Indigenous Data Sovereignty — CARE Principles, IEEE 2890-2025, and operational anchors in Peru and Canada

Global (with operational anchors in Peru, Canada, Mexico, Aotearoa New Zealand)

Content

Indigenous Data Sovereignty (IDSov) is the right of Indigenous Peoples to own, control, access and possess data that derive from them, and which pertain to Nation membership, knowledge systems, customs, or territories. The framework is articulated through the CARE Principles, operationalised in IEEE 2890-2025, and anchored in the UN Declaration on the Rights of Indigenous Peoples (UNDRIP).

This unit captures the framework and the operational anchors — Indigenous-led deployments that have moved from framework articulation to substantive community outcomes.

The CARE Principles (Carroll et al. 2020, Gaborone)

Drafted: November 2018, International Data Week and Research Data Alliance Plenary, Gaborone, Botswana Co-leads: Stephanie Russo Carroll (University of Arizona) and Maui Hudson (University of Waikato, Aotearoa New Zealand) Citation count: 1,808 (Carroll et al. 2020, Data Science Journal) — substantive academic uptake Translations: Spanish, Vietnamese, Māori, German, Khmer

The four principles:

The “FAIR + CARE” framing. CARE Principles were explicitly developed to complement the FAIR Principles (Findable, Accessible, Interoperable, Re-usable). The GIDA framing: “Existing principles within the open data movement (e.g. FAIR) primarily focus on characteristics of data that will facilitate increased data sharing among entities while ignoring power differentials and historical contexts.”

IEEE 2890-2025 — Provenance of Indigenous Peoples’ Data

Approved: August 2025, after five-year development process Status: World’s first global standard for the provenance of Indigenous data Format: IEEE Recommended Practice (industry specification, not binding regulation)

What it does: Operationalises the CARE Principles into industry specifications by detailing the process for describing and recording the provenance (origin and history of ownership) of data derived from Indigenous Peoples, lands, and waters.

Recognition: GIDA recognised IEEE 2890-2025 as including the active participation of Indigenous members in the development process.

Operational anchors — Indigenous-led deployments

Indigenous Navigator Peru (ONAMIAP-IWGIA, 2023-2025)

Lead organisations: ONAMIAP (Organización Nacional de Mujeres Indígenas Andinas y Amazónicas del Perú — National Organisation of Andean and Amazonian Indigenous Women of Peru) + IWGIA (International Work Group for Indigenous Affairs) Funding: European Union Communities: Quechua and Asháninka in Peru Period: 2023-2025 Published: December 2025 (case study), updated April 2026

Concrete outcomes:

Substantive significance: This is a concrete Indigenous-led deployment with policy outcomes (municipal ordinances). Not just framework articulation.

FNIGC — First Nations Information Governance Centre (Canada)

Founded: 1990s Status: Established national-scale Indigenous data governance in Canada Annual Report 2024-2025 referenced as the operational anchor for First Nations data sovereignty OCAP® principles (Ownership, Control, Access, Possession) — the Canadian Indigenous data governance framework

Te Mana Raraunga — Māori Data Sovereignty Network (Aotearoa NZ)

Positioning: Māori Data Sovereignty / Māori Data Governance “Tino Rangatiratanga Raraunga” — Māori data sovereignty as self-determination “State of the Nation” Report 2025 (Taiuru & Associates, September 2025) — annual state-of-Māori-data-sovereignty assessment Context: Aotearoa NZ has substantive Māori-led AI/data infrastructure development, including Te Reo Māori language AI, Māori data governance legislation

UNESCO Indigenous AI Report (2023, updated 2025)

“Indigenous People-Centered Artificial Intelligence: Perspectives from Latin America and the Caribbean” Region covered: 800+ Indigenous Peoples in LAC; 10%+ of world’s Indigenous population; ~30% in extreme poverty; 40% with basic computer skills

Five Mexico case studies:

  1. UAM researchers — text-strings and AI proposal to catalogue and identify form, aesthetic, and iconographic elements of indigenous garments of the Altos de Chiapas region
  2. Technological Institute of Coatzacoalcos (Veracruz) — NLP bot to assess pronunciation of indigenous languages
  3. Technological Institute of Oaxaca — interactive learning app for Tu’un Savi (Mixtec) language using visual computing
  4. UNAM (IIMAS) — automatic translation between 11 indigenous language families using ML/deep learning (Wixarika, Náhuatl, Yorem nokki, P’urhecha, Mexicanero, Spanish)
  5. f<A+i>r + CEPIADET + Oaxaca Human Rights Defender — conversational agent for indigenous language interpreters; the proposed system was inadequate according to the evaluation — a substantive honesty about implementation challenges

The fifth case is particularly worth knowing: it failed, and that failure was reported honestly. Worth surfacing in any talk about IDSov operationalisation.

