Abstract
Agrifood chain processes are based on a multitude of knowledge, know-how and experiences forged over time. This collective expertise must be shared to improve food quality. Capex software implements a comprehensive methodology to create a knowledge base integrating collective expertise, while also using it to recommend technical actions required to improve food quality. Capex proposes an innovative core ontology that utilizes the international languages of the Semantic Web to effectively represent knowledge in the form of decision trees. These decision trees depict potential causal relationships between situations of interest and provide recommendations for managing them through technological actions, as well as a collective assessment of the efficiency of those actions. Mind map files created using mind-mapping tools are automatically translated into an RDF knowledge base using the core ontological model. Finally, capex includes a multicriteria decision-support filtering system (MCDSS) using the knowledge base. It consists of an explanatory view allowing navigation in a decision tree and an action view for multicriteria filtering and possible side effect identification.