FAIR Go: New resources to support FAIR data

Keith Russell1, Kerry Levett2, Richard Ferrers3, Andrew White4
1 Australian Research Data Commons, Melbourne, Australia, keith.russell@ardc.edu.au
2 Australian Research Data Commons, Adelaide, Australia, kerry.levett@ardc.edu.au
3 Australian Research Data Commons, Melbourne, Australia, richard.ferrers@ardc.edu.au
4 Australian Research Data Commons, Brisbane, Australia, andrew.white@ardc.edu.au

 

POSTER OBJECTIVE

The poster will showcase a number of resources and materials the ARDC (the Australian Research Data Commons) and partners developed around FAIR data in 2017-2018. These resources have helped increase the understanding of what the FAIR data principles are, outlined the steps that can be taken to make data more FAIR, and highlighted gaps in this space. Future plans for the ARDC FAIR agenda are proposed.

BACKGROUND

The FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) were drafted at a Lorentz Center workshop in the Netherlands in 2015 and published in 2016 [1]. They have since received international recognition as a useful framework for considering data in a way that will enable maximum use and reuse not only by humans but also by machines. In 2017-18, ANDS-Nectar-RDS (now ARDC) undertook a number of activities to promote the FAIR data principles and to increase research community understanding around Australia about what FAIR means in practice. This included recommending actions that research organisations and research infrastructure organisations can take to make their data more FAIR.

WERE WE FAIR AWARE?
The ‘Are you FAIR aware?’ survey was conducted in October 2017 and attracted 249 responses [3]. It showed that at that time there were varying levels of awareness for the FAIR data principles, but they were considered useful and 78% would recommend these to colleagues. The most frequently mentioned gaps that were mentioned in making data FAIR were standardised data formats, provenance tools, ethics and access advice.

SELF ASSESS the FAIRNESS of YOUR DATA

The widely popular FAIR Self assessment tool [4], was released in May 2018 and has already been adopted by CSIRO as well as a number of universities and projects. It is considered a good educational vehicle to improve the FAIRness of data by highlighting the steps that can be taken to make a data set more FAIR.

TRAINING MATERIALS AND RESOURCES RELATED TO FAIR

A collection of training materials [5] related to the FAIR principles broken down by principle were published. These support the community wanting to train and grow the understanding around the more detailed principles. The FAIR data infographic (Figure 1) links to detailed advice on each aspect of FAIR, from each of the coloured squares. The collection is now available for sharing, expanding and is being aligned internationally with other organisations working on data management training.

Figure 1: FAIR data infographic (CC-BY except F.A.I.R logos CC-BY-SA by Sangya Pundir [6]

 

AGU FAIR PROJECT

The ARDC is a partner (with NCI and AuScope and others) in the American Geophysical Union Enabling FAIR Data [7] project. In this project we are working with publishers, repository managers and researchers in Australian Earth, Space and Environmental Sciences to require authors submitting a publication to make their data FAIR and accessible from a recognised repository that can provide a persistent identifier and a landing page for each dataset cited. The project will also deliver supporting resources for researchers in Earth, space and environmental sciences on how they can make their data FAIR.

NEXT STEPS IN 2018-2019

In 2018-2019, ARDC will continue the work with the FAIR principles, providing further resources and support related to what FAIR means in practice, emphasising topics such as provenance, ethics and access. The ARDC will also be looking at how software, tools and infrastructure can be improved to make it easy and seamless for researchers to make their data FAIR.

REFERENCES

  1. ANDS-Nectar-RDS, ‘FAIR data principles: how well known or understood are they? 26 March 2018. Available from: https://www.ands-nectar-rds.org.au/single-post/2018/03/26/FAIR-data-principles-how-well-known-or-understood-are-they, accessed 30 August 2018.
  2. ANDS-Nectar-RDS, FAIR self-assessment tool. Available from: https://www.ands-nectar-rds.org.au/fair-tool, accessed 30 August, 2018.
  3. ANDS, FAIR Data Training. Available from: https://www.ands.org.au/working-with-data/fairdata/training, accessed 30 August, 2018.
  4. FAIR data principles logo https://commons.wikimedia.org/wiki/File:FAIR_data_principles.jpg accessed 30 August, 2018
  5. COPDESS [Coalition for Publishing Data in the Earth and Space Sciences], Enabling FAIR Data Project. Available from: http://www.copdess.org/enabling-fair-data-project/, accessed 30 August, 2018.

 

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