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.
翻译:在本文件中,我们报告了研究数据联盟(RDA)研究数据联盟(ARDA)Agrismantics工作组的产出和通过情况,该工作组由一系列建议组成,目的是促进采用语义技术和方法,以在农业和营养领域实现数据互操作性,从2016年至2019年,该小组在信息技术和农业科学之间的交叉点聚集了研究人员和从业人员,研究语义资源生命周期的各个方面:概念化、版本、共享、标准化、服务、调整、长期支持。首先,工作组进行了景观研究,研究了农产食品中语义学的使用情况,随后收集了利用语义资源开发的案例 -- -- 一个通用术语,以包括词汇、术语、术语、理论、理论学等。由此产生的要求被综合为39个语义资源用户和开发者以及语义资源服务提供方的 " 暗 " 。我们认为,采纳这些建议将使农业食品科学参与必要的过渡,以利用数据生产、共享和再利用,并采用FAIR数据原则。论文中包括了数据领域要求的通过实例。