The Environmental Data Science book

A living, open and community-driven online resource to showcase and support the publication of data, research and open-source tools for collaborative, reproducible and transparent Environmental Data Science.

Information	Links
Project
News
Chat
Build
Cite

Contributors

We welcome and recognize all contributions. You can see a list of current contributors in the contributors tab.

Alejandro © 📖 👀 🚧 📆 📋 💬 📢	Amandine Debus 👀	Andrés Camilo Zúñiga-González 📝 💻	Anne Fouilloux 🤔 🚇 🚧 👀	Anne Lee Steele 🤔	Bryn N. Ubald ⚠️ 📝 💻	Cam Appel 📝 💻
Caroline Arnold 👀	Daniela Pinto Veizaga 📝 💻	Delphine Lariviere 🤔	Devanjan Bhattacharya 👀	Doran Khamis 👀	Ed Chalstrey 🤔	Esther Plomp 👀 🤔
Ethan White 👀	James Millington 🖋 📝 💻	Jim Circadian 📝 💻	Jorge Eduardo Peña Velasco 📝 💻	Kirstie Whitaker 🤔	Malvika Sharan 🤔	Matt Allen 👀
Matt Fry 👀	Meghna Asthana 👀	Mukulika 📝 💻	NHomer-Edi 🖋 👀	Owen Allemang 📝 💻	Paolo Pelucchi 👀	RUTIKA 📝 💻
RachelFurner 👀	Raquel Carmo 📝 💻	Ricardo Barros Lourenço 👀	Samuel Jackson 📝 💻	Sarah Gibson 🤔	Scott Hosking 🤔	Tina Odaka 👀
Tom Andersson 👀	Viktor Domazetoski 🐛 📝 💻	Wei Ji 👀	Will Gregory 👀	garimamalhotra 📝 💻	jmifdal 📝 💻	louisavz 👀
nbarlowATI 👀	oscarbau 👀	rsignell 🐛	shmh40 📝 💻	svadams 📝 💻	timo0thy 🖋 📝 💻

Acknowledgment

This work was supported by:

• Wave 1 of The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1 and EPSRC Grant EP/W006022/1, particularly the “AI for Science” theme within those grants & The Alan Turing Institute.
• EPSRC Grant EP/Y028880/1, A national UK programme in AI and digital twins to address the biodiversity and climate crisis, particularly the “Foster an open international environmental data science community” workstream led by The Alan Turing Institute.

From July 2024, the project is unfunded and is being maintained by the community.

Credits

The individual notebooks repositories are hosted at the eds-book organisation. The How to run section in the README of each notebook repository is adapted from the Project Pythia Cookbook project. The workflow actions to generate the rendered version of notebooks were adapted from 2i2c’s hub-user-image-template released under BSD-3-Clause license.

We also acknowledge the template of README, LICENSE and PULL_REQUEST_TEMPLATE provided by the Turing Way project. Other templates adapted include the review checklist/criteria templates provided by Turing Data Stories and SciPy Proceedings.

The project also thanks the OLS-4 training programme team, cohort and in special, Delphine Lariviere Delphine-L (mentor) for all their valuable knowledge, discussions and feedback.