Cultivating Semantics for Data in Agriculture and Nutrition. Recommendations from the RDA Agrisemantics Working Group.

The poster reports on results of the activities carried within the Agrisemantics Working Group of the Research Data Alliance (RDA) (https://www.rd-alliance.org/groups/agrisemantics-wg.html). The group gathers together researchers and practitioners at the intersection between semantic technologies and agriculture. As a highly interdisciplinary domain, agriculture needs semantics as a possible response to data findability and interoperability. Yet, semantics remain unevenly adopted in this community partly because of unawareness, skill gaps, and lack of tooling usable by non-semantics experts to edit, map, and use semantic resources. The Agrisemantics WG has recently produced a set of recommendations to facilitate the use of semantics for Data on Agriculture and Nutrition, with the ultimate goal of improving data interoperability, discoverability and reusability. Based on an open dialog with a community of researchers and practitioners of semantic technologies, we have identified four basic points to address in order to make their use more widespread and effective. First, foster the development of a generic web-based framework to work with semantic resources. Such a framework should be adaptable according to: the task to perform, the domain of interest, the coverage within the domain, and the user competencies. Second, promote initiatives that support the reuse of existing resources, or their alignment. Third, promote the adoption of common metadata models for the description of semantic resources and alignments, and the use of global identifiers to facilitate reuse, usage tracking, and proper citation. Finally, promote courses on semantics and integrate them into curricula in all relevant disciplines-ie. computer sciences, data & information management and analytics, agronomy, bioinformatics, etc. These high level recommendations are further specified and translated into specific recommendation related to roles and activities in: data stewardship (or data management), software development, semantics professionals, and policy makers. Many of our recommendations either address or indirectly contribute to the implementation of FAIR principles. Our poster will show higher level recommendations together with the specific recommendations.