Multi-source observed data are generally characterized by their syntactic, structural and semantic heterogeneities. A key challenge is the semantic interoperability of these data. In this context, we propose an ontology-based system that supports environmental monitoring. Our contributions could be resumed around 1) the construction of an ontology which allows to represent the knowledge and reuse it in a real-world way, 2) the guarantee of the semantic interoperability of ontological modules since the proposed ontology is based on the upper level ontology Basic Formal Ontology (BFO) 3) the modularity of the proposed ontology in order to facilitate its reuse and evolution. The proposed ontology has been implemented and evaluated using quality metrics. We also present a real use case study that demonstrates how the proposed ontology allows implicit knowledge generation
