Data to Knowledge in Agronomy and Biodiversity

Description: D2KAB’s primary objective is to create a framework to turn agronomy and biodiversity data into knowledge –semantically described, interoperable, actionable, open– and investigate scientific methods and tools to exploit this knowledge for applications in science & agriculture. Agronomy/agriculture and biodiversity (ag & biodiv) face several major societal, economical, and environmental challenges, a semantic data science approach will help to address. We shall provide the means –ontologies and linked open data– for ag & biodiv to embrace the semantic Web to produce and exploit FAIR data.

Institution: University of Montpellier, CNRS, INRAE, ACTA, IRD, Stanford University


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Ontologies Used