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FAIR Principles for Research Data

14 June 2024
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FAIR principles are designed to make research data more discoverable, both by humans and machines, and to promote wider sharing and reuse of data. They can be applied to digital data from any discipline. FAIR stands for

  • Findable
  • Accessible
  • Interoperable
  • Re-usable

Working towards making research data more FAIR provides many benefits including:

  • increasing the visibility and citations of your research
  • improving the reproducibility and reliability of your research
  • enabling  new innovative research approaches and tools
  • aligning with international standards and approaches

To make research data findable, publish the data (or a metadata-only record) with as much as much Research metadata as possible. Most research data publishing platforms (including the University's Institutional Figshare ) provide you with a persistent identifier, such as a digital object identifier, which you can then use to cite or share the work.

To make research data accessible, ensure it can be downloaded over the internet from the publishing platform it is hosted on. Consider using a publishing platform that supports API access to make it easier for machines and databases to harvest the research data or it's metadata.

To make research data interoperable, use community-accepted languages, formats and vocabularies in the data and metadata. Metadata should reference and describe relationships to other data, metadata and information through the use of identifiers.

To make research data reusable, it should come with a clear human and machine-readable licence and provenance information on how it was collected or generated. It should also abide by discipline-specific data and metadata standards where possible, to ensure it retains important context.

The FAIR principles can complement the CARE and Māori Data Sovereignty principles by encouraging the consideration of both people and purpose. For more information, see this presentation on Māori Data Sovereignty, the Global Indigenous Alliance, and CARE principles by Maui Hudson (Associate Professor University of Waikato, Te Pua Wananga ki te Ao).

Practical steps for working with FAIR, CARE and Māori Data Sovereignty as complementary data principles

  1. Publish a description or metadata-only record of research data in a data repository (e.g. Institutional Figshare ) with citable DOIs for research (DOI). This enables others to discover and understand the applicability of the research data. Consider a meaningful name (e.g. avoid 'Thesis data'), appropriate metadata, and providing a sample of the data, actual or synthetic.
  2. Establish and maintain a mediated access process (e.g,. email request or form) linked to the publish description. This process should follow agreed governance processes and ideally, take a people and purpose-oriented approach to granting access.
  3. Create a data sharing agreement to define and record who the data is shared with, for what purpose, under what conditions (e.g. method of transfer, security requirements) and by whose authority (governance). Dropbox for Researchers and the Institutional Figshare Projects feature may be useful for storing agreements and sharing files with named individuals.
  4. Produce a data availability statement within the publication (e.g. journal article, thesis) linking to the description, possibly referencing the mediated access process and alignment with FAIR, CARE and Māori Data Sovereignty data principles.

For support in this area, please contact the eResearch team by filling out the eResearch Consultancy ServiceNow Form.

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