The FAIR Principles
The FAIR Principles
FAIR is an acronym for Findable, Accessible, Interoperable and Reusable. Each word represents principles that are a set of guidelines which aim to increase the value and impact of research by promoting good data management practices. These practices enable data to be effectively shared, discovered, and reused by both humans and machines.
An important guiding line when working with FAIR principles is to make data "as open as possible and as closed as necessary”. While it is not possible to make all data available for the public, it is still very much relevant to work with the principles. Also, FAIR is a continuum – meaning you can't be either FAIR or not FAIR. You can start by working with a few of the principles and later dive more into the remaining principles.
Benefits of working with the FAIR Principles
- Increased visibility and impact: Your research becomes more accessible, interoperable and transparent which can lead to increased exposure, recognition, citations and create opportunities for new collaborations.
- Improved data quality: The FAIR principles helps promote better data documentation and organization which leads to increased data quality.
- Time-saving: By making data easier to find and reuse, researchers saves time and resources that otherwise would have been used for duplicating existing data.
- Awareness on compliance: Working with the FAIR principles helps ensure that your data handling practices comply with international and institutional standards.
FAIR training materials
Here you will find a selection of relevant resources where you can learn more about the FAIR principles.