Investigating FAIR data principles compliance in horizon 2020 funded Agri-food and rural development multi-actor projects

CONTEXT: The agri-food and rural development sector in Europe is undergoing digitalization, and therefore becoming increasingly data-dependent. However, limited experience in implementing Findable, Accessible, Interoperable, and Reusable (FAIR) data principles has restricted knowledge sharing and reusability. OBJECTIVE: This study aims to investigate the existing FAIR Data Management practices in the agri-food and rural development sector by assessing the FAIRness of project outputs from recent H2020-funded Multi-Actor Projects (MAPs). METHODS: We conducted a FAIRness assessment of project outputs using both semi-automatic and manual framework, and we also carried out a comprehensive review of the data sharing practices among selected MAPs. RESULTS AND CONCLUSIONS: Of the investigated MAPs, <10% have achieved FAIR compliance and applied FAIR data management practices. The measured FAIRness of project products, including journal articles, conference papers, and books, is higher than that of other product types such as videos, audios, and presentations. SIGNIFICANCE: The study highlights the critical need for standardizing the adoption of FAIR data principles and data management practices across both the agri-food and rural development sector but also across bureaucratic data management throughout Europe more widely. Such a change would facilitate broader utilization and re-use of MAPs outputs and results, enhancing decision-making and agri-food and rural development practices.