AGUAPAN — Association of Guardians of the Native Potato of Central Peru

Founded: July 2015 Type: Custodian farmer network — farmer-led biodiversity conservation Activities: Protect varietal richness of Central Peruvian Andean potatoes; exchange of landraces across Peru’s many agro-ecological zones; 5th Annual Assembly convened Funding: McKnight Foundation / Collaborative Crop Research Program (CCRP) Related initiative: Potato Park (Pisac, Peru) — climate-resilient potato breeding

Worth distinguishing: AGUAPAN is not primarily a data sovereignty project — it’s a custodian-farmer biodiversity network. But it intersects with IDSov because the genetic resources and traditional knowledge at stake are Indigenous data in the broader sense (genetic resources, traditional cultivation knowledge). The WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge (2024) explicitly addresses this intersection.

UNDRIP — UN Declaration on the Rights of Indigenous Peoples: Article 3 (self-determination), Article 31 (traditional knowledge). The legal anchor for IDSov.

EMRIP 18th Session (July 2025): Expert Mechanism on the Rights of Indigenous Peoples adopted draft study “Right of Indigenous Peoples to Data, Including with Regard to Data Collection and Disaggregation,” framing data as “cultural, strategic and economic resource.” Issued Advice No. 18, calling on states to recognise and protect Indigenous data sovereignty through laws, policies, and frameworks.

WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge (2024): First ratifications by Malawi (December 2024) and Uganda (July 2025). Will enter into force after 15 ratifications. Distinct from CARE / IEEE 2890 but addresses the genetic resource / traditional knowledge intersection.

Cali Fund (CBD): Fair and Equitable Sharing of Benefits from use of Digital Sequence Information on Genetic Resources. Growing global recognition.

GIDA “CARE Directs Us Home” communiqué (August 2025): Warns against treating CARE as static compliance checklist. Reasserts CARE as high-level guidance directing researchers toward community-specific protocols.

Global Indigenous Data Sovereignty Conference (Canberra, April 2025): 250+ Indigenous representatives; three foundational actions: advancing Indigenous data priorities, addressing systemic barriers, building Indigenous data capability.

Critical context

The framework is more developed than the Indigenous-led AI deployment. CARE Principles (2018/2020), IEEE 2890-2025, EMRIP 18, GIDA communiqués — the framework layer is substantive. The Indigenous-led AI deployment layer is thin in agrifood specifically; the UNESCO report’s five Mexico case studies are the most concrete operational anchors in agriculture-adjacent AI.

The geographic distribution matters. Aotearoa NZ (Te Mana Raraunga, Māori data sovereignty), Canada (FNIGC, OCAP®), Peru (ONAMIAP-IWGIA Indigenous Navigator), Australia (FNIGC’s analog), Mexico (UNESCO report), Asia (AIPP), Africa (African Commission on Human and Peoples’ Rights, 9 August 2025 statement) — IDSov is global but uneven in operational scale.

The “be FAIR and CARE” framing is the key insight. CARE complements FAIR rather than replacing it. Talks about Indigenous data governance should engage with both — CARE addresses people and purpose; FAIR addresses technical interoperability. Together they form a complete framework.

Worth naming honestly: Indigenous-led AI deployment in agrifood specifically is under-deployed relative to vendor-led or state-led AI deployment. The gap is real. Worth knowing for any talk about IDSov operationalisation.

What this unit is doing in the taxonomy

First unit in the field guide with data-rights-framework: Indigenous-sovereign as primary value. Fills the v4 schema gap identified in the data cooperatives / commons deepening.

Anchors the data-substrate × Indigenous-sovereign cell with the CARE Principles framework, IEEE 2890-2025 standard, and concrete operational anchors in Peru, Canada, Mexico, and Aotearoa NZ.

Distinct from:

Why it matters for talks

Critical context