Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme

Yun Sing Koh; Albert Bifet; Karin Bryan; Guilherme Cassales; Olivier Graffeuille; Nick Lim; Phil Mourot; Ding Ning; Bernhard Pfahringer; Varvara Vetrova; Heitor Gomes

Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme

Yun Sing Koh
, Albert Bifet
, Karin Bryan
, Guilherme Cassales
, Olivier Graffeuille
, Nick Lim
, Phil Mourot
, Ding Ning
, Bernhard Pfahringer
, Varvara Vetrova
, Heitor Gomes

University of Auckland
University of Waikato
Waikato Regional Council
University of Canterbury
Victoria University of Wellington

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

Résumé

New 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.

langue originale	Anglais
titre	Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
rédacteurs en chef	Kate Larson
Editeur	International Joint Conferences on Artificial Intelligence
Pages	7314-7322
Nombre de pages	9
ISBN (Electronique)	9781956792041
état	Publié - 1 janv. 2024
Evénement	33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 - Jeju, Corée du Sud Durée: 3 août 2024 → 9 août 2024

Série de publications

Nom	IJCAI International Joint Conference on Artificial Intelligence
ISSN (imprimé)	1045-0823

Une conférence

Une conférence	33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
Pays/Territoire	Corée du Sud
La ville	Jeju
période	3/08/24 → 9/08/24

SDG des Nations Unies

Ce résultat contribue à ou aux Objectifs de développement durable suivants

SDG 13 Action climatique

Contient cette citation

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. Dans K. Larson (Ed.), Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 (p. 7314-7322). (IJCAI International Joint Conference on Artificial Intelligence). International Joint Conferences on Artificial Intelligence.

Koh, Yun Sing ; Bifet, Albert ; Bryan, Karin et al. / Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024. Editeur / Kate Larson. International Joint Conferences on Artificial Intelligence, 2024. p. 7314-7322 (IJCAI International Joint Conference on Artificial Intelligence).

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title = "Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme",

abstract = "New 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.",

author = "Koh, \{Yun Sing\} and Albert Bifet and Karin Bryan and Guilherme Cassales and Olivier Graffeuille and Nick Lim and Phil Mourot and Ding Ning and Bernhard Pfahringer and Varvara Vetrova and Heitor Gomes",

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year = "2024",

month = jan,

day = "1",

language = "English",

series = "IJCAI International Joint Conference on Artificial Intelligence",

publisher = "International Joint Conferences on Artificial Intelligence",

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}

Koh, YS, 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. Dans K Larson (Ed.), Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024. IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, p. 7314-7322, 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024, Jeju, Corée du Sud, 3/08/24.

Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. / Koh, Yun Sing; Bifet, Albert; Bryan, Karin et al.
Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024. Ed. / Kate Larson. International Joint Conferences on Artificial Intelligence, 2024. p. 7314-7322 (IJCAI International Joint Conference on Artificial Intelligence).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

TY - GEN

T1 - Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme

AU - Koh, Yun Sing

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AU - Bryan, Karin

AU - Cassales, Guilherme

AU - Graffeuille, Olivier

AU - Lim, Nick

AU - Mourot, Phil

AU - Ning, Ding

AU - Pfahringer, Bernhard

AU - Vetrova, Varvara

AU - Gomes, Heitor

PY - 2024/1/1

Y1 - 2024/1/1

N2 - New 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.

AB - New 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.

M3 - Conference contribution

AN - SCOPUS:85204303270

T3 - IJCAI International Joint Conference on Artificial Intelligence

SP - 7314

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BT - Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024

A2 - Larson, Kate

PB - International Joint Conferences on Artificial Intelligence

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Y2 - 3 August 2024 through 9 August 2024

ER -

Koh YS, Bifet A, Bryan K, Cassales G, Graffeuille O, Lim N et al. Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. Dans Larson K, Editeur, Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024. International Joint Conferences on Artificial Intelligence. 2024. p. 7314-7322. (IJCAI International Joint Conference on Artificial Intelligence).

Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme

Résumé

Série de publications

Une conférence

SDG des Nations Unies

Empreinte digitale

Contient cette citation