Making your data FAIR

When you are planning a research project, you should plan for collecting, storing and sharing research data. This is the ideal time to consider how to make your data more findable, accessible, interoperable and reusable via the FAIR principles.

Why you need to understand FAIR principles

Your research publications and their underpinning data are likely to exist for some considerable time online, so you need to ensure your data are created with longevity in mind. Giving the research community access to your data facilitates knowledge discovery and improves research transparency and reproducibility.

In 2016 the FAIR data mission to optimise data sharing and reuse by humans and machines,  resulted in the publication of The FAIR Guiding Principles for scientific data management and stewardship, published in "Scientific Data".

The FAIR principles describe how research outputs should be organised so they can be more easily accessed, understood, exchanged and reused. Funding bodies and research organisations promote FAIR data to maximise the integrity and impact of their research. 

Support and guidance

The Library Open Research and Publishing team can provide support and guidance on meeting FAIR expectations.  Perhaps you want to learn more about appropriate documentation to contextualise data, or creation of metadata, use of community defined terminologies, assigning persistent identifiers and clear licensing, or the choice of file formats, all of which are essential for digital preservation.

Steps to becoming FAIR

Make your data more:

Findable

Findable data are data deposited in reputable and trusted repositories with appropriate metadata that can be read by humans and machines. At Dundee, data deposited with Discovery are harvested by both Open Access tools and by search engines.

Accessible

When you publish your research findings include a DAS or data access/availability statement directing readers to the location of your data and describing how they can request or obtain access.

Interoperable

The file formats you select when collecting and sharing your data will determine whether the data can be used by others. Using widely adopted languages, standards and formats will make possible the combination and comparison of your data with other datasets. There are other identifiers you can associate with your data to assist with its interoperability such as your ORCID or a persistent identifier for your data, e.g. a DOI.  There are free tools that can assist you with file migration to ensure your data are machine- interoperable. Take a look at this software available from AppsAnywhere, Pandoc | University of Dundee

Reusable

The FAIR principles were created with the aim of improving the reuse and reproducibility of data. Data can only be reused if it is made available with sufficient contextual information. A ReadMe file providing context and provenance can serve as a set of instructions for recreating, to the extent possible, the conditions in which data were created or collected. Licensing details will inform users what they are allowed to do with the data, e.g. whether they can repurpose or build on your work.

Resources

There are lots of resources to help you on your path to FAIR:

• The ’FAIR Principles in a nutshell’ are summarised in this document produced by FAIRsharing.org
• Create a data management plan
• Where to store your data at Dundee
• The University Repository Discovery can be used to publish your data, follow the Depositing your research data guide
• Create Data Access Statements
• Try the FAIRAWARE tool to measure how well you are doing

You can request further support by emailing [email protected].

Licensing

This page has borrowed from and adapted Edinburgh University’s Quick Guide MAKING YOUR RESEARCH DATA ‘FAIR’, a document which adapted content produced by the GO FAIR initiative (CC BY), under the Creative Commons Attribution 2.5 UK: Scotland License.