Summary
This paper presents Rothamsted's institutional approach to improving data stewardship of their long-term agricultural experiments through adoption of FAIR data principles. The authors discuss practical challenges in refactoring and describing existing legacy datasets and establishing meaningful connections between datasets, emphasising that active data stewardship is essential to realise the scientific potential of these unique, irreplaceable time-series resources for addressing food security and climate adaptation questions.
UK applicability
Directly applicable to United Kingdom agricultural research infrastructure and policy. Rothamsted's experience and recommendations for FAIR data implementation are immediately relevant to UK agricultural science institutions managing long-term experimental datasets and seeking to enhance their research impact and accessibility to the wider scientific community.
Key measures
Data accessibility, FAIR data adoption, dataset linkages, data stewardship approaches for legacy agricultural experiment data
Outcomes reported
The paper discusses approaches to implementing FAIR data principles for long-term agricultural experiment datasets at Rothamsted, addressing challenges in refactoring legacy data and establishing meaningful linkages between datasets. It reports on data stewardship strategies to increase accessibility and reuse of time-series data for understanding soil health and sustainable crop production.
Topic tags
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.