning ontologies, or finding the correspondence between their components. These alignments deserve to be treated as objects: they can be referenced on the web as such, be completed by an algorithm that improves a particular alignment, be compared with other alignments and be transformed into a set of axioms or a translation program. We present here a format for expressing alignments in RDF, so that they can be published on the web. Then we propose an implementation of this format as an Alignment API, which can be seen as an extension of the OWL API and shares some design goals with it. We show how this API can be used for effectively aligning ontologies and completing partial alignments, thresholding alignments or generating axioms and transformations.
Ontology matching/Alignement d'ontologies

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