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A semantic enrichment of Data Tables Applied to Food Risk Assessment

Abstract : Our work deals with the automatic construction of domain specific data warehouses. Our application domain concerns microbiological risks in food products. The MIEL++ system, implemented during the Sym'Previus project, is a tool based on a database containing experimental and industrial results about the behavior of pathogenic germs in food products. This database is incomplete by nature since the number of possible experiments is potentially infinite. Our work, developed within the e.dot project1, presents a way of palliating that incompleteness by complementing the database with data automatically extracted from the Web. We propose to query these data through a mediated architecture based on a domain ontology. So, we need to make them compatible with the ontology. In the e.dot project, we exclusively focus on documents in Html or Pdf format which contain data tables. Data tables are very common presentation scheme to describe synthetic data in scientific articles. These tables are semantically enriched and we want this enrichment to be as automatic and flexible as possible. Thus, we have defined a Document Type Definition named SML (Semantic Markup Language) which can deal with additional or incomplete information in a semantic relation, ambiguities or possible interpretation errors. In this paper, we present this semantic enrichment step.
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https://hal.inria.fr/inria-00000930
Contributor : Nathalie Pernelle <>
Submitted on : Tuesday, December 13, 2005 - 6:46:14 PM
Last modification on : Wednesday, October 14, 2020 - 3:56:52 AM
Long-term archiving on: : Saturday, April 3, 2010 - 7:02:48 PM

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Hélène Gagliardi, Ollivier Haemmerlé, Nathalie Pernelle, Fatiha Saïs. A semantic enrichment of Data Tables Applied to Food Risk Assessment. Discovery in Science, 2005, Singapore, Singapore. ⟨inria-00000930⟩

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