Ensuring maximum impact from Australian research

Making research outputs more Findable, Accessible, Interoperable and Reusable (FAIR) provides a range of benefits to researchers, research communities, research infrastructure facilities and research organisations alike, including:

  • gaining maximum potential from research outputs, such as datasets and software
  • 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.
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National and international recognition

The FAIR principles were first drafted at an international scientific workshop in 2014, with the principles officially being published in 2016. Since then the principles have received worldwide recognition and are endorsed by international organisations including FORCE11, National Institutes of Health and the European Commission as an essential framework for sharing data and outputs in a way that will maximise use and reuse. In Australia the NCRIS guidelines now require NCRIS facilities to work making the research outputs they enable FAIR.

The FAIR principles are designed to:

  • support knowledge discovery and innovation both by humans and machines
  • support data and knowledge integration
  • promote sharing and reuse of data
  • be applied across multiple disciplines
  • help data and metadata to be ‘machine readable’, supporting new discoveries through the harvest and analysis of multiple datasets and outputs.

Supporting initiatives that enable making data FAIR

The ARDC supports and encourages initiatives that enable making data and other related research outputs FAIR. This includes working on policy, developing what FAIR means for specific disciplines, data and output types, supporting developers when developing code that enables FAIR outputs and building skills for research support staff and researchers. We connect, share and work on international and disciplinary initiatives to make data FAIR.

Find out more about how to make your data FAIR, and access our FAIR data training resources.