Abstract

The Environmental Data Science Book (or EDS Book) is a pan-european community-driven resource hosted on GitHub and powered by Jupyter Book. The resource leverages executable notebooks, regional cloud resources and technical implementations of the FAIR principles to support the publication of datasets, innovative research and open-source tools in environmental science. The EDS book does not aim to replace academic journals. It is a pedagogical opportunity maximizing open infrastructure services to translate research outputs into curated, interactive, shareable and reproducible executable notebooks which benefit from a collaborative and transparent reviewing process.

Building upon existing global open science communities such as the Turing Way and Pangeo, the EDS book provides clear guidelines for submission and reviewing, templates for creating and scheduling notebooks using GitHub Actions CI/CD tools, FAIR practices through RoHub (a platform suited for managing, sharing and preserving earth system and environmental research objects) and Binder to facilitate fully documented, shareable and reproducible notebooks.

The quality of the published content is ensured by a transparent reviewing process supported by GitHub related technologies. To date, the community has successfully published ten python-based notebooks covering a wide range of topics in environmental data science. The notebooks consume open-source python libraries e.g., intake, iris, xarray, hvplot for fetching, processing and interactively visualizing environmental research.

In future work, we expect to increase contributions showcasing scalable and interoperable open-source developments in other programming languages e.g Julia and R, and engage with computational notebooks communities alike towards improving scientific software practices in environmental science.

What is the EDS book?

• A book: https://edsbook.org
• An open source project: https://github.com/alan-turing-institute/environmental-ds-book
• A community: The EDS book is also an open-source collaborative project that involves and supports its members of diverse skills and backgrounds to ensure that data science is accessible and useful for everyone interested in Environmental sciences.

Impact and outreach over last 12 months

Metrics of success

• 51 GitHub starts (top 20 most starred repository on the Alan Turing Institute GitHub organisation, https://github.com/alan-turing-institute)
• 10 executable notebooks (see the monitoring board in https://github.com/alan-turing-institute/environmental-ds-book/projects/2)
• 23 contributors
• 189 Twitter followers (see