Who should read the FAIR Cookbook?

Recipe metadata

identifier: RX.X

version: v1.0

Difficulty level

Reading Time

15 minutes

Recipe Type

Background Information

Executable Code


Intended Audience

Principal Investigators

Data Managers

Data Scientists


The FAIR Cookbook for IMI participants

The aim of the FAIR Cookbook is to reach as wide an audience as possible to improve the understanding of the FAIR principles, explain how to implement them and evaluate FAIR levels but also to provide practical guidance and hands-on, practical examples.

But it is also true that, owing to the nature of the IMI FAIRPlus project, the intent is also to act as support material for IMI funded projects in order to guide awardees in either complying with the best practices and recommendations made by the funding agencies or simply to familiarize themselves with the FAIR principles.

The content of the FAIR Cookbook is a collection of birds-eye view pieces explaining the tenets of FAIR compliant data management practicesw and applied pieces offering a deep dive in technical aspects of FAIR data management.

The key point is that all these pieces are the results of close interactions with a number of IMI projects, pasts or ongoing, therefore covering a range of scenarios which we hope will be meaningful to IMI awardeeds or applicants.

If you are principal investigator of an IMI grant or applying to one

If you are in such capacity, first congratulations for the successful application or for assembling together a consortium and applying. For you, the most important sections for you will probably be found in the pieces detailing the following points:

If you are a data manager

The task befalling on the data manager in an IMI project varies greatly but can be quite daunting. It very much depends on the context of the project. Indeed, whether the project's focus is Clinical Trials (IMI Oncotrack) or Epidemiological studies (such as IMI EHDEN) or Molecular aspects drugs or targets (IMI Resolute), different requirements and constraints will need to be taken into account. But another variable also matters: the overall consortium position in keeping with data sharing. Since IMI2, all funded projects are by default included in the Open Data Release Pilot, but consortia can decide to opt out at any time. While this decision has a profound impact on the accessibilty of the data, for all other aspects of data management, the FAIR Cookbook still provides useful guidance.

If you are a data producer

As a data producer, you may find yourself with a new sets of data management requirements or you may be requested to provide descriptive information about the nature and technical characteristics of specific data acquisition modalities. The FAIR Cookbook provides guidance and organizing principles for assisting IMI data managers as they establish the data management plan.

If you are a data controler

If dealing with sensitive, patient centric data, the data controler will be in charge of handling data access requests and monitoring who gains access to data generated by the consortium.

The requirements vary greatly depending on the various EU country legislation. The FAIR Cookbook provides general recommendations in line the European Union GDPR regulation.

If you are an IMI Grant Officer

The FAIR Cookbook from an EFPIA standpoint

The FAIR principles are having a massive impact on the perception of how essential good data management is in preserving data assets. This has resonated particularly in the Pharma industry, which has been looking at how to apply the principles not only to research data but also to a range of business processes in the industry. Therefore, from an EFPIA standpoint, the FAIR Cookbook provides critical insights into the following:

While the FAIR Cookbook can not cover all business area, by providing hands on recipes applied to research data, the FAIR Cookbook offers unique insights into operation steps and allows a good appreciation of resources needed, which in turns can inform decision makers in charge of estimated the costs of applying the FAIR principles to other domains. In short, the FAIR Cookbook helps with evaluating the costs of porting the FAIR principles to a new business area.

The FAIR Cookbook from a Small and Medium Entreprise.

Small and medium entreprises (SMEs), which operate in IMI projects and which often cooperate with EFPIA partners, are often spin outs from academic lab. They often offer agility, reactivity and innovation in supporting business processes. The capabilities offered by SMEs range from CRO, curation services, literature search, ontology developement. For SMEs, the FAIR Cookbook is an opportunity to highly their offerings but chiefly it is the means to bolster their practices and demonstrate their ability to deliver FAIR compliant services.

Examples can be found in the following contributions by companies such as the Hyve, Ontoforce or ITTM for instance.


The FAIR Cookbook will appeal to diverse audiences. While the FAIR Cookbook authors worked primarily to assist EU IMI funded applicants and awardees, providing guidances and examples rooted in experience garnered while working with specific IMI projects, the lessons learned along the way as well as the procedures developed can be of use to many. This is what we have introduced in this section.

By identifying a number of functions as personas, the aim is also to engage with the community and seek feedback, contributions and comments. The authors therefore encourage readers to send requests and feedback using the following means:

  • log a recipe request using the FAIR Cookbook issue tracker
  • rate the FAIR Cookbook and each of its recipes
  • contribute content by sending a recipe
  • contact us using


  1. Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).
  2. The FAIR Cookbook.


Name Affiliation orcid CrediT role
Philippe Rocca-Serra University of Oxford, Data Readiness Group 0000-0001-9853-5668 Writing - Original Draft
Susanna Assunta Sansone University of Oxford, Data Readiness Group 0000-0001-9853-5668 Writing - Original Draft