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  • Data and tikanga

    Ngā Tikanga Paihere aligns with the Data Stewardship Framework, guiding good data practice and building public trust and confidence. Currently, it is used alongside the 5 safes framework to help evaluate applications to microdata at Stats NZ.

  • Annual feedback survey

    Each year we invite users of data.govt.nz to complete a short survey about their experience using this website.

  • The roadmap

    This page lays out the refreshed roadmap for the government data system of Aotearoa NZ. The roadmap was published as part of the Government Data System Strategy and Roadmap 2021.

  • Statistics Act review - join the conversation

    1975. The Corolla ruled, mix tapes were a ‘thing’ and the Stats Act became law. How things change! Actually… the legislation hardly has. It doesn’t even feature the word ‘data’. Far-out!

  • Steady state data flow mapping

    This page describes steady state data flow mapping, why it might be useful for you and what it involves. 

  • A club funded approach to IDI research

    Earlier this year Motu released new research that breaks down the rate of driver licence holders among different groups in in Aotearoa New Zealand.

  • Launch of a new GCDS speaker series, Raraunga Ara Rau

    Earlier today, the first of a new GCDS speaker series, Raraunga Ara Rau, took place at Stats NZ. Read more about it here. 

  • Principle 3: Wānanga & Kaitiaki

    Principle 3: Use good data standards and practices. This principle includes ngā tikanga Wānanga (organisations) and Kaitiaki (guardians).

  • Thanks for your input: September 2018 data.govt.nz community feedback results

    We look at the latest results from the data.govt.nz community feedback survey, to find out what works for you, what doesn't, and how we can improve the experience of using data.govt.nz.

  • Controlling access to your data to keep it safe

    Protecting the confidentiality of information people supply is essential to retaining public trust and confidence in the system. Without cooperation, willingness to provide data can be too low and threaten its accuracy or the usefulness.

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