1. The Ontologies Community of Practice: An Initiative by the CGIAR Platform for Big Data in Agriculture
- Author
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Pankaj Jaiswal, Rosemary Shrestha, Ibnou Dieng, Erick Antezana, Julian Pietragalla, Cyril Pommier, Felix Shaw, Sandrine Auzoux, Abhishek Rathore, Esther Dzale Yeumo, Afolabi Agbona, Alexandra Lafargue, Sabina Leonelli, Christopher J. Mungall, Brian King, Lukas A. Mueller, Elizabeth Arnaud, H. Juarez, Brian Chiputwa, Laurel Cooper, Leroy Mwanzia, Enrico Bonaiuti, Medha Devare, Gideon Kruseman, Jacqueline Muliro, Guillaume Bauchet, Marie-Angélique Laporte, Soonho Kim, David A. Lyon, Kevin A. T. Silverstein, Céline Aubert, Olatunbosun Obileye, Pier Luigi Buttigieg, Naama Menda, V. Hualla, Jeffrey Detras, and Roma Rani Das
- Subjects
2. Zero hunger ,0303 health sciences ,0209 industrial biotechnology ,business.industry ,Big data ,02 engineering and technology ,15. Life on land ,Ontology (information science) ,computer.software_genre ,Data science ,Knowledge sharing ,Metadata ,03 medical and health sciences ,020901 industrial engineering & automation ,Community of practice ,Data quality ,Controlled vocabulary ,business ,computer ,030304 developmental biology ,Data integration - Abstract
Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labelling to be interoperable. As recommended by the FAIR principles, data, labels and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no agreed full set of ontologies recommended for data annotation across agricultural research disciplines, which may span genetics, environment, agroecology, biology and socioeconomics. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant ontology expertise. This CoP aims to stimulate knowledge sharing and directly support platform development teams by producing ontologies or contributing missing concepts, recommending best practices and identifying mitigation solutions when gold standard datasets are difficult to attain.
- Published
- 2020
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