Importance of making scientific data FAIR

Categorised: COLLABORATE

The Australian Research Data Commons (ARDC) along with the National Computational Infrastructure (NCI) and AuScope were the first Australian organisations to support the international Enabling FAIR Data project, convened by the American Geophysical Union. The Australian support and leadership on FAIR (Findable, Accessible, Interoperable, Reusable) played an important role in the successful application for a grant from Arnold Ventures, that enabled the breakthrough needed to help make data a valued first class object of research, particularly in the publication process.

The Nature article Make scientific data FAIR, published 4 June 2019, shows how far the FAIR principles have been adopted, especially in the Earth, space and environmental sciences, and what steps are needed to shift research culture more broadly to making FAIR data a priority. The ARDC is specifically recognised in this paper for our extensive repository of online training guides and self-help web pages that assist researchers to properly cite data, samples and software.

Dr. Lesley Wyborn, a co-author of the Nature article, winner of the US Earth Science Information Partners Martha Maiden Award and Senior Data Strategist, ARDC, is a strong advocate for making all research data FAIR in support of scientific integrity and transparency.

There are many benefits to making data FAIR, including how it supports knowledge discovery and innovation, promoting sharing and reuse of data, and its adaptability to multiple disciplines” said Dr. Wyborn.

Dr. Wyborn and others within ARDC have worked on the establishment of tools and projects to help advance the way Australian researchers manage and share data. These tools and projects include, but are not limited to:

  • FAIR data self-assessment tool: assesses the ‘FAIRness’ of a dataset, and determine how to enhance its FAIRness.
  • 23 Research Data Things: a training guide to research data management, for all disciplines.
  • Enabling FAIR Data project: easy discovery, recombination, reuse, and to test reliability, and where information about samples, methods, and tools are standardized, available, and linked across publications in the Earth, Space and Environmental Sciences.

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