Research and Publications

Introduction

This article introduces the TAIAO research programme, outlining how it advances time‑evolving data science and artificial intelligence to support open, scalable, and impactful environmental science in Aotearoa. It highlights the programme’s interdisciplinary approach, combining machine learning, environmental modelling, and open‑source tools to address complex, rapidly changing environmental challenges.

Key outcomes

• Establishes a national research framework for time‑evolving data science applied to environmental systems.

• Demonstrates how AI and machine learning can support real‑time environmental monitoring and decision‑making.

• Presents open‑source tools, datasets, and methodologies developed through the TAIAO programme.

• Showcases collaborative research across universities, Crown Research Institutes, and industry partners.

• Highlights applications in areas such as climate modelling, biodiversity monitoring, and environmental forecasting.

Funding

This work was supported by TAIAO – Time‑Evolving Data Science / Artificial Intelligence for Advanced Open Environmental Science, funded by the New Zealand Ministry of Business, Innovation and Employment (MBIE).

How to cite this article

APA 7th Edition: Koh, Y. S., Bifet, A., Bryan, K., Cassales, G., Graffeuille, O., Lim, N., Mourot, P., Ning, D., Pfahringer, B., Vetrova, V., & Gomes, H. (2024). Time‑evolving data science and artificial intelligence for Advanced Open Environmental Science (TAIAO) programme.

MLA 9th: Koh, Yun Sing, et al. “Time‑evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme.” 2024.

Chicago (Author-Date): Koh, Yun Sing, Albert Bifet, Karin Bryan, Guilherme Cassales, Olivier Graffeuille, Nick Lim, Phil Mourot, Ding Ning, Bernhard Pfahringer, Varvara Vetrova, and Heitor Gomes. 2024. “Time‑evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme.”