Throughout this guide where information relates to the FAIR Data Principles you will see one of these icons.
According to the FAIR Data Principles, data should be: Findable, Accessible, Interoperable and Reusable. The FAIR Data Principles were developed and endorsed by researchers, publishers, funding agencies and industry partners in 2016, from a Nature Scientific Data publication, and are designed to enhance the value of all digital resources.
The benefits of FAIR data to the the broader research community are immeasurable and following the lead of the European Commission and Horizon 2020, Irish funders, such as the Health Research Board (HRB) and Irish Research Council (IRC) are now asking researchers how they will make their data FAIR, via a Data Management Plan (DMP).
A Checklist produced for use at the EUDAT summer school to discuss how FAIR the participant's research data were and what measures could be taken to improve FAIRness. Taken from Jones & Grootveld (2017).
Australian Research Data Commons’ FAIR data self assessment tool.
Using this tool you will be able to assess the ‘FAIRness’ of you data and determine how to enhance its FAIRness (where applicable).
Force11 - The FAIR Data Principles - A set of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable.
FAIRsharing - A curated, informative and educational resource on data and metadata standards, inter-related to databases/repositories and data policies.
Addressing the FAIR Data Principles in a Data Management Plan - A useful guide produced by University College Dublin (UCD) on how to integrate the FAIR data principles into your Data Management Plan.