Abstract : A preliminary step in microbial risk assessment in foods is the gathering of experimental data. In the framework of the Sym'Previus project, we have designed a complete data integration system opened on the Web which allows a local database to be complemented by data extracted from the Web and annotated using a domain ontology. We focus on the Web data tables as they contain, in general, a synthesis of data published in the documents. We propose in this paper a flexible querying system using the domain ontology to scan simultaneously local andWeb data, this in order to feed the predictive modeling tools available on the Sym'Previus platform. Special attention is paid on the way fuzzy annotations associated with Web data are taken into account in the querying process, which is an important and original contribution of the proposed system.
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00538961
Contributeur : Patrice Buche
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Soumis le : mardi 23 novembre 2010 - 15:51:04
Dernière modification le : jeudi 24 mai 2018 - 15:59:22
Patrice Buche, Olivier Couvert, Juliette Dibie, Gaëlle Hignette, Eric Mettler, et al.. Flexible Querying of Web data to Simulate Bacterial Growth in Food. Food Microbiology, Elsevier, 2011, 28 (4), pp.685-693. 〈lirmm-00538961〉
