This website will take you on a deep dive into the subject matter of FAIR research data. Over the course of about two hours, it will show you that FAIR is not a time-consuming administrative mantra, but a set of principles that makes your research efficient, transparent and sustainable. Working in line with the FAIR principles to make your data more FAIR will improve your research data management and safeguard your research data for the future.
The aim here is to explore six key FAIRification practices, and show how they apply to your research. You will meet researchers working across Denmark in different research disciplines who share their thoughts and experiences on how they make their research data more FAIR.
Go through the course all in one sitting, or come back to each FAIRification practice as needed, it's up to you.Get started
The FAIR principles stand for making your research data Findable, Accessible, Interoperable and Reusable. Start the course here for an introduction to FAIR and FAIRification practices and ensure you can make full use of this How to FAIR website.
If you have not heard about the FAIR principles before, you may also want to take our 60-minute e-Learning introduction to Research Data Management and FAIR.
Making your research data FAIR could help to maximise your research impact and help peers and your ‘future self’ understand your research projects and data. But don’t just take our word for it. Hear more from two of the authors of the FAIR principles on the advantages of making research data FAIR here.Read more
This is where this How to FAIR website takes off. This section will show you how you can make your research data more FAIR by taking you through six key FAIRification practices. You will be shown short video clips of researchers in Engineering, Humanities, Health Sciences, and Social Sciences. Recommendations, standards and examples are given for quantitative, qualitative and sensitive data. These will guide you through the steps you can take before, during and after your own research project to help you produce FAIRer research data in a way that makes sense for you.Read more
Are you a FAIR-apprentice or a FAIR-master?
Test your knowledge of the FAIR principles here. Three quizzes on qualitative, quantitative and sensitive quantitative data will take you through example research situations, where the best practices for FAIR may clash with what is practical or possible in reality. Choose the quiz that is most relevant for you – or test yourself on all three.