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Until now, there has been no standard or generalisable process for the ‘FAIRification’ of any given dataset. As a consequence, over the course of the FAIRplus project, it was necessary to develop such a methodology so that a) any given dataset could be onboarded for FAIRification (IMI or EFPIA); b) passaged through a defined and repeatable process, and c) could be shown to be demonstrably more FAIR at the conclusion of such a process. Originally, we conceived of a process whereby a FAIRplus ‘FAIR-CMMI’ team would collaborate with IMI projects through a number of “Bring your own data” (BYOD) workshops. However, early in the project, we refined our strategy such that these teams were known as ‘squads’ and collaborated closely with IMI projects representatives on an ongoing basis, rather than in discrete one-off workshops, but otherwise executed precisely the same functions (see ‘Background’). We report here the development of a methodology, which has been iteratively refined over the lifetime of the project, to describe how the personnel responsible for the FAIRification will work, essentially providing a ‘user manual’ for those people engaged in the practical work. For the FAIRplus project we formed ‘squads’, inspired by but differing from ‘agile’ and ‘sprint’ practices. Here, we populated teams across project-organisational and reporting boundaries, based on required expertise for specific FAIRification tasks. Squads were fluid in population, with members switching as required for specific tasks, and tactically responsive, with additional teams ‘spun up’ or down as required. Squads worked in 3-monthly ‘release cycles’, targeting specific FAIRification tasks around which they would ‘swarm’. Accompanying the defined steps (e.g. inputs and outputs) of the FAIRification, we have developed a variety of checkpoints and templates to assist in developing a repeatable process. The squads have been an important mechanism in achieving FAIRplus project objectives, being heavily embedded in many major outputs, and acting as a point of contact with other FAIRification stakeholders such as RDMkit and Pistoia Alliance.
FAIR data, FAIR Cookbook, RDMkit, FAIRplus, Innovative Medicines Initiative, Pistoia Alliance, FAIRification
FAIR data, FAIR Cookbook, RDMkit, FAIRplus, Innovative Medicines Initiative, Pistoia Alliance, FAIRification
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