A decision support system using multi-source scientific data, an ...

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A decision support system using multi-source scientific data, an ...

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Abstractâ In decision tasks such as bioprocess efficiency comparison, scientific literature is a valuable source of data. This large number of scientific data is.

A decision support system using multi-source scientific data, an ontological approach and soft computing – Application to eco-efficient biorefinery Lousteau-Cazalet Charlotte INRA IATE Montpellier, France [email protected]

Barakat Abdellatif INRA IATE Montpellier, France Abdellatif.Barakat @supagro.inra.fr

Dervaux Stéphane INRA/AgroParisTech MIAF-75231 Paris stephane.dervaux @versailles.inra.fr

Destercke Sébastien CNRS Heudiasyc F-60200 Compiègne [email protected]

Belaud Jean-Pierre INP-ENSIACET, LGC Toulouse, France JeanPierre.Belaud @ensiacet.fr

Abstract— In decision tasks such as bioprocess efficiency comparison, scientific literature is a valuable source of data. This large number of scientific data is heterogeneously structured mainly in textual format. New tools able to integrate and treat continuously new information are required. In this context, the use of semantic web methods such as ontologies seems relevant to structure the experimental information. Imprecision and uncertainty can arise from data incompleteness and variability. This is particularly true for processes involving biological materials. Document reliability should also be considered. Soft computing methods have the potential to be the kingpin of specialized software that can be integrated in decision support systems (DSS) intended to solve these issues. This paper presents the implementation of a pipeline which permits to: (1) structure and integrate the experimental data of interest by using ontologies, (2) assess data source reliability, (3) compute and visualize indicators taking into account data imprecision. Keywords— Decision support system, uncertainty management, belief theory, fuzzy numbers, knowledge engineering, ontology, bioprocess eco-design

Full text on https://doi.org/10.1109/FUZZIEEE.2016.7737694

Buche Patrice INRA IATE/LIRMM Montpellier, France [email protected] ,

Dibie Juliette INRA/AgroParisTech MIA F-75231 Paris [email protected]

Busset Guillaume INP-ENSIACET, CAI Toulouse, France guillaume.busset @ensiacet.fr

Charnomordic Brigitte INRA MISTEA Montpellier, France [email protected]

Sablayrolles Caroline INP-ENSIACET, CAI Toulouse, France caroline.sablayrolles @ensiacet.fr

Vialle Claire INP-ENSIACET, CAI Toulouse, France claire.vialle @ensiacet.fr