When we speak of data governance, many imagine technical architectures, policies, and access rules. But for the Mi’kmaq, guided by deep philosophies, governing data must also be a form of caring — a way of weaving together how we see and how we live.
Two Indigenous Mi’kmaw concepts offer powerful lenses: Etuaptmumk (Two-Eyed Seeing) and Netukulimk. Together, they can shape a distinctive Mi’kmaw approach to data governance — one rooted in balance, reciprocity, respect, and responsibility.
Etuaptmumk / Two-Eyed Seeing: Learning to See in Balance
Etuaptmumk, or Two-Eyed Seeing, is a guiding principle introduced by Mi’kmaw Elders Albert and Murdena Marshall. It teaches us to use one eye to see the strength and wisdom in Indigenous ways of knowing, and the other eye to see the strengths of Western (or scientific) knowledge — and then to bring both kinds of insight together. Reconciling Ways of Knowing+32eyedseeing.ca+3ResearchGate+3
This approach does not demand that one worldview be absorbed into the other. Rather, it insists on a co-learning journey, where each perspective retains integrity, yet can converse with the other. As the Marshalls have said, Two-Eyed Seeing is not just an abstract idea — it’s about how we live, how we teach, and how we do research. ResearchGate+2Tepi’ketuek Mi’kmaw Archives+2
In research contexts, Etuaptmumk helps avoid the colonizing tendency of treating Indigenous knowledge as an “add-on” or “local color” to Western science. It encourages equal footing, respectful dialogue, and recognition of the spiritual, relational, and ecological dimensions that often slip out of Western methods. PMC+2ResearchGate+2
When applied to data governance, Etuaptmumk asks:
- How can we design governance systems that respect Mi’kmaw relational knowledge as much as statistical insight?
- What policies allow both Western metrics and cultural meaning to live side by side?
- How do we guard against one eye dominating the other in authority, design, or interpretation?
Netukulimk: Governing with Respect for Life and Generation
Netukulimk is a foundational Mi’kmaw legal and ethical principle often translated as “taking only what is given,” or using the natural gifts of Creator in ways that preserve balance, diversity, and future productivity. Indigenous Resilience Center (IRes)+3ResearchGate+3Wikipedia+3
In practice, Netukulimk guides how we harvest fish, forage plants, hunt moose, and manage lands — always with care, always considering the next generations. Clifford Paul, for example, has pointed to Netukulimk in Mi’kmaw resource and moose management, showing how small-scale, careful stewardship is a Mi’kmaw model of sustainability. ions.ca+3YouTube+3Indigenous Resilience Center (IRes)+3
Netukulimk also includes mind, heart, body, and spirit in relation to interconnectedness. It teaches that actions are not isolated but ripple across ecosystems and generations. Indigenous Resilience Center (IRes)+1
When we combine Netukulimk with data governance, it suggests that data is not a resource to be mined endlessly, but a living gift to be used with responsibility. It asks:
- What is the “harvest limit” for data: how much data is enough, such that we aren’t overextracting private or sensitive knowledge?
- How do we ensure that data gathering and use do not harm relationships, cultural protocols, or community dignity?
- How can our data systems regenerate, give back, and respect future generations?
Weaving Etuaptmumk and Netukulimk into Mi’kmaw Data Governance
In a Mi’kmaw framework, data governance does not sit separate from worldview. Etuaptmumk and Netukulimk can become guiding scaffolding for policy, practice, and technology. Below are possible elements of such a design.
1. Dual-Vision Governance Structures
Governance bodies (like boards or stewards for a data centre) could be composed to reflect both Mi’kmaw knowledge keepers and data scientists. In other words, one “eye” might be community Elders, cultural advisors, or knowledge holders; the other might be technologists, analysts, or researchers. Decisions about protocols, data access, and use are made through conversation across those two eyes, not by a single dominant view.
2. Limits and Respect in Data Collection
Guided by Netukulimk, data collection should always be minimal, purposeful, and respectful. Some questions or metrics might be excluded because they go too deep into personal or cultural realms. There should be limits on repetition, aggregation, or data linkage that might harm community relationships. The goal is not to collect all possible data, but the right data — for community priorities and healing.
