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Principle 5: Tapu & Noa

Principle 5: Balance benefits and risks. This principle includes ngā tikanga Tapu (sacred, prohibited, restricted, or to be set apart) and Noa (ordinary, unrestricted, or normality).

Tapu | Sacred, prohibited, restricted, or to be set apart

He whakamārama | Meaning

Kei raro i te mana o ngā atua, o te wāhi ngaro, kei raro rānei i ngā here o te whakapono, e rāhuitia ana, kāore e tika ana kia takahia, kia raweketia. Kei tua atu i te kaha o tētahi, kāore e taea.

E tika ana kia noho (te kōrero) ki waenga i ngā tāngata anake kua whakaritea kia mōhio.

The concept of tapu is an important element in all tikanga, and there are many meanings and conditions associated with tapu such as being sacred, prohibited, restricted, set apart, or forbidden.

Tapu comes from the gods and embraces all the powers and influences associated with them. Everything (including land, oceans, rivers, forests, and people) has inherent tapu and the level of tapu can change depending on the context.

Tapu can even be applied when details are kept private between individuals who should know about such matters.


Sensitivities in the use of data are identified, including privacy issues for whānau and identifiable groups.

Research that examines the current state of people can have an element of sensitivity when integrating social, justice, economic, and health data about them. There is an obligation to keep data safe, protect privacy and confidentiality, and ensure appropriate use.

This tikanga consideration examines how well risks and issues have been identified and whether these have been considered prior to undertaking the research.

Researchers should be able to explain the nature and extent of associated risks (such as integrity of the original source data, risks to the data providers) and potential harms to individuals, collectives, businesses, or organisations, even when they are not easily identifiable.

These risks should be noted early and mitigations implemented if issues arise in later stages of the research.

Things to consider

  • Does the researcher intend to use restricted data, or data of a sensitive nature?
  • The consideration the researcher has given to how the data will be managed.
  • Any privacy concerns for individuals, whānau, and sections of communities.
  • Limitations in the data or in its use, and what could be done to address these.
  • Prior ethics approvals and permission sought for restricted data (for example, DHB data).
  • Risks, issues, and mitigations identified in a data management plan.

Noa | Ordinary, unrestricted, or normality

He whakamārama | Meaning

Ka noho wātea i ngā here o te taha wairua, ka noho tapu kore.

Rere māori, kāore he here o runga, ehara rānei i te mea i āta mahia he mahi kia pērā ai te āhua. Kāore he utu, hei aha te utu.

The standard definition of noa is when something is free from spiritual restrictions and is not sacred.

It can also be described as something that is free-flowing and not restricted in any way nor is it designed to work in such a way. Another explanation for noa is when something is free of charge and comes at no cost.

Noa can also be described as having much to do with normality and with reaching a state whereby a new idea is accepted, incorporated into the thinking of people, and is no longer is a cause for controversy.


Data is readily accessible and there is demonstrated awareness of the impact on communities of interest.

This tikanga consideration examines the potential benefits and opportunities of integrating and sharing data. Once the risks and potential harms have been identified, the benefits to communities of opening and unlocking new streams of information are examined.

These benefits are balanced with the risks and sensitivities that are identified in Mauri and Tapu.

Things to consider

  • Has the researcher demonstrated that potential risks have been balanced with benefits?
  • The value of the new information being revealed.
  • The extent to which the data could be made available to communities of interest.
  • Ways in which research findings may be shared widely by researchers or the organisations they work with, including plans to disseminate results through social media, blogs, vlogs, workshops, or presentations to large audiences.
  • Potential development opportunities with communities in the areas of data literacy, capability, and resource sharing.

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Content last reviewed 23 November 2020.

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