Making data FAIR could supercharge medicine development. FAIRplus is putting the principles into practice.
When it comes to big data, no other industry has as much at stake as the biopharmaceutical sector. Data from sources like health records, imaging, genome sequencing and wearables are potentially very valuable, and could drive massive improvements in European health systems. Making this data FAIR (findable, accessible, interoperable and reusable) is a simple message with wide appeal to researchers who spend an inordinate amount of time finding, processing, organising and curating data. FAIR data can speed up digital transformation, as it underpins analytical tools like AI and machine learning.
But it’s easier said than done.
Datasets identified for FAIRification
The FAIRplus project was set up to try out the process of ‘FAIRifying’ data from at least 20 IMI projects, as well as internal datasets from EFPIA companies. The first datasets were selected in 2019 based on set of specific criteria, from the IMI projects eTox, ND4BB, OncoTrack and resolute. In 2020, a further nine IMI datasets have so far been identified; these datasets have the potential to generate high societal impact, an important goal of FAIRplus. The datasets are from the IMI projects UltraDD, UBIOPRED, IMIDIA, RHAPSODY, EQIPD, ABIRISK, EBISC I, EBISC II, iPIE.
Image: the FAIRification process (zoom in for detail)
FAIR cookbook first version launched
The first version of the FAIR Cookbook has been made available. The FAIR Cookbook is an open-source collection of instructions (or ‘recipes’) for making life science data FAIR. The Cookbook is a collaborative effort of many FAIRplus partners and is coordinated by University of Oxford, Novartis and Bayer AG . It shows users how to FAIRify datasets, how to put the FAIR principles in practices, learn about levels and indicators of FAIRness; and the technologies and tools available to assess and improve FAIRness.
The FAIR cookbook is open source and anyone is invited to contribute.
Fellowship programme
The FAIRplus Fellowship Programme is a training programme in FAIR data management that will run for about 8 months, starting in April 2021. The programme will guide participants through a series of modules combining online learning, 'training on the job' and short face-to-face meetings. After completing the programme, people will have the confidence to lead, advise and initiate FAIR data processes in their respective companies and organisations.
The programme is designed on the basis of the FAIRplus FAIRification Process and consists of a number of compulsory modules corresponding to the steps in the process. At the end of the programme, Fellows will present their FAIRification project results to demonstrate their understanding of FAIR data management and their capability of acting as FAIR data experts.
Most fellows will be selected from FAIRplus partner organizations (including EFPIA participants), and ;imited spaces are reserved for applicants from outside the FAIRplus consortium, in particular from small and medium-sized enterprises (SMEs). Though fellowship programme is still under development and applications are not yet open, you can register your interest by signing-up to the mailing list to be notified once open.