FAIR Cookbook

Created by researchers and data managers professionals, the FAIR Cookbook is an online resource for the Life Sciences with recipes that help you to make and keep data Findable, Accessible, Interoperable and Reusable (FAIR).

Turning FAIR into practice

The FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. However, the FAIR Principles are aspirational and generic. The FAIR Cookbook guides researchers and data stewards of the Life Science domain in their FAIRification journey; and also provides policymakers and trainers with practical examples to recommend in their guidance and use in their educational material.

Learning objectives

The FAIR Cookbook provides recipes for you to learn: how to FAIRify datasets, 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 FAIRness.

The recipes

The FAIR Cookbook organizes the recipes according to the FAIR elements, audience type (your role), reading time, and level of difficulty. The FAIR Cookbook is a live resource, meaning that content is added and improved, iteratively, in an open manner, therefore bear with us if several sections are work in progress! Below there are links to some key recipes, click on them to explore their content; otherwise use the main menu on the left-hand side to browse all the current recipes.


The FAIR Cookbook is developed by a thriving community of Life Science professionals, in the academia and the industry sectors, including members of the ELIXIR community. Funded by the IMI FAIRplus project, a private-public partnership, the FAIR Cookbook is a community-driven resource that is being populated and improved, iteratively, in an open manner. If you want to participate, join us and contribute, or contact us at fairplus-cookbook@elixir-europe.org

How to cite it

The FAIR Cookbook: a deliverable of the FAIRplus project (grant agreement 802750), funded by the IMI programme, a private-public partnership that receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA Companies.