This page describes holistic data governance, how it differs from other approaches, why you might consider it, and what it might involve.
The initial terms of reference for the New Zealand Government-Te Kāwanatanga o Aotearoa Algorithm Charter Community of Practice outlines the purpose, role, and membership of the CoP in its establishment phase.
An early paper on the data flow model, with a particular emphasis on how it was being implemented at Stats NZ. This paper was written by…
In November 2021 we wrote about co-developing NZ’s first transport sector open data framework and we're excited to announce that it's now live and ready for…
Stats NZ's dashboard for March 2019 quarter which highlights key deliverables for its data leadership role under the Government Chief Data Steward function.
Learn about the lifecycle of a dataset, and data management plans (DMP), why they are important, and how to write one.
Principle 1: Have appropriate expertise, skills, and relationships with communities. This principle includes ngā tikanga Pūkenga (skills and expertise) and Whakapapa (genealogy).
The Institute of Environmental Science and Research Ltd (ESR) has developed a Responsible AI Framework guided by the Algorithm Charter for New Zealand. Read more about it here.
A high-level summary of the approach to data governance that guides implementation of the operational Data Governance Framework and use of Steady State Data Flow mapping.…
Learn about the decisions you need to make before creating a data dictionary and the tools that might help. Explore examples of data dictionaries published by…