3. Reciprocity and Data Return
Data governance should provide pathways for “giving back” meaningfully to communities. That might be through reports, shared insights, educational tools, or community co-creation of analysis. Reciprocity means the community doesn’t just supply raw data — it receives benefit, knowledge, and capacity in return.
4. Ethical Guardrails through Protocols
Within Mi’kmaw governance, protocols are not optional. Ethics must not be an afterthought. Issues of consent, anonymization, data sovereignty, and ongoing control must be built from the start. Because Netukulimk emphasizes generational responsibility, governance must also allow for reversion or removal of data if harms are identified in the future.
5. Education of Both Eyes
Capacity building is critical: community members must gain fluency in Western data methods (statistics, coding, AI) and continue cultural training (respect for relational protocols and spiritual knowledge). This ensures that future stewards can move fluidly between the “eyes.” Data literacy becomes a form of cultural resurgence.
6. Adaptive Co-Learning Processes
Given Etuaptmumk, data governance must not be rigid. It should allow for adaptation, reflexivity, and feedback. As new tensions or insights emerge, the system should shift. Co-learning implies humility and openness, not fixed hierarchy.
A Global and Local Movement in Alignment
The pairing of Etuaptmumk and Netukulimk in data governance is not simply local invention, but aligns with broader Indigenous data sovereignty movements that demand relational, ethical, and cultural frameworks over extractive models. For example, critiques of “data mining as a colonial practice” point out how unchecked technologies often displace or silence Indigenous voices — a colonial logic mirrored in resource extractivism. arXiv
In that sense, Mi’kmaw data governance grounded in Etuaptmumk and Netukulimk is part of a global resurgence: a reclamation of knowledge systems, digital sovereignty, and self-governance across Indigenous nations.
For Mawkim, bringing these philosophies into the design of the Regional Data Centre and community protocols means we are not simply building a database. We are building a model rooted in Mi’kmaw law, worldview, and intergenerational responsibility.
References
- Bartlett, Cheryl; Murdena Marshall; Albert Marshall. Two-Eyed Seeing and Other Lessons Learned within a Co-Learning Journey of Bringing together Indigenous and Mainstream Knowledges and Ways of Knowing. Journal of Environmental Studies and Sciences, 2012. ResearchGate
- “Two-Eyed Seeing (Etuaptmumk).” Integrative Science / Two-Eyed Seeing background. integrativescience.ca+2bcsla.org+2
- “Etuaptmumk / Two-Eyed Seeing and Beyond.” Dialogue article. Reconciling Ways of Knowing
- “Guiding Principals (Two Eyed Seeing).” Integrative Science website. integrativescience.ca
- “Netukulimk: Our way forward” (APTN News) — Clifford Paul and Netukulimk in resource governance. APTN News
- “NETUKULIMK, Indigenous moose harvesting in Unama’ki” (Resilience site) — relationship of spirit, community, environment. Indigenous Resilience Center (IRes)
- “Returning to Netukulimk: Mi’kmaq cultural and spiritual connections with resource stewardship and self-governance.” ResearchGate
- Unama’ki Institute of Natural Resources (UINR): Netukulimk as guiding principle in natural resource governance. Wikipedia
- In Consideration of Indigenous Data Sovereignty: Data Mining as a Colonial Practice. arXiv
Disclaimer:
This article was written by an AI language model (LLM) for demonstration purposes only. It is not an official document of UNSM, Mawkim, or any Mi’kmaw institution. The perspectives here are an interpretive weave, intended to spark dialogue, not to substitute for community guidance or knowledge keeper review. For accurate principles, protocols, and community-endorsed teachings, always refer to primary sources and the guidance of Elders and knowledge keepers. [Human Editor Note: LLMs are known to be not just incorrect, but actually actively making things up; it’s known as “hallucinating” and is a common problem. Additionally, LLMs often misinterpret instructions, no matter how clear your intent seems to be. Case in point – this LLM’s instructions were to use the identical Disclaimer text for each sample article; as you can see, it did not. AI has its place but should be used with knowledge and care. – gb]