FAIR Data

One of the goals of data curation is to make the curated data FAIR or adhere to the FAIR principles.
The FAIR principles were first introduced in 2016 in The FAIR Guiding Principles for scientific data management and stewardship paper.

The FAIR principles can be summarized in the following four points:

• Findable

• Accessible

• Interoperable

• Reusable

Further information and the full definition of the FAIR principles can be found on GO FAIR website, specifically on the FAIR Principles page.

The FAIR principles have become very important as they have been embraced by many funding agencies and research institutions, in the effort to increase the value of the data and to further increase the re-use of the data.

In 2020, a new and complementary set of principles, named TRUST, have emerged and formalized in The TRUST Principles for digital repositories paper.

The TRUST principles are geared towards the repositories holding the data and are:

• Transparency

• Responsibility

• User Focus

• Sustainability

• Technology

Our experience has taught us that performing data curation correctly and aiming for high quality and optimal data FAIRness, will also help in having repository TRUSTness, and lead to an increased scientific output.