Koh, Yun SingBifet, AlbertBryan, Karin R.Cassales, GuilhermeGraffeuille, OlivierLim, Nick Jin SeanMourot, PhilNing, DingPfahringer, BernhardVetrova, VarvaraMurilo Gomes, HeitorLarson, K2024-10-112024-10-112024Koh, Y. S., Bifet, A., Bryan, K., Weigert Cassales, G., Graffeuille, O., Lim, N., Mourot, P., Ning, D., Pfahringer, B., Vetrova, V., & Murilo Gomes, H. (2024). Time-evolving data science and artificial intelligence for Advanced Open Environmental Science (TAIAO) programme. IJCAI International Joint Conference on Artificial Intelligence, 7314-7322. https://doi.org/10.24963/ijcai.2024/809https://hdl.handle.net/10289/16982New Zealand's unique ecosystems face increasing threats from climate change, impacting biodiversity and posing challenges to safety, livelihoods, and well-being. To tackle these complex issues, advanced data science and artificial intelligence techniques can provide unique solutions. Currently, in its fourth year of a seven-year program, TAIAO focuses on methods for analyzing environmental datasets. Recognizing this urgency, the open-source TAIAO platform was developed. This platform enables new artificial intelligence research for environmental data and offers an open-access repository to enhance reproducibility in the field. This paper will showcase four environmental case studies, artificial intelligence research, platform implementation details, and future development plans.© 2024 International Joint Conferences on Artificial Intelligence (IJCAI).http://creativecommons.org/licenses/by/4.0/computer sciencemachine learningConference Contribution10.24963/ijcai.2024/80946 Information and Computing Sciences4611 Machine Learning