What are the FAIR data principles, and how can they benefit you?

Find out how you can make your data more discoverable, to increase the visibility of your research.

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What are the FAIR principles?

The FAIR principles were developed to support the discovery and reuse of research data. FAIR stands for:

Findable

Accessible

Interoperable 

Reusable

2021 marks five years since the FAIR data principles were published in the data journal Scientific Data

How can the FAIR principles help me?

If your research data are findable, accessible and reusable, they can be accessed by researchers in different institutions, different regions, and even different disciplines. Not only can sharing data in this way be valuable for science, it can also benefit you and your career. Sharing research data can lead to:

  • More citations of your published research articles
  • Greater discoverability and enhanced visibility
  • Credit for your work, helping you to gain recognition.

Read more about the benefits of research data sharing. 

Are other researchers making their data FAIR?

If you haven’t heard of the FAIR principles before, you’re not alone. In 2020 we surveyed nearly 5,000 researchers in over 190 countries about the FAIR principles, for the State of Open Data survey, and found that 39% of survey respondents had never heard of the FAIR principles before taking the survey. 

However, more and more researchers are becoming aware of the FAIR principles. In 2020, a total of 61% of researchers had heard of the FAIR principles – up from 40% in 2018. Since 2017 there is also a positive trend in how well researchers view their data as complying with FAIR.

How can I start applying the FAIR data principles?

Here are a few simple ways to get started.

  • Deposit your data in a repository. Data which are archived to a data repository are more likely to be accessible for the longer term. They are also easier to find, to reuse and to cite. Learn more and get started.
  • Include a data availability statement (DAS) in your manuscript. This is a short narrative statement explaining to readers how and where your data can be accessed. Read our useful tips to get started.
  • Cite the data you have used, and that you have generated in your study. Acknowledging and building on previously published research is a key part of scholarly activity. Learn more about data citation 

Learn more about FAIR

Here are some useful links:

What does the future of FAIR look like? Read our white paper with expert opinions on the impact of the FAIR principles on a global pandemic, ethical considerations for research data sharing, and more. 

Do you have a question about research data? 

Get free help and advice on sharing your research data: visit our research data help desk.

Photo by Markus Winkler on Unsplash

Varsha Khodiyar, Ph.D

Data Curation Manager, Springer Nature

As part of the Research Data team working on research data publishing initiatives at Springer Nature, Varsha leads the curation team at Springer Nature, and contributes to the design, development and delivery of Springer Nature’s research data training workshops. She is also responsible for curating and maintaining the Scientific Data and Springer Nature recommended repository lists. Varsha is an Executive Advisor of FAIRsharing.org, a member of CODATA’s International Data Policy committee, programme chair for the Better Research through Better Data conference series, and a co-author of the TRUST principles.