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Ontology evolution for an experimental data integration system
Author(s) -
Liliana Ibănescu,
Patrice Buche,
Stéphane Dervaux,
Juliette Dibie-Barthélemy,
Rim Touhami
Publication year - 2016
Publication title -
international journal of metadata semantics and ontologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.185
H-Index - 20
eISSN - 1744-263X
pISSN - 1744-2621
DOI - 10.1504/ijmso.2016.083518
Subject(s) - ontology based data integration , ontology , computer science , suggested upper merged ontology , upper ontology , workflow , process ontology , open biomedical ontologies , ontology alignment , information retrieval , ontology inference layer , data integration , domain (mathematical analysis) , annotation , data mining , database , owl s , artificial intelligence , semantic web , mathematical analysis , philosophy , mathematics , epistemology , semantic web stack
International audienceThis paper describes an ontology evolution activity designed for a data integration system called ONDINE (Ontology based Data INtegration) which proposes a complete workflow to acquire, annotate and query experimental data extracted from scientic documents. The core element of the ONDINE system is an ontology which allows experimental data annotation and querying. In order to adapt to domain changes, new usages and new annotated data, the ontology may change. This paper presents our a priori ontology evolution activity, which takes as input an ontology in a consistent state, denes and applies some changes and manages all the consequences of those changes by producing an ontology in a consistent state. The implementation and evaluation of the evolution activity are presented. Our work is illustrated through an ONDINE system's use case, the annotation of experimental data in the domain of matter transfer

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