In recent years, conversations about data governance have broadened beyond technical standards and infrastructure. Increasingly, researchers, institutions, and communities are asking deeper questions: Who does data serve? Who benefits? Who has authority over its use, especially when it concerns Indigenous Peoples?
The CARE Principles for Indigenous Data Governance provide an essential framework for addressing these questions. Developed alongside the widely cited FAIR Principles, CARE shifts the focus from machines and metadata to people and purpose.
As part of International Love Data Week 2026, this blog post shares reflections on the CARE Principles, explains why they matter and explores what more intentional practices around support for CARE principles might look like.
Origins of the CARE Principles
As efforts to make research data more open and shareable have gained momentum over recent years, it is unsurprising that some of the most strongly supported principles have been those that have focused on data utility and purpose, such as the Open Data Charter and the FAIR principles.
In the article, Operationalizing the CARE and FAIR Principles for Indigenous data futures the authors observed that data principles such as FAIR were aligned to an overall shift towards open science and open data, ‘that facilitate increased data sharing among entities while ignoring relationships, power differentials, and the historical conditions associated with the collection of data’ (Carroll et al., 2021).
In data privacy discourse, some scholars have highlighted that data protection laws, despite being more oriented towards the individual, are similarly flawed and can perpetuate the myth of the “sovereign subject,” a model that presumes all individuals are ‘inherently free, self-possessive, and equally capable of entering into contracts’ (Weinberg, 2017). A long-read article by Privacy International (2024) further argues that ‘this model neglects the historical exploitation and exclusion of certain groups from being recognised as full individuals’.
In September 2019, following a year-long public discussion and building on Indigenous Data Sovereignty network activities, the Global Indigenous Data Alliance released the CARE Principles for Indigenous Data Governance, which aimed to address some of these deeper-rooted issues.
In open science and research, the CARE principles are, comparatively, lesser known to their more technically-oriented counterparts. While the former were conceived to address a very particular set of concerns relating to Indigenous Data Sovereignty (which draws on the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP)) they were also intended to be viewed as complementary, not distinct, to FAIR principles and adhered to simultaneously, in the relevant context.
One possible explanation for the current perceived obscurity of CARE principles may be that it takes time to build trust and partnerships with indigenous scholars and communities. This is often considered to be significantly at odds with dominant research cultures that have favoured relatively fixed funding cycles, a precarity of work in early career research positions, the continuing spectre of “publish or perish” and the rapid expansion of machine learning approaches that accelerate data re-use, more recently (Winker, M.A. et al. 2023).
In their article, Carroll et al. (2021) argue that ‘the CARE Principles should be seen as a required dimension of open and FAIR data that ensures that the use of data aligns with Indigenous rights, is as open as determined by Indigenous communities, is purposeful, and enhances the wellbeing of Indigenous Peoples’. This is particularly important in light of the tension they observed between needing to protect Indigenous rights and interests in data while also encouraging FAIR data in a global research landscape that also supports open data.
Defining Indigenous Peoples and Indigenous Data:
In order to gain an informed understanding of the CARE principles it is first essential to understand what is meant by certain key related terms:
Indigenous Peoples:
Firstly, the UN Declaration on the Rights of Indigenous Peoples (2007) does not include a formal definition of Indigenous Peoples and many human rights documents have been equally cautious in proposing one, maintaining instead that self-identification should be the fundamental criterion. This is important not least because of the plurality of umbrella terms that may be used and preferred by particular peoples in specific regions or contexts.
According to the UN Permanent Forum on Indigenous Issues, the system has instead worked towards developing a modern understanding of the term based on the following:
- Self-identification as indigenous peoples at the individual level and accepted by the community as their member.
- Historical continuity with pre-colonial and or pre-settler societies
- Strong links to territories and surrounding natural resources
- Distinct social, economic and political system
- Distinct language, culture and beliefs
- Form non-dominant groups of society
- Resolve to maintain and reproduce their ancestral environments and systems as distinctive peoples and communities
Indigenous data:
According to Carroll et al. (2021) indigenous data are ‘data, information, and knowledge, in any format, that impact Indigenous Peoples, nations, and communities at the collective and individual levels; data about their resources and environments, data about them as individuals, and data about them as collectives’.
Indigenous data has the potential therefore to span a wide range of domains that are not limited to scientific, geographic, environmental, cultural, demographic, and linguistic information. Such data might exist as born‑digital or newly digitised materials and can take the form of biodiversity surveys carried out within Indigenous territories, personal health records, community knowledge, and oral histories.
The Paradox of Indigenous Data: Scarcity and Abundance
Due to the enduring impacts of colonial violence and other systems of oppression that have continued to violate Indigenous Peoples’ rights, data concerning Indigenous lands, knowledge systems, peoples, and identities are often held and governed by institutions or organisations whose practices have not aligned with the interests and rights of those Indigenous communities. This has made it especially problematic for Indigenous communities wishing to exercise agency in the stewardship, governance, and decision‑making processes surrounding these data. (Amnesty International; Ravindran, 2024).
