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Open data, FAIR, CARE and research partnerships

Open data and Māori Data Sovereignty are not opposites. Māori organisations may choose to make information widely available where that serves the kaupapa. The important distinction is between deliberate sharing and openness being treated as the default simply because a platform, funder or agency prefers it.

Public access does not settle reuse​

A document, map or dataset being publicly accessible answers one question: whether people can obtain it. It does not automatically answer whether every piece of information within it should be extracted, joined, interpreted, mapped at greater precision or republished in another form.

This matters for public Waitangi Tribunal material, historical records, planning evidence, newspapers, Gazette notices, maps and open government datasets. A source may include whakapapa-linked kōrero, sensitive locations, disputed evidence, approximate geography or information provided for a particular inquiry or purpose.

GIS and AI can change the effect of that information. Extracting hundreds of references into one table can make patterns visible that were difficult to see in the original sources. Geocoding can turn a loose historical description into a precise-looking point. Joining a public layer to parcels, addresses or imagery can create a new disclosure.

Keep the source and context with derived information, and consider whether the new dataset or map changes the sensitivity, certainty or intended audience of the original material.

See Before you use AI with Māori information, Inference risk and Provenance and source checking.

FAIR solves a different problem​

FAIR encourages data to be:

  • Findable
  • Accessible
  • Interoperable
  • Reusable

These properties are useful for science, government and GIS interoperability. They do not answer questions about whakapapa, collective benefit, local relationships or what future uses make sense for a particular kaupapa.

CARE adds people and purpose​

The Global Indigenous Data Alliance developed CARE around:

  • Collective Benefit
  • Authority to Control
  • Responsibility
  • Ethics

CARE complements FAIR by bringing people, relationships, power and historical context into the picture.

For Māori GIS, FAIR and CARE can sit alongside kaupapa, tikanga, rangatiratanga and kaitiakitanga rather than being treated as competing frameworks.

See Rangatiratanga and Māori data, Whakapapa of data and Kaupapa Māori GIS.

Intentional openness can support rangatiratanga​

Māori-controlled publication can support:

  • restoration of traditional place names
  • environmental advocacy
  • public education
  • evidence in planning
  • whānau and rangatahi access
  • accountability of agencies
  • research collaboration

The useful question is not simply open or closed? It is what kind of sharing serves the kaupapa and what context should travel with the information.

More restriction is not always better​

Excessive restriction can:

  • duplicate field collection
  • make whānau access harder
  • reduce environmental research benefit
  • make datasets invisible to future Māori researchers
  • discourage rangatahi engagement
  • create systems that are difficult to maintain

Rangatiratanga includes the ability to share deliberately as well as the ability to keep information within a smaller group.

Iwi data-sharing guidance​

Te Kāhui Raraunga published Iwi Data Sharing Guidance in June 2026 as a preliminary position and decision framework for individual-level iwi data. The guidance is useful because it asks practical questions about whether individual-level data is actually needed, what benefit is expected, how data will be stored, whether it will be linked with other datasets, whether AI is involved, and what happens to the data later.

For spatial data, extra questions include:

  • does location make a record identifiable?
  • how much spatial precision is needed for the task?
  • what new information appears after joining with parcels, addresses or other geography?
  • what derived spatial products are created?

This is especially relevant where a table appears de-identified but a coordinate or small-area geography makes the person or place obvious.

See Inference risk, Sensitive places and Templates and registers.

Research should leave usable material behind​

The Nunatsiavut case study provides a useful international warning. Researchers examined projects approved by the Nunatsiavut Government Research Advisory Committee between 2011 and 2021 and found that, in two-thirds of projects, researchers did not return the data they had collected.

For Māori GIS research, useful return products can include:

  • source spatial data where that forms part of the arrangement
  • metadata
  • code lists
  • attachments
  • method documentation
  • open or software-independent exports
  • maps and reports
  • code or scripts used to create important derivatives

A PDF report may be useful, but it is not the same thing as returning reusable GIS data where that was part of the research relationship.

See Working with consultants, GIS succession and When funding ends.

Local Contexts and richer metadata​

Local Contexts Traditional Knowledge and Biocultural Labels allow Indigenous communities to express provenance, protocols and expectations through metadata. Examples include culturally sensitive, community-use and non-commercial conditions.

The value for GIS is the reminder that metadata can communicate much more than copyright and licence terms. It can preserve some of the whakapapa and context of a dataset as it travels.

See Metadata and documentation and Attribution, sources and metadata.

Research derivatives matter​

A research project may create:

  • cleaned datasets
  • geocoded records
  • model outputs
  • maps
  • classifications
  • inferred sites
  • code
  • embeddings or AI-derived outputs

Those derivatives can be as important as the source data. A good project record makes clear which outputs come back, which remain with the research team, and what future use is expected.

A useful research discussion​

Before spatial data moves into a research project, it can help to be clear about:

  1. kaupapa and expected benefit
  2. datasets and level of spatial detail
  3. people or organisations involved in decisions about the data
  4. who will work with it
  5. analyses and joins expected
  6. derivatives that will be created
  7. public outputs
  8. source acknowledgement and metadata
  9. AI or automated analysis
  10. data and code return
  11. archive and retention
  12. what happens when the project ends

That is a project-design conversation, not a universal approval checklist.

Keep researching​

This page should not be the only source used to make an open-data or research decision. Consider the Māori-led frameworks, project agreements, iwi or hapū policies, ethics requirements, legal obligations, licences and current organisational guidance that apply to the particular mahi.

Useful starting points include Te Mana Raraunga, Te Kāhui Raraunga, Ngā Tikanga Paihere, CARE and Local Contexts.

See Further reading and frameworks for a wider set of sources. Revisit the decision if the research purpose, data, technology, partners or publication plans change.

Sources​

Last verified: 2 September 2026

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