No matter what kind of research you do or where you are in your career, sooner or later you will come across the FAIR principles for research data. Applying the FAIR principles means to make your research data findable, accessible, interoperable and reusable. Findable means that others can discover your data. Accessible means that your data can be made available to others. Interoperable means that your data can be integrated with other data or can be easily used by machines. Reusable means that your data can be used for new research. These four principles should be applied throughout the entire data life cycle and they are closely interconnected.

Please note applying the FAIR principles to your research workflows does not necessarily mean that you share your data openly. FAIR data is not the same as open data. Open data (fd.info Glossar) is data that can be freely used, shared and built on by anyone anywhere and for any purpose, while the FAIR principles provide a set of best practices for sharing data respecting any ethical, legal or contractual restrictions. If your data contains personal information or is subject to copyrights or intellectual property rights you must comply with regulations and protect your data from unauthorized access. But even if the data itself cannot be shared openly, you should create and publish a description of your data so that researchers with a relevant purpose can request permission to reuse the data.

This module introduces you to best practices for making your data FAIR. Following these best practices will help you to produce high quality data that can result in maximizing your research output and impact and enhancing your recognition as a researcher.