FAIR research data

FAIR research data are data that are findable, accessible, interoperable and reusable. The Swedish Research Council has issued a recommendation on data management according to FAIR. There are also criteria and guidelines to support the achievement of FAIR research data.

What does FAIR mean?

FAIR is an internationally recognised concept, consisting of 15 guiding principles for research data and data management. According to the FAIR principles, research data shall be

  • Findable
  • Accessible
  • Interoperable
  • Reusable

In 2016, Sweden and the EU member states adopted the EU Council’s conclusions on the transition towards an open science system. The Council’s conclusions encouraged member states to follow the FAIR principles in their research programmes and principles for funding.

The EU Council’s conclusions on the transition towards an Open Science system (9526/16) External link.

The Swedish Research Council’s recommendation on data management according to FAIR

The Swedish Research Council recommends that the research data produced through research are managed according to the FAIR principles, clarified via the criteria developed by the Swedish Research Council to achieve FAIR data.

The FAIR principles should be implemented taking into account applicable legislation, and, as far as is possible and applicable, based on the technical, organisational and/or discipline-specific preconditions that apply.

The recommendations relates in the first instance to research data (and metadata) financed by public funds that can be published with open access, but the application of the FAIR principles can be made broader than this, and be used also for research data that cannot be published entirely openly. The recommendation on data management according to FAIR is overarching, and aims to create a common starting point for the implementation of FAIR data management.

The recommendation on data management according to FAIR is overarching, and aims to create a common starting point for the implementation of FAIR data management.

Criteria for FAIR research data

The Swedish Research Council has developed criteria for all 15 FAIR principles. The FAIR criteria aim to increase the understanding and knowledge of what the FAIR principles mean in practice. They can be used by researchers, research funding bodies, or for strategic decisions when implementing FAIR in the policies of organisations.

Certain aspects of FAIR are more demanding and complex to fulfil than others – and to assess the fulfilment of. Certain principles assume that other principles have been fulfilled, for example PID (Persistent Identifier, in Principle F1) is a fundamental component that must be in place to enable other principles to be fulfilled. The fulfilment of certain principles entail collaboration with various support functions.

A criterion can be fulfilled in different ways, and to different degrees. Certain aspects may, in some situations, be achieveable only for metadata and not for data, for example when they consist of sensitive data.

The criteria are worded in a general way, and any comparison of FAIR-ness must take into account the research field and type of data.

To support the work with FAIR data management, there is also a need for supporting infrastructure, services, and not least competence in and a culture of FAIR and good data management.

Research data shall be findable

Research data shall be accessible

Research data shall be interoperable

Research data shall be reusable


Guidelines for implementation of the criteria

To enable FAIR data management to be implemented in the research process, the Swedish Research Council has produced a more detailed description in the form of guidelines to the criteria. The guidelines aim to provide support for the practical implementation of the criteria at a more detailed level. They can be used as a joint source of information for all who support researchers in planning data management, in particular the support functions for data management at higher education institutions and infrastructures, where adaptation to FAIR data management and practical implementation of the FAIR principles are often done.

Guidelines for implementation of criteria for FAIR research data (in Swedish)

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