Logical Detection of Invalid SameAs Statements in RDF Data

Abstract : In the last years, thanks to the standardization of Semantic Web technologies, we are experiencing an unprecedented production of data, published online as Linked Data. In this context, when a typed link is instantiated between two different resources referring to the same real world entity, the usage of owl:sameAs is generally predominant. However, recent research discussions within the Linked Data community have shown issues in the use of owl:sameAs. Problems arise both in cases in which sameAs is automatically discovered by a data linking tool erroneously, or when users declare it but meaning something less 'strict' than the semantics defined by OWL. In this work, we discuss further this issue and we present a method for logically detect invalid sameAs statements under specific circumstances. We report our experimental results, performed on OAEI datasets, to prove that the approach can be promising.
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Communication dans un congrès
In proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014, Nov 2014, Linkoping, Sweden. 2014, 〈10.1007/978-3-319-13704-9_29〉
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Laura Papaleo, Nathalie Pernelle, Fatiha Saïs, Cyril Dumont. Logical Detection of Invalid SameAs Statements in RDF Data. In proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014, Nov 2014, Linkoping, Sweden. 2014, 〈10.1007/978-3-319-13704-9_29〉. 〈hal-01275943〉

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