Authors:
Caterina Caracciolo, Sophie Aubin, Clement Jonquet, Emna Amdouni, Romain David, Leyla Garcia, Brandon Whitehead, Catherine Roussey, Armando Stellato, Ferdinando Villa
Abstract:
In this paper, we report on the outputs and adoption of the Agrisemantics Working Group of the Research Data Alliance (RDA), consisting of a set of recommendations to facilitate the adoption of semantic technologies and methods for the purpose of data interoperability in the field of agriculture and nutrition. From 2016 to 2019, the group gathered researchers and practitioners at the crossing point between information technology and agricultural science, to study all aspects in the life cycle of semantic resources: Conceptualization, edition, s (...)
In this paper, we report on the outputs and adoption of the Agrisemantics Working Group of the Research Data Alliance (RDA), consisting of a set of recommendations to facilitate the adoption of semantic technologies and methods for the purpose of data interoperability in the field of agriculture and nutrition. From 2016 to 2019, the group gathered researchers and practitioners at the crossing point between information technology and agricultural science, to study all aspects in the life cycle of semantic resources: Conceptualization, edition, sharing, standardization, services, alignment, long term support. First, the working group realized a landscape study, a study of the uses of semantics in agrifood, then collected use cases for the exploitation of semantics resources a generic term to encompass vocabularies, terminologies, thesauri, ontologies. The resulting requirements were synthesized into 39 hints for users and developers of semantic resources, and providers of semantic resource services. We believe adopting these recommendations will engage agrifood sciences in a necessary transition to leverage data production, sharing and reuse and the adoption of the FAIR data principles. The paper includes examples of adoption of those requirements, and a discussion of their contribution to the field of data science. © 2020 The Author(s). Brandon Whitehead acknowledges with thanks the support of the CABI Development Fund. CABI is an international intergovernmental organization and we gratefully acknowledge the core financial support from our member countries (and lead agencies) including the United Kingdom (Department for International Development), China (Chinese Ministry of Agriculture), Australia (Australian Center for International Agricultural Research), Canada (Agriculture and Agri-Food Canada), Netherlands (Directorate-General for International Cooperation), and Switzerland (Swiss Agency for Development and Cooperation). See https:// www.cabi.org/about-cabi/who-we-work-with/key-donors/ for details. Sophie Aubin, Clement Jonquet, Emna Amdouni, Romain David and Catherine Roussey were supported, in part, by the French National Research Agency (ANR) Data to Knowledge in Agronomy and Biodiversity (D2KAB – www.d2kab.org – ANR-18-CE23-0017). Romain David was partly supported by the EPPN2020 project (H2020 grant N°731013), the EOSC-Life european program (grant agreement N°824087), the ‘Infrastructure Biologie Sante’ PHENOME-EMPHASIS project funded by the French National Research Agency (ANR-11-INBS-0012) and the ‘Programme d’Investissements d’Avenir’.
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