D2KAB project Data Management Plan

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. To do so, we will develop new original methods and algorithms in the following areas:
data integration, text mining, semantic annotation, ontology alignment and linked data
exploitation.

D2KAB project brings together a unique multidisciplinary consortium of 12 partners to
achieve this objective: 2 informatics research units (LIRMM, I3S); 6 INRA/IRSTEA/IRD applied
informatics research units (URGI, MaIAGE, IATE, DIST, TSCF, DIADE) specialized in agronomy
or agriculture; 2 labs in biodiversity and ecosystem research (CEFE, URFM); 1 association of
agriculture stakeholders (ACTA); and 1 partnership with Stanford BMIR department. Each of
the project driving scenarios (food packaging, agro-agri linked data, wheat
phenotype, ecosystems & plant biogeography) will have a significant impact and
produce concrete outcomes for ag & biodiv scientific communities and socio-economic
actors in agriculture.