TAIAO is a data science programme funded by the Ministry of Business, Innovation, and Employment, which aims to improve the accessibility and usability of environmental data for researchers, scientists, and the wider community.

The programme is a collaboration between several universities and organisations, including the Universities of Waikato, Auckland, Canterbury, and Victoria University Wellington, as well as Beca and MetService.

Work and purpose

Recognising that good data is essential to research, understand, and set policy for effective management of our natural environment, the team at TAIAO aim to develop new machine learning methods that are tailored to process environmental data gathered from our New Zealand context.

TAIAO plan to codesign their work with iwi, industry, and government with the vision of harnessing data science to preserve our natural resources. In parallel with developing open-source software, TAIAO is working to build New Zealand’s environmental data science capabilities through the delivery of workshops, undergraduate, and postgraduate research projects. The team also stay connected with international researchers to see where they can adapt the latest global advancements to our unique environment.

An example of a tool made by TAIAO is the Aotearoa Species Classifier. This publicly-available app uses machine learning to help people identify around 11,000 species of New Zealand flora and fauna.

Community

TAIAO brings together a community of likeminded thinkers across a number of disciplines to share data and build capacity in the environmental space. The TAIAO platform allows data scientists to view and share datasets and notebooks, access software and tutorials, and have discussions with the wider TAIAO community.

Get Involved

Are you passionate about finding solutions to some of the biggest environmental problems facing New Zealand, and the world? Come join us! Head to our community page to sign up here.

Who are we?

Project Partners

Meet the team

Prof. Albert Bifet, Project Leader, AI Institute, University of Waikato
Prof. Karin Bryan, School of Environment, University of Auckland
Prof. Bernhard Pfahringer, AI Institute, University of Waikato
Prof. Eibe Frank, AI Institute, University of Waikato
Dr. Phil Mourot, Senior Research Fellow, University of Waikato and Waikato Regional Council
Assoc. Prof. Te Taka Keegan, AI Institute, University of Waikato
Prof. Geoff Holmes, Pro Vice Chancellor - Health, Engineering, Computing, and Science, University of Waikato

Dr. Yun Sing Koh, School of Computer Science, The University of Auckland
Dr. Joerg Wicker, School of Computer Science, The University of Auckland
Dr. Varvara Vetrova, College of Engineering, University of Canterbury
Dr. Heitor Murilo Gomes, School of Engineering and Computer Science, Victoria University of Wellington

Dr. Nick Lim, Postdoctoral Fellow, AI Institute, University of Waikato
Dr. Guilherme Weigert Cassales, Postdoctoral Fellow, AI Institute, University of Waikato
Dr. Anany Dwivedi, Postdoctoral Fellow, AI Institute, University of Waikato
Dr. Yaqian Zhang, Postdoctoral Fellow, AI Institute, University of Waikato
Mr. Peter Reutemann, Senior Research Programmer, Department of Computer Science, University of Waikato
Corey Sterling, Research Programmer, AI Institute, University of Waikato

Gregory Pearson, Meteorological Design Engineer, MetService

Orlando Kootstra, Manager - Digital Services, Beca Group Limited
Monica Daniel, Senior Project Manager, Beca Group Limited
Stephen Witherden, Beca Group Limited
Megan Taylor-Silva, Senior Communications and Engagement Advisor, Beca Group Limited.

Dr. Moritz Lehmann, Senior Scientist, Xerra
Christopher McBride, Senior Research Officer, Environmental Research Institute, University of Waikato