The CARE Principles for Indigenous Data Governance (Collective benefit, Authority to control, Responsibility, Ethics) and the FAIR data principles (Findable, Accessible, Interoperable, Reusable) are often presented as complementary. In practice they have a real tension: FAIR maximises openness and access; CARE centres Indigenous community authority over data, including over what counts as accessible and to whom. The Global Indigenous Data Alliance’s 2024 manifesto on CARE-FAIR integration is the most developed framework for reconciling them. This post walks through the tension, the GIDA Manifesto’s resolution, and what implementers should do.
What FAIR says and what it does not
FAIR, articulated by Wilkinson and colleagues in 2016, is a framework for making data more useful. Findable: data have rich metadata and persistent identifiers. Accessible: data can be retrieved by an authentication-and-authorisation protocol that is open and free. Interoperable: data use shared vocabularies and standards. Reusable: data have clear provenance, licensing, and usage information.
What FAIR does not directly address is who decides what is findable, accessible, interoperable, and reusable. FAIR is technically permissive about access controls — the principles allow that authentication-and-authorisation may restrict access — but the dominant interpretation of FAIR has been maximalist: open by default, restricted only with clear justification. This has produced an implementation pattern where Indigenous data are often treated as candidates for openness with restrictions, rather than as community-governed assets whose access decisions sit with the community.
What CARE says
The CARE Principles, articulated by the Global Indigenous Data Alliance in 2019 and formally published in 2020, are a counterweight rather than a contradiction of FAIR. Collective benefit: data ecosystems are designed and function in ways that enable Indigenous peoples to derive benefit from the data. Authority to control: Indigenous peoples’ rights and interests in Indigenous data must be recognised, and they must have the authority to control such data. Responsibility: those working with Indigenous data have a responsibility to share how those data are used. Ethics: Indigenous peoples’ rights and wellbeing should be the primary concern at all stages of the data lifecycle.
CARE applies to Indigenous data, defined broadly to include data about Indigenous peoples, Indigenous lands, Indigenous resources, and Indigenous knowledge. The principles are not anti-openness; they are pro-authority-with-the-community-on-openness-questions.
The tension in practice
Three illustrative tensions.
First, a researcher working with an Indigenous community produces a dataset documenting traditional ecological knowledge. FAIR-maximalist implementation would push for open deposit with a CC BY licence. CARE-aligned implementation would defer to the community’s governance: the community may choose to share openly, may choose to share with use restrictions, may choose to restrict access entirely, may choose to share with attribution requirements via Traditional Knowledge Labels. The community’s decision is determinative under CARE; the FAIR-maximalist instinct is to nudge toward openness.
Second, a population health dataset includes Indigenous community-level data. FAIR-maximalist implementation would push for de-identified open deposit. CARE-aligned implementation asks whether de-identification is sufficient to prevent community-level identification (often it is not), whether the community has consented to research uses beyond the original study, and whether the planned uses generate collective benefit. The answers may permit open deposit, may require controlled access, or may require negotiated terms.
Third, a museum collection includes Indigenous cultural objects with associated metadata. FAIR-maximalist implementation would push for full metadata openness. CARE-aligned implementation defers to the community on what metadata is appropriate to share, what should be retained but restricted, and what should be returned to community governance.
The GIDA Manifesto
The GIDA Manifesto on CARE-FAIR integration, published in 2024 after extended consultation across the international Indigenous data networks (Te Mana Raraunga in Aotearoa New Zealand, Maiam nayri Wingara in Australia, the United States Indigenous Data Sovereignty Network, the First Nations Information Governance Centre in Canada, and others), articulates a reconciliation framework.
The framework’s core proposition is that FAIR and CARE are sequenced, not simultaneous. CARE comes first: the community’s governance decisions determine what data exist, who has rights in them, what uses are permitted, and what access conditions apply. FAIR then operates within the CARE-determined envelope: findable to those who should find them, accessible under the access conditions the community has set, interoperable for the uses the community has permitted, reusable subject to community-defined terms.
This is not a watering-down of FAIR; the manifesto is explicit that all four FAIR principles are honoured within their proper scope. It is a re-ordering of the implementation question. The pre-FAIR step is not assumed-open; it is community-determined.
Operational implications
For repositories, the operational implications are concrete. Repositories holding or potentially holding Indigenous data need governance arrangements that surface CARE compliance. This means: identifying Indigenous data at deposit; verifying community authorisation; recording the community’s access decisions in machine-readable form; honouring those decisions in the access-control layer; providing for community-initiated access changes over time.
The CASRAI Indigenous data and CARE domain tracks repository implementations. Several have led: the SOLES repository at the Smithsonian, the Indigenous-managed nodes of the OCAP-aligned First Nations data ecosystem in Canada, the Maori Data Sovereignty Network’s portal in Aotearoa New Zealand.
For researchers, the operational implications are about partnership. Research that produces Indigenous data needs to be conducted in partnership with the community, with data-governance arrangements agreed upfront, with the community holding control over downstream uses. The Free, Prior, and Informed Consent framework is the standard reference.
For funders and journals, the operational implications are about review and policy. Funder data-management requirements should recognise CARE-aligned deposit; journal data-availability requirements should accommodate community-governed access decisions. Several major funders and journals have updated their policies in 2024-2025 to do this; the implementation is uneven.
The OCAP and FPIC interfaces
Two adjacent frameworks deserve mention. OCAP (Ownership, Control, Access, Possession), articulated by the First Nations Information Governance Centre in Canada, predates CARE and operates in a more granular operational space; OCAP and CARE are compatible and OCAP-aligned implementations can claim CARE alignment in the relevant scope. FPIC is the consent framework derived from the UN Declaration on the Rights of Indigenous Peoples; FPIC operates at the research-design stage, before data are collected, and is upstream of both CARE and FAIR.
The integrated operational pattern: FPIC governs research design and data collection; OCAP governs the data-control arrangements during and after collection; CARE provides the data-governance framework for repository-level and ecosystem-level decisions; FAIR provides the technical-implementation framework for the openness-within-CARE-envelope work.
What CASRAI recommends
Four recommendations. First, repositories should adopt CARE-aligned governance, with community-controlled access decisions surfaced in the deposit and discovery layers. Second, researchers working with Indigenous communities should structure partnerships under FPIC and follow OCAP or equivalent arrangements. Third, funders and journals should recognise CARE-aligned deposit as fulfilling data-availability requirements. Fourth, the FAIR-data community should adopt the GIDA Manifesto’s sequencing as the default implementation pattern, with the FAIR-first interpretation explicitly identified as inappropriate for Indigenous data.
The reconciliation works. It requires more upfront attention to governance than the FAIR-maximalist default, but it produces outcomes that respect community sovereignty while delivering the technical-interoperability benefits that FAIR was designed for.
