RSP - RDM

F.A.I.R. Data

F.A.I.R. Data Principles are a set of principles to guide researchers in making their research data findable, accessible, interoperable and reusable (Wilkinson et al. 2016), directing data producers and publishers to promote maximum use of research data.  The Principles also highlight the importance of data to be machine-readable, as humans rely on computers to search for and deal with increasing volumes of data, in addition to data complexity.  

Following the FAIR Principles would be seen as good research practice by all Research Funders, particularly beneficiaries of Horizon 2020 funding.  Data Management Plans for European Commission projects must address how datasets will be created, if these data can be made accessible and how they will be curated, stored and preserved.  Further details can be found in the following documents:

H2020 Programme: Guidelines on FAIR Data Management in Horizon 2020

European Research Council (ERC): Guidelines on Implementation of Open Access to Scientific Publications and Research Data

Go Fair expand on the granular details of the F.A.I.R. Principles (CC-BY 4.0):

Findable

The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process.

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

F2. Data are described with rich metadata

F3. Metadata clearly and explicitly include the identifier of the data they describe

F4. (Meta)data are registered or indexed in a searchable resource

Accessible

Once the user finds the required data, she/he needs to know how can they be accessed, possibly including authentication and authorisation.

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

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

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

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

Interoperable

The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.

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

Reusable

The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.

R1. Meta(data) are richly described with 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 detailed provenance

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

The principles refer to three types of entities: data (or any digital object), metadata (information about that digital object), and infrastructure. For instance, principle F4 defines that both metadata and data are registered or indexed in a searchable resource (the infrastructure component).