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Research Data Management

FAIR Principles

Granting agencies and publishers are increasingly requiring researchers to follow the FAIR Principles when sharing and publishing their research data. These guidelines are intended to improve the Findability, Accessibility, Interoperability, and Reuse of research data and other digital assets.

The following information is from the Fair Principles by GOFAIR:

Findable

Research data must be described with human and machine-readable metadata:

  • F1. (Meta)data are assigned a globally unique and persistent identifier
  • F2. Data are described with rich metadata (defined by R1 below)
  • F3. Metadata clearly and explicitly include the identifier of the data they describe
  • F4. (Meta)data are registered or indexed in a searchable resource

Accessible

  • A1. (Meta)data are retrievable by their identifier using a standardised communications protocol
    • A1.1 The protocol is open, free, and universally implementable
    • A1.2 The protocol allows for an authentication and authorisation procedure, where necessary
  • A2. Metadata are accessible, even when the data are no longer available

Interoperable

  • I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
  • I2. (Meta)data use vocabularies that follow FAIR principles
  • I3. (Meta)data include qualified references to other (meta)data

Reusable

  • R1. (Meta)data are richly described with a plurality of accurate and relevant attributes
  • R1.1. (Meta)data are released with a clear and accessible data usage license
  • R1.2. (Meta)data are associated with detailed provenance
  • R1.3. (Meta)data meet domain-relevant community standards

For more information about the FAIR Principles, visit GOFAIR, "FAIR Principles," https://www.go-fair.org/fair-principles/

CARE Principles

CARE Principles for Indigenous Data Governance

The following is quoted from the Research Data Alliance International Indigenous Data Sovereignty Interest Group, (September 2019), “CARE Principles for Indigenous Data Governance,” The Global Indigenous Data Alliance, GIDA-global.org.

Collective Benefit 

Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data for inclusive development and innovation, improved governance and citizen engagement, and equitable outcomes.

Authority to Control

Indigenous Peoples’ rights and interests in Indigenous data must be recognised and their authority to control such data be empowered. Indigenous data governance enables Indigenous Peoples and governing bodies to determine how Indigenous Peoples, as well as Indigenous lands, territories, resources, knowledges and geographical indicators, are represented and identified within data.

Responsibility

Those working with Indigenous data have a responsibility to share how those data are used to support Indigenous Peoples’ self-determination and collective benefit. Accountability requires meaningful and openly available evidence of these efforts and the benefits accruing to Indigenous Peoples.

Ethics

Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.

Copyright

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