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Linked data meets ontology matching: enhancing data linking through ontology alignments

François Scharffe 1 Jérôme Euzenat 2
1 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 EXMO - Computer mediated exchange of structured knowledge
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : The Web of data consists of publishing data on the Web in such a way that they can be connected together and interpreted. It is thus critical to establish links between these data, both for the Web of data and for the Semantic Web that it contributes to feed. We consider here the various techniques which have been developed for that purpose and analyze their commonalities and differences. This provides a general framework that the diverse data linking systems instantiate. From this framework we consider the relation between data linking and ontology matching activities. Although, they can be considered similar at a certain level (they both relate formal entities), they serve different purposes: one acts at the schema level and the other at the instance level. However, they would find a mutual benefit at collaborating. We thus present a scheme under which it is possible for data linking tools to take advantage of ontology alignments. We present the features of expressive alignment languages that allows linking specifications to reuse ontology alignments in a natural way.
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https://hal.inria.fr/hal-00781027
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François Scharffe, Jérôme Euzenat. Linked data meets ontology matching: enhancing data linking through ontology alignments. Proc. 3rd international conference on Knowledge engineering and ontology development (KEOD), Oct 2011, Paris, France. pp.279-284. ⟨hal-00781027⟩

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