The standardisation and accessibility of plant data is a major challenge for agricultural research. MIAPPE, which was developed as part of the transPLANT and ELIXIR-EXCELERATE projects, has made a decisive contribution to unifying data capturing. Also, the FONDUE Implementation Study facilitated the integration of phenotypic and genotypic data.
Nevertheless, challenges persist in achieving full FAIRness of plant data. The development of guidelines and best practice documents within the Commissioned Service INCREASING has improved this. However, further enhancements are required, such as providing additional documentation and reference datasets.
To address these needs, it is important to assess the practical effort required to FAIRify datasets using MIAPPE, ISA, ARC and RO-Crate standards. The idea is to provide biologist-friendly data documentation and at the same time introduce machine-actionable formats for bioinformaticians to use. A further challenge arises from the scattered nature of the information, as there is no single resource on which all the information is collated.
In HARVEST, we aim to address these challenges by FAIRifying datasets (DROPS, AGENT) using the latest version of MIAPPE as a basis, which now covers more diverse and complex use cases. This process will include enriching the MIAPPE documentation in particular with example datasets, updating training material and refining mappings to other interoperable formats such as BrAPI, Bioschemas and ISA-Tab/JSON. We will also establish links using FAIDARE to repositories such as EMBL-EBI EVA, e!DAL-PGP, recherche.data.gouv and Zenodo, to enhance data sharing and reuse opportunities. An extension of the RDMkit Plant Sciences pages will be implemented to serve as a primary hub for information on FAIRification of plant data. Furthermore, we will be consolidating resources and improving accessibility through direct linking to the original web resources and recipes, also adding Jupyter notebooks to the FAIR Cookbook where possible.
Co-lead
Sebastian Beier
