Ben Wills1,2, Julie Parker1, Nathan Robinson1, Megan Wong1
1 Centre for eResearch and Digital Innovation, Federation University Australia, Ballarat, Vic, 3350, Australia. www.cerdi.edu.au, 2 Corresponding author: email@example.com
Across Australia’s arable landscapes, thousands of crop trials have been conducted to improve the profitability and sustainability of Australian grain production. Although there have been significant steps to make knowledge gained from trials available to users, there is the potential to further support the development of next generation data models and knowledge products by integrating trials from disparate sources by adhering to FAIR principles of data management. That is, making data: findable, accessible, interoperable and reusable. This research explores whether Online Farm Trials increase the FAIRness of agricultural grains trial datasets through a comparison of the trial data capture and handling practices of organisations whose datasets are not discoverable through Online Farm Trials (OFT) (N = 50) with the FAIRness of the datasets discoverable through OFT. The findings demonstrate that OFT is helping to make the results of Australia’s grains trials more FAIR to the users of trial data, and suggests a number of improvements to the FAIRness of trial datasets, foremost through the use of machine-readable metadata.