What is FAIR data?
The FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) were drafted at a Lorentz Center workshop in Leiden in the Netherlands in 2015.
The principles have since received worldwide recognition by various organisations including FORCE11, National Institutes of Health (NIH) and the European Commission as a useful framework for thinking about sharing data in a way that will enable maximum use and reuse.
The principles are useful because they:
- support knowledge discovery and innovation
- support data and knowledge integration
- promote sharing and reuse of data
- are discipline independent and allow for differences in disciplines
- move beyond high level guidance, containing detailed advice on activities that can be undertaken to make data more FAIR
- help data and metadata to be ‘machine readable’, supporting new discoveries through the harvest and analysis of multiple datasets.
Why make your data FAIR?
Making research data more FAIR will provide a range of benefits to researchers, research communities, research infrastructure facilities and research organisations alike, including:
- gaining maximum potential from data assets
- increasing the visibility and citations of research
- improving the reproducibility and reliability of research
- staying aligned with international standards and approaches
- attracting new partnerships with researchers, business, policy and broader communities
- enabling new research questions to be answered
- using new innovative research approaches and tools
- achieving maximum impact from research.
How to make your data FAIR
Translating the FAIR principles in practice will be different for different disciplines, however the below guidelines set out the broad principles:
Use the ANDS-Nectar-RDS FAIR data self-assessment tool to assess the 'FAIRness' of a dataset, and determine how to enhance its FAIRness.
FAIR webinar series
ANDS held a FAIR data webinar series throughout August and September 2017, covering each of the four principles in turn. It included practical case studies from a range of disciplines, Australian and international perspectives, and resources to support the uptake of FAIR principles.
- #1 Findable: 30 Aug 2017
- #2 Accessible: 6 Sep 2017
- #3 Interoperable: 13 Sep 2017
- #4 Reusable: 20 Sep 2017
The slides and recordings from all events are now online to catch up or view again.
FAIR data at eResearch Australasia 2017
ANDS, Nectar and RDS teamed up to promote the FAIR data principles at the eResearch Australasia conference in Brisbane which took place 16-20 October 2017.
The joint booth included FAIRground games and information, including tips on how to make your data more FAIR. It also included asking people to fill in a survey about their knowledge and use of FAIR data (which will be used to help shape promotional activity and training about FAIR data).
A number of sessions at the conference also touched on the FAIR principles and their importance.
International and national initiatives
- Australia: FAIR Access to research outputs policy statement
- Europe: GO FAIR initiative
- US: NIH Data Commons Pilot Phase Explores Using the Cloud to Access and Share FAIR Biomedical Big Data
- International: FAIRmetrics working group
- International: AGU coalition project to advance open and FAIR data standards in the Earth and Space Sciences
- The FAIR principles as published by FORCE11
- Nature article launching the FAIR concept (March 2016)
- Revisiting the FAIR principles for the European Open Science Cloud (March 2017)
- Explanation of the FAIR Data principles by the Dutch Centre for Life Sciences
- Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud
- All the flavours of FAIR, fair & F.A.I.R ' webinar organised by AOASG on 6 March 2018
- ANDS FAIR data webinar series
- Jisc report: FAIR in Practice
- SURF report: FAIR Data Advanced Use Cases