The latest news from The Hyve on Open Source solutions for bioinformatics

Recent Posts

Four quick tips to start making your data FAIR

August 15, 2017 | By Jarno van Erp

Making your data “FAIR” is something you hear more and more. In the age of creating large volumes of data and a variety of datatypes, and after experiencing data management difficulties when running large scale projects, researchers realized that making their data Findable, Accessible, Interoperable and Reusable is becoming a necessity.

So you want to follow best practices of data management and want to make your data FAIR.Where do you start? With these four quick and easy tips you can start your FAIR journey today.

 FAIR data dtl image

Describe the origin of your dataset in the metadata

A lot of datasets lack a description of their origin. Where is the data created? How? and by whom? Is the data processed? Or is it the raw dataset? These are important questions for other researcher which need to be answered before they can actually use your data for their research. A genomic dataset which is created with the Illumina Next Generation Sequencing platform is different from one that is created with a Roche sequencer. Maybe your pipeline is only compatible with a specific machine. Describing this in the metadata, a file which contains all the information about your dataset (so basically data about your data), will greatly help others with filtering on relevant and usable datasets. A good example to store this information is a readme file which you add next to your dataset.

Describe purpose of your dataset in the metadata

Why is this dataset created? What was your goal when you created this dataset? A lot of datasets are created for a single purpose. FAIRifying your data ensures that you start thinking about other possible purposes or applications for your data. Maybe while thinking about these purposes you can think of someone who can also benefit from your data? Sharing is caring.

FAIR survey 


Check out our FAIR survey quiz!


Add license if needed 

Is your data freely available for use? Or for what purposes can it be used? Maybe you do not want it to be used for a publication, but it can still help other researchers with narrowing down their searchfield. Or maybe you want to get something in return for the use of your dataset. By adding a license to your data, you ensure that no one can legally use your data for purposes for which it is not intended. Some examples for these licenses are:


Each license comes with its own benefits. For example, the Public Domain Dedication and License is highly customizable to what you want your data to be used for, while the Open Database License ensures your work gets attributed to you and not someone else.


Store your data in a FAIR way

When you have gone through all the steps mentioned above, you of course want to be able to share your amazing FAIR dataset with others in an easy way. Storing your data in places that do not require login or review by a data access committee decrease the hassle it takes to download data, thus making it easily accessible. Some examples of these storage places are:

And one extra tip: SCREAM IT FROM THE ROOFTOPS. Let other researchers know that your data is open and available. Data for them, citations for you: It’s a win-win situation.