These challenges are starkly highlighted by Carroll et al. (2021) who argue that Indigenous communities today face a unique and complex paradox:
On the one hand, there is a scarcity of data that they control or can access, aligned with their rights, interests, and governance structures.
On the other hand, there is an abundance of data about them often mislabeled, buried in large repositories, gathered without consent, or governed by institutions with little connection to Indigenous Peoples’ priorities.
Scholars of indigenous data like Carrol et al. (2021) argue that these types of power imbalances clearly illustrate why embedding CARE principles in open science and research data practices is vital. Without ethical, community-centered governance, even well‑intentioned open data practices can result in the replication of existing inequalities.
Introducing the CARE Principles:
In their overview of the principles, the Global Indigeneous Data Alliance (GIDA) have stated that ‘the CARE Principles for Indigenous Data Governance are people and purpose-oriented, reflecting the crucial role of data in advancing Indigenous innovation and self-determination. These principles complement the existing FAIR principles (www.go-fair.org) encouraging open and other data movements to consider both people and purpose in their advocacy and pursuits’.
The top-level principles are summarised as follows (with a related subset of principles available to view in the overview link above):
C: Collective Benefit:
Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data.
A: 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.
R: 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.
E: Ethics
Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.
CARE and FAIR: Complementary, Not Competing
The top-level overview above illustrates that while FAIR principles focus on ensuring that data are technically usable, discoverable, and integrated into global research infrastructures (Findable, Accessible, Interoperable, and Reusable), CARE emphasises the human and relational dimensions of data governance, ensuring that data use is equitable, ethical, and aligned with the rights of Indigenous Peoples. The two frameworks meet at the point where technical openness intersects with meaningful stewardship, and in doing so the authors of the CARE principles challenge us to consider a healthier data ecosystem that is capable of being both technically robust and socially just. This is much of the rationale behind the CARE data maturity model.
Summary:
The CARE Principles offer a powerful and humane counterbalance to purely technical views of data governance. By centering collective benefit, authority, responsibility, and ethics, they remind researchers that data do not exist in a vacuum but that they are also a reflection of people, histories, and futures.
When combined with FAIR, open science can promote data ecosystems that are both open and just, innovative and respectful, global and grounded in community rights. These steps might guide researchers working with indigenous communities to include protected time for relationship building in the early stages of the project lifecycle; ensure they reflect indigenous knowledge systems in notices, licences and agreements; play a role in supporting community capacity-building; uphold equal attribution including acknowledgement and authorship in publications; disclose benefit sharing plans as part of data policy requirements required by funders, and more.
If you have any feedback for this blog post or would like to discuss any of the ideas shared here, please contact the Research Data Management Team.
Acknowledgements:
We acknowledge the important work of the members of the Global Indigenous Data Alliance (GIDA) alongside the following people whose knowledge and scholarship informed this blog:
- Jane Anderson
- Stephanie Russo Carroll
- Oscar L. Figueroa‑Rodríguez
- Ibrahim Garba
- Edit Herczog
- Jarita Holbrook
- Maui Hudson
- Raymond Lovett
- Andrew Martinez
- Simeon Materechera
- Mark Parsons
- Kay Raseroka
- Desi Rodriguez‑Lonebear
- Robyn Rowe
- Keith Russell
- Rodrigo Sara
- Cas Sedran‑Price
- Shelley Stall
- Riley Taitingfong
- Jennifer D. Walker
We are also grateful to Imperial colleagues who participated in the informal discussion that took place on 4 December 2025, ‘SCM Forum: CARE Principles’.
Useful Resources:
- CARE Principles: https://www.gida-global.org/care
- FAIR Principles: https://www.go-fair.org/fair-principles/
- Local Contexts website: https://localcontexts.org/about/
- Research and Indigenous Librarianship Resource List: International Perspective: https://indigenousdatalab.org/wp-content/uploads/2025/05/International-Resource-List.pdf
- Relational Science podcast: https://open.spotify.com/show/7lpKP6htmByX8hxOVYpird
- UNESCO Recommendation on Open Science: https://www.unesco.org/en/open-science/about
- Unsettling Knowledge Inequities podcast: https://knowledgeequitylab.ca/podcast/
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Carroll, S.R. et al. (2020) ‘The CARE Principles for Indigenous Data Governance’, Data Science Journal, 19(1). Available at: https://doi.org/10.5334/dsj-2020-043.
Carroll, S.R. et al. (2021) ‘Operationalizing the CARE and FAIR Principles for Indigenous data futures’, Scientific Data, 8(1), p. 108. Available at: https://doi.org/10.1038/s41597-021-00892-0.
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Ravindran, S. (2024) ‘Not a free-for-all’: Indigenous communities want limits on how their data are shared. Available at: https://www.science.org/content/article/not-free-all-indigenous-communities-want-limits-how-their-data-are-shared (Accessed: 9 February 2026).
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