Skip to Main Content

Indigenous Data Sovereignty

Contributor: Lucia Costanzo

What is Indigenous Data?

Any data, knowledge, or information created by, for, with, or about Indigenous people or communities, and can include data:

  • About Indigenous environmental resources (land management and history, geological data, information on wildlife and water sources)  
  • About Indigenous peoples, social groups, communities, and Nations (demographics, health information, employment data, education statistics)
  • From Indigenous communities (relating to ancestral knowledge and cultural practices, such as languages, songs, stories, oral histories, art, and images) 
  • Presented as photographs, videos, sound recordings, textual documents, data sets, and more. 

What is Indigenous Data Sovereignty (IDS)?

Indigenous data sovereignty refers to the right of Indigenous peoples to control data from and about their communities and lands. It includes both the individual and collective rights to data access and to privacy. 

How does it relate to Research Data Management (RDM)?

The Tri-Agency Research Data Management Policy (March 2021) affirms that data related to research by and with First Nations, Métis, or Inuit communities must be managed in accordance with principles developed and/or approved by these communities. Data management plans (DMPs) should incorporate Indigenous data sovereignty. FAQ #2 (Indigenous Research) addresses how the policy relates to the management of Indigenous research, knowledge and data. 

Indigenous Data Governance Frameworks

Local data governance protocols are interconnected with broader governance frameworks, such as:

The First Nations Principles of OCAP (FNIGC, 1998)

The First Nation Principles of OCAP are a set of standards to guide data governance.

  • Ownership (O): Indigenous communities own their information in the same way that an individual would own their personal information.
  • Control (C): Indigenous communities and Nations can seek control over research data and its management at all stages of the research cycle.
  • Access (A): Indigenous communities and Nations must be able to access data about themselves and have the right to make or be involved in decisions regarding access to the data.
  • Possession (P): Physical control of the data should be with the First Nation or Indigenous-controlled steward, or otherwise with a third party data steward (decided upon by the Indigenous community or Nation) who will ensure the principles of ownership, control, and access are upheld.

FAIR Principles (2016)

The FAIR Principles guide researchers in ensuring that data are effectively managed and made available for broader use while maintaining machine-actionability to support data-driven research.

  • Findable (F): The first step is ensuring data can be easily found by both humans and computers. This involves assigning globally unique and persistent identifiers to data, describing data with rich metadata, including data identifiers in metadata, and registering or indexing data in searchable resources.
  • Accessible (A): Once data is found, users need to know how to access it, potentially involving authentication and authorization. Data should be retrievable by their identifier using a standardized, open, and universally implementable communications protocol. Metadata should remain accessible even when the data is no longer available.
  • Interoperable (I): Data often need to be integrated with other data and must be able to interoperate with various applications and workflows. This requires using formal, shared, and broadly applicable languages for knowledge representation, employing vocabularies adhering to FAIR principles, and including qualified references to other data.
  • Reusable (R): The ultimate goal is to optimize data reuse. To achieve this, data and metadata should be well-described, have clear and accessible usage licenses, be associated with detailed provenance information, and meet relevant community standards.

CARE Principles for Indigenous Data Governance (GIDA, 2018)

The CARE Principles for Indigenous Data Governance are intended to complement the FAIR Principles.

  • Collective Benefit (C): Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data.
  • Authority to Control (A): 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 (R): 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 (E): Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.

National Inuit Strategy on Research (Inuit Tapiriit Kanatami, 2018)

The National Inuit Strategy on Research outlines several priority areas and objectives to advance research in Inuit communities.


Diviacchi, T (2023, Oct 10). Indigenous Data Sovereignty and Open Data. EveryONE (PLOS ONE Blog).

Doctor, J., Ward, J., Jang, T., Polack, J. (2022)  #DataBack: Asserting and Supporting Indigenous Data Sovereignty. Animikii.

Health Data Research Network Canada. Indigenous Data Sovereignty.

Indigenous Innovation Initiative (2021). Indigenous Knowledges and Data Governance Protocol. Toronto: Indigenous Innovation Initiative. Ontario Federation of Indigenous Friendship Centres (OFIFC). USAI Research Framework (2016).

Open North in collaboration with BC First Nations Data Governance Initiative (2017). Decolonizing Data: Indigenous Data Sovereignty Primer.

Redden, M., & Kwan-Lafond , D. (2023). Indigenous Data Sovereignty: Moving Toward Self-Determination and a Future of Good Data. In K. Thompson, E. Hill, E. Carlisle Johnston, Danielle Dennie, & É. Fortin (Eds.), Research Data Management in the Canadian Context: A Guide for Practitioners and Learners. e-Campus Ontario.

Ruckstuhl, K. (2022). Trust in Scholarly Communications and Infrastructure: Indigenous Data Sovereignty. Frontiers in Research Metrics and Analytics, vol. 6.

Suggest an edit to this guide

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.