The FAIR Cookbook - the essential resource for and by FAIR doers

Abstract

The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an open, online resource of hands-on recipes for “FAIR doers” in the Life Sciences. Created by researchers and data managers professionals in academia, (bio)pharmaceutical companies and information service industries, the FAIR Cookbook covers the key steps in a FAIRification journey, the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges to achieve and improve data FAIRness. Part of the ELIXIR ecosystem, and recommended by funders, the FAIR Cookbook is open to contributions of new recipes.

Reanalysis of single-cell RNA sequencing data does not support herpes simplex virus 1 latency in non-neuronal ganglionic cells in mice

“…As we had to specifically request that the scRNAseq datasets be made available to us post-publication (and these data are not linked to the publication on the journal website), we feel obligated to reiterate the FAIR (Findability, Accessibility, Interoperability, and Reusability) data principles. These guidelines provide a framework to increase transparency and promote the reuse of data by the scientific community ( 47 , 48 ), which in turn will accelerate scientific discoveries and provide the opportunity for dataset correction by other analyses. Many funding agencies, universities, and scientific journals aim to promote open science by recommending or requiring researchers to adhere to the FAIR principles and open-access publishing.…”

Ontologies for increasing the FAIRness of plant research data

“…One common theme apparent throughout the ontologies covered within this review is the importance of open and collaborative efforts for increasing the FAIRness of data. It is widely accepted by the greater scientific community that making data more FAIR will greatly benefit data reproducibility and data management practices ( Rocca-Serra et al., 2023 ). However, the actual task of making data FAIR remains costly and time consuming, hindering progress.…”

Metadata integrity in bioinformatics: Bridging the gap between data and knowledge

“…After the original draft, each of the four principles have been refined in the 2016 article introducing the FAIR Guiding Principles by Wilkinson et al [19] , which are also part of the introduction of the FAIR Cookbook by Rocca-Serra et al (2023) [20] , and summarized in Table 1 .…”