/environmental-ds-book

A computational notebook community for open environmental data science 🌎

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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.

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Contributors

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

Alejandro Β©
Alejandro Β©

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Amandine Debus
Amandine Debus

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Anne Fouilloux
Anne Fouilloux

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Anne Lee Steele
Anne Lee Steele

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Daniela Pinto Veizaga
Daniela Pinto Veizaga

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Delphine Lariviere
Delphine Lariviere

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Doran Khamis
Doran Khamis

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Ed Chalstrey
Ed Chalstrey

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Esther Plomp
Esther Plomp

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James Millington
James Millington

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Jorge Eduardo PeΓ±a Velasco
Jorge Eduardo PeΓ±a Velasco

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Kirstie Whitaker
Kirstie Whitaker

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Malvika Sharan
Malvika Sharan

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Matt Allen
Matt Allen

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Matt Fry
Matt Fry

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NHomer-Edi
NHomer-Edi

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RachelFurner
RachelFurner

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Raquel Carmo
Raquel Carmo

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Ricardo Barros Lourenço
Ricardo Barros Lourenço

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Samuel Jackson
Samuel Jackson

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Sarah Gibson
Sarah Gibson

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Scott Hosking
Scott Hosking

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Tom Andersson
Tom Andersson

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Viktor Domazetoski
Viktor Domazetoski

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garimamalhotra
garimamalhotra

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jmifdal
jmifdal

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nbarlowATI
nbarlowATI

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oscarbau
oscarbau

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shmh40
shmh40

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svadams
svadams

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timo0thy
timo0thy

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Acknowledgment

This work was supported by Wave 1 of The UKRI Strategic Priorities Fund under the EPSRC Grant EP/W006022/1, particularly the Environment & Sustainability theme within that grant & The Alan Turing Institute.

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 toward a common goal Open Science for All.

Credits

This project is created using the excellent open source Jupyter Book project and the executablebooks/cookiecutter-jupyter-book template. The individual notebooks repositories are hosted at the eds-book-gallery 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.