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Studying the Reuse of Content in Biomedical Ontologies: An Axiom-Based Approach


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Title:
Studying the Reuse of Content in Biomedical Ontologies: An Axiom-Based Approach
Authors:
Quesada-Martínez, Manuel
Fernández-Breis, Jesualdo Tomás
Editor:
Springer
Department:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Issue Date:
2017-06
URI:
https://hdl.handle.net/11000/39013
Abstract:
The biomedical community has developed many ontologies in the last years, which may follow a set of community accepted principles for ontology development such as the ones proposed by the OBO Foundry. One of such principles is the orthogonality of biomedical ontologies, which should be based on the reuse of existing content. Previous works have studied how ontology matching techniques help to increase the number of terms reused. In this paper we investigate to what extent the reuse of terms also mean reuse of logical axioms. For this purpose, our method identifies two different ways of reusing terms, reuse of URIs (implicit reuse) and reuse of concepts (explicit reuse). The method is also able of detecting hidden axioms, that is, axioms associated with a reused term but that are not actually reused. We have developed and applied our method to a corpus of 144 OBO Foundry ontologies. The results show that 75 ontologies implicitly reuse terms, 50% of which also explicitly does it. The characterisation based on reuse enables the visualisation of the corpus as a dependency graph that can be clustered for grouping ontologies by their reuse profile. Finally, the application of a locality-based module extractor reveals that roughly 2 000 terms and 20 000 hidden axioms, on average, could be automatically reused.
Keywords/Subjects:
Biomedical ontologies
Ontology axiomatisation
Reuse
Type of document:
info:eu-repo/semantics/conferenceObject
Access rights:
info:eu-repo/semantics/restrictedAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI:
10.1007/978-3-319-59758-4 1
Published in:
Artifical Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine - AIME, Proceedings(2017)
Appears in Collections:
Artículos - Estadística, Matemáticas e Informática



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