Lignocellulosic biomass and agro-waste valorization routes are two of the promising methods towards a more sustainable bio-economy. Scientific literature in this domain is increasing fast and could be a valuable source of data. As these abundant scientific data are mostly in textual format and heterogeneously structured, using them to compute biomass treatment efficiency is not straightforward. The implementation of a Decision Support System (DSS) based on an original pipeline coupling knowledge management (KM) based on semantic web technologies, soft computing techniques and environmental factor computation has been already done for lignocellulosic biomass valorization routes into glucose [Lousteau-Cazalet et al. 2016]. The DSS allows using data found in the literature to assess environmental sustainability of biorefinery systems. The pipeline permits to: (1) structure and integrate relevant experimental data, (2) assess data source reliability [Destercke et al. 2013], (3) compute and visualize green indicators taking into account data imprecision and source reliability. This pipeline has been made possible thanks to 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-Ontological Resource (TOR) called Biorefinery and available at http://www6.inra.fr/cati-icatatweb/ Ontologies/Biorefinery. Data source reliability assessment is based on domain knowledge and 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 validated the usefulness of the system.