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39 Hints to Facilitate the Use of Semantics for Data on Agriculture and Nutrition
Copyright policy )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’.
Microsoft Academic Graph classification: Standardization Computer science Information technology business.industry business Knowledge management Field (computer science) Use case Semantic technology Semantics Conceptualization Reuse
Library of Congress Subject Headings: lcsh:Science (General) lcsh:Q1-390
agrifood data, FAIR data, semantics, semantic resources, ontology, vocabulary, terminology, thesauri, ontology repository, terminology service, [INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDE.ES]Environmental Sciences/Environmental and Society, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Agricultural robots, Agriculture, Data Science, Life cycle, Nutrition, Agricultural science, Crossing point, Data interoperability, Data production, Research data, Semantic resources, Semantic technologies, Working groups, Semantics, Agricultural robots, Agriculture, Data Science, Life cycle, Nutrition, Agricultural science, Crossing point, Data interoperability, Data production, Research data, Semantic technologies, Working groups, Computer Science Applications, Computer Science (miscellaneous), Settore ING-INF/05, Settore INF/01, [INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET], [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDE.ES] Environmental Sciences/Environmental and Society, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, Semantic web, agricultural data, agrifood data; FAIR data; semantics; semantic resources; ontology; vocabulary; terminology; thesauri; ontology repository; terminology service, Quantitative Biology - Other Quantitative Biology, Computer Science - Databases, Other Quantitative Biology (q-bio.OT), Databases (cs.DB), FOS: Biological sciences, FOS: Computer and information sciences
agrifood data, FAIR data, semantics, semantic resources, ontology, vocabulary, terminology, thesauri, ontology repository, terminology service, [INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDE.ES]Environmental Sciences/Environmental and Society, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Agricultural robots, Agriculture, Data Science, Life cycle, Nutrition, Agricultural science, Crossing point, Data interoperability, Data production, Research data, Semantic resources, Semantic technologies, Working groups, Semantics, Agricultural robots, Agriculture, Data Science, Life cycle, Nutrition, Agricultural science, Crossing point, Data interoperability, Data production, Research data, Semantic technologies, Working groups, Computer Science Applications, Computer Science (miscellaneous), Settore ING-INF/05, Settore INF/01, [INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET], [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDE.ES] Environmental Sciences/Environmental and Society, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, Semantic web, agricultural data, agrifood data; FAIR data; semantics; semantic resources; ontology; vocabulary; terminology; thesauri; ontology repository; terminology service, Quantitative Biology - Other Quantitative Biology, Computer Science - Databases, Other Quantitative Biology (q-bio.OT), Databases (cs.DB), FOS: Biological sciences, FOS: Computer and information sciences
Microsoft Academic Graph classification: Standardization Computer science Information technology business.industry business Knowledge management Field (computer science) Use case Semantic technology Semantics Conceptualization Reuse
Library of Congress Subject Headings: lcsh:Science (General) lcsh:Q1-390
- Université de Montpellier France
- University of Rome Tor Vergata Italy
- French National Centre for Scientific Research France
- Food and Agriculture Organization of the United Nations China (People's Republic of)
- UNIVERSITE PARIS DESCARTES France
- Université de Montpellier France
- University of Rome Tor Vergata Italy
- French National Centre for Scientific Research France
- Food and Agriculture Organization of the United Nations China (People's Republic of)
- UNIVERSITE PARIS DESCARTES France
- University of Montpelier
- Università degli Studi di Roma Tor Vergata
- Centre for Life United Kingdom
- Landcare Research New Zealand
- Manaaki Whenua - Landcare Research
- Food and Agriculture Organization of the United Nations (FAO)
- University of Montpellier France
- Food and Agriculture Organization of the United Nations
- Université de Montpellier (EPE)
- UNIVERSIDAD DEL PAIS VASCO/ EUSKAL HERRIKO UNIBERTSITATEA Spain
- Université Paris Diderot France
- Université Montpellier
- Boston College United States
- Food and Agriculture Organization of the United Nations Ghana
- UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATA
- National Research Institute for Agriculture, Food and Environment France
- Food and Agriculture Organization of the United Nations Italy
- UNIVERSITE DE MONTPELLIER 1
- Basque Centre for Climate Change Spain
- INRAE France
- Dips (Norway) Norway
- United Nations United States
- INRAE
- FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS FAO Italy
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’.