Good research data management is not a goal in itself, but rather a key element leading to knowledge discovery and innovation. The FAIR principles may be considered as guidelines and good practices for both human scholars and machines in order to enhance the findability, accessibility, interoperability and reusability of data.

Findable

F1. (Meta)data are assigned a globally unique and eternally persistent identifier

F2. Data are described with rich metadata

F3. (Meta)data are registered or indexed in a searchable resource

F4. Metadata specify the data identifier

in order to be reusable, (meta)data should be easy to find for both humans and computers.

automatic and reliable retrievement of datasets is THE result of THE correct use of PERSISTENT identifiers (PID), such as DOI (digital objecT identifier), Handle or URN (uniform resource name). descriptive metadata must be stored in data repositories so that (meta)data can be indexed by machines too.

Accessible

A1.  (Meta)data are retrievable by their identifier using a standardized communications protocol

A1.1. The protocol is open, free, and universally implementable

A1.2. The protocol allows for an authentication and authorization procedure, where necessary

A2. Metadata are accessible, even when the data are no longer available

(meta)data should be accessible by humans and machines possibly followING authentication and authorisation procedureS AS WELL AS standardised communication protocolS.

(meta)data should persist over time through THE USE OF repositories and be EASILY RETRIEVABLE on the internet. metadata sHould BE KEPT accessibLE even if data are non-oa.

Interoperable

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.

I2. (meta)data use vocabularies that follow FAIR principles.

I3. (meta)data include qualified references to other (meta)data.

data usually need to be integrated with other data, applications or workflows for analysis, storage, and processing. Data formats AND DATASETS must therefore be open and understandable by different SYSTEMS.

interoperability should be applied to metadata as well. fOR INSTANCE METADATA SHOULD ADOPT A STANDARD LANGUAGE IN COHERENCE WITH THE ONE USED BY THE MAIN INTERNATIONAL INDEXING SERVICES.

Reusable

R1. (meta)data have a plurality of accurate and relevant attributes.

R1.1. (meta)data are released with a clear and accessible data usage license.

R1.2. (meta)data are associated with their provenance.

R1.3. (meta)data meet domain-relevant community standards.

both metadata and data must be described and documented in the best possible way.

the reuse of metadata and data should be declared AND THE CORRESPONDING Open licenses SHOULD BE ACCESSIBLE AND PROPERLY WRITTEN.

data processing should conform to the standards or protocols recognized by the relevant scientific communities.

The FAIR data principles ↗

The first formal publication of the FAIR Principles, which includes the rationale behind them and some exemplar implementations in the community.

Assessing the FAIRness of data ↗

In this short course, you’ll learn how to go about assessing the FAIRness of research data using freely accessible tools and resources. 

How FAIR are your data? ↗

A checklist produced for use at the EUDAT summer school to discuss what measures could be taken to improve FAIRness of data.