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  • Mandated data standard for gender and sex

    A new mandated data standard for gender and sex was recently approved for use across the Public Service.

  • References

    The development of Ngā Tikanga Paihere relied heavily on the use of external key sources. We provide these key sources to help others curious about this kaupapa to explore.

  • Change to mandated data standards

    The process for selecting mandated data standards (previously called Data Content Requirements, or DCRs) has been updated and approved by the Information Group.

  • Group members

    The Data Ethics Advisory Group comprises 7 members, including the Chair.

  • Harnessing emerging technology to improve Kiwis’ lives

    Our Interim Centre for Data Ethics and Innovation provides support to maximise opportunities from new and emerging data. Learn more about the centre and how you can get involved. 

  • Centre for Data Ethics and Innovation news and commentary: February 2025

    The following articles are from the Centre for Data Ethics and Innovation's February 2025 newsletter. The newsletter comes out quarterly, full of news, commentary, opinion, and education.…

  • Video transcript: Luis Carrasqueiro

    Kia ora.

    I am helping deliver consulting services that enable organisations to increase their data capability and know-how by brokering access to specialist knowledge here at Stats…

  • What are tikanga?

    Tikanga are appropriate customary practices or ‘layers of the culture’ developed by Māori communities and individuals and informed by common cultural values and concepts.

  • Data stewardship and the role of national statistical offices

    In April 2024, the United Nations Economic Commission for Europe (UNECE) published a guide to help national statistical offices understand the importance of data stewardship and their changing roles as data stewards.

  • Searching for more than datasets

    We tested two concepts with a number of our users from the data community to extend the search so it includes results from both datasets and content. Read about our process and provide your feedback.

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