Résumé
Lignocellulosic biomass and agro-waste valorization routes are two of the promising methodstowards a more sustainable bio-economy. Scientific literature in this domain is increasing fast andcould be a valuable source of data. As these abundant scientific data are mostly in textual formatand heterogeneously structured, using them to compute biomass treatment efficiency is notstraightforward. The implementation of a Decision Support System (DSS) based on an originalpipeline coupling knowledge management (KM) based on semantic web technologies, softcomputing techniques and environmental factor computation has been already done forlignocellulosic biomass valorization routes into glucose [Lousteau-Cazalet et al. 2016]. The DSSallows using data found in the literature to assess environmental sustainability of biorefinerysystems. The pipeline permits to: (1) structure and integrate relevant experimental data, (2) assessdata source reliability [Destercke et al. 2013], (3) compute and visualize green indicators takinginto account data imprecision and source reliability. This pipeline has been made possible thanksto innovative researches in the coupling of ontologies, uncertainty management and propagation.In this first version, data acquisition is done by experts and facilitated by a Termino-OntologicalResource (TOR) called Biorefinery and available at http://www6.inra.fr/cati-icatatweb/Ontologies/Biorefinery. Data source reliability assessment is based on domain knowledgeand done by experts. The operational prototype has been used by field experts on realistic use cases(glucose extraction for biofuel production [Licari et al. 2016]). The obtained results have validatedthe usefulness of the system.