How to make data FAIR

Last changed: 02 July 2024
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The FAIR Principles are intended to serve as guidelines for improving the reusability of scientific data and play an important role in the work for open science.

FAIR is an acronym for Findable, Accessible, Interoperable, and Reusable. The principles were originally published in The FAIR Guiding Principles for scientific data management and stewardship (Wilkinson et al 2016) and have since been widely endorsed by research communities, governments, funders and publishers.

SLU's data management policy states that data from research and environmental monitoring activities at SLU should be FAIR to the greatest extent possible. Below you will find tips on how to make the data you are working with more FAIR, links to useful checklists, as well as information on the support available at SLU.

How to make data FAIR: four starting points

Plan data management with sharing and re-use in mind

Include data sharing in your project planning and data management plan from the outset.

Use sustainable and interoperable file formats

Ensure data accessibility by using open, widely used and machine-readable file formats that can be opened with standard or open software.

The Swedish National Data Service (SND) provides a list (link below) of criteria for file formats suitable for accessibility and long-term preservation, as well as a list of suggested formats for text, spreadsheets, audio, video, etc.

Think about what information will be needed to understand and re-use the data

Provide rich documentation of the data (metadata) at project, dataset and variable level to make it interpretable and reusable by others (both people and computers). When available, follow data management standards and guidelines established in your field of research, and use standard vocabularies and ontologies.

Publish data

Publish data in a trusted data repository that supports many of the FAIR principles. The Swedish National Data Service (SND), of which SLU is a member, has created a research data catalogue that supports many of the FAIR principles, including providing data with a persistent identifier (e.g. a DOI).

For legal or ethical reasons, it may not always be possible to publish data openly. In this case, the FAIR way is to still publish a description of the dataset (i.e. metadata) so that it can be discovered, but with restricted access.

Checklist for assessing data "FAIRness"

The following checklists can help you assess whether or not you are on the right track towards FAIR data, and also help you learn more about how to apply the principles:

  • How FAIR are your data? – a short checklist to help you “think FAIR” when it comes to data.
  • FAIR assessment tool – by filling out a form you can get an idea of the FAIRness of the data in your project and what steps could be taken to increase FAIRness.
  • FAIR Aware – this tool can help you to better understand the FAIR Principles and how making data FAIR can increase the potential value and impact of research data

Support at SLU

SLU Data Management Support (DMS) assists SLU employees with data management. If you have any questions about the FAIR principles (or anything else related to data management), please contact DMS via email ( or use our web form to book a Data Date.

Help us improve this guide

Did you find this guide useful? Is there anything missing, or is there another aspect of data management you would like guidance on? Please let us know!

Your feedback is important and will help us improve our website and our services. Send us an email ( or see our contact page for other ways to get in touch.

Read more

Summaries and explanations of the principles can be found on the websites of the Swedish National Data Service (SND) and the GO FAIR Foundation.