FAIR
FAIR principles
In this module, we will discover the FAIR data principles and their main elements. At the end of this module, you should be able to:
Understand the FAIR principles and their relation to RDM
Identify the license that fits your research output
What are the FAIR principles?
The FAIR principles were created in order to maximize the reuse of scientific data, to promote best practices on Research Data Management and to enable Open Science. Applying the FAIR principles means to make research data Findable, Accessible, Interoperable and Reusable (Wilkinson et al. 2016).
- Findable means that others (both human and machines) can discover the data
- Accessible means that the data can be made available to others
- Interoperable means that the data can be integrated with other data and can be easily used by machines or in data analysis workflows.
- Reusable means that the data can be used for new research
These four principles should be applied (as much as possible) throughout the entire research cycle and they are closely interconnected with each other.
The FAIR Data principles are NOT:
- A standard. The FAIR principles need to be adapted and followed as much as possible by considering the research practices in your field. FAIR principles should be rather seen as progressive steps that help you make your data re-usable.
- Equivalent to Open Data. FAIR data does not necessarily mean openly available: it should be clear to others that the data exists and which steps they could take to potentially access the data.
- Applied using a particular technology or tool. There might be different tools that enable FAIR data within different disciplines or research workflows.
There are important elements to consider within your research workflows if you aim to make the data of your project FAIR:
Scripts of the videos copied or adapted from (Holmstrand et al. 2019).
Ecological Society of America journals have a data policy that requires sharing of:
Raw data and metadata used to generate tables, figures, plots, videos/animations
Novel code or computer software utilized to generate results or analyses
All methods or protocols utilized to generate the data, both existing (including references) and new methods/protocols
Derived data products
Test how aware of FAIR you are
Data and Code Licences
More resources on licences:
- Licenses for data, presentations and articles: Use the CC license chooser.
- Software: Choose a License. (For more detailed information, see ‘How to choose a software licence’).
- Note that apart from CC0, the licenses for data and code are different. Software licenses are more complex as software differs from data in the ways you can reuse it, as unlike data, software is executable.