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Published April 30, 2024 | Version v2
Output management plan Open

D2KAB project Data Management Plan

  • 1. ROR icon National Research Institute for Agriculture, Food and Environment
  • 2. ROR icon University of Montpellier
  • 1. ROR icon National Research Institute for Agriculture, Food and Environment
  • 2. INRAE Provence-Alpes-Cote d'Azur
  • 3. ROR icon Centre d'Écologie Fonctionnelle et Évolutive
  • 4. ROR icon Université Côte d'Azur
  • 5. Institut National de Recherche pour l'Agriculture l'Alimentation et l'Environnement Centre Occitanie-Montpellier
  • 6. Institut de recherche pour le développement France-Sud
  • 7. Institut National de Recherche pour l'Agriculture l'Alimentation et l'Environnement Centre Île-de-France-Versailles-Grignon
  • 8. ROR icon Montpellier Laboratory of Informatics, Robotics and Microelectronics

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. 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.

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24-04_DMP_D2KAB_v2_opidor_per_product.pdf

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Additional details

Funding

D2KAB – Data to Knowledge in Agriculture and Biodiversity ANR-18-CE23-0017
Agence Nationale de la Recherche