FAIR in practice - Jisc report on the Findable Accessible Interoperable and Reuseable Data Principles

This report investigates the meaning and (potential) impact
of the FAIR data principles in practice. These principles
were established by a group of diverse stakeholders
engaging via a working group in FORCE11. They are
referenced in many policy documents and in developments
of open science, for example, the European Open Science
Cloud. 

This report explored FAIR with stakeholders in the
UK academic research community. Its aims were to
understand how using or being inspired by these principles
improves the findability, accessibility, interoperability and
reuse of research data, including consideration of
disciplinary differences.

Jisc established a group of research data experts and Jisc
staff who provided expertise and helped to validate
findings. Interviews and focus groups were conducted,
primarily with researchers, but also involving input from
research support professionals, publishers and funders.

An assessment of the use of FAIR principles in institutional
research data management (RDM) guidance was also
carried out. Data collected from these activities was
synthesised and structured using a PEST framework -
grouped into factors relating to Political, Economic, Social
and Technical aspects.

Explicit use of FAIR was seen to be limited, in many cases,
to discussion at a fairly conceptual level amongst those
most heavily involved in best practice of data management.
Even where FAIR was fairly well established as a term and
a concept, it tended to largely reflect existing practice.
Arguably this was without significantly influencing many
practical changes for those at the “leading edge” of data
management, although it did provide a new and effective
common way of communicating best practice.

However, in exploring the underlying practices of research,
demonstrating findability, accessibility, interoperability
and reusability, there was considerable evidence that
good practice existed in all of these elements. In many
cases this was both well established (over many years)
and continually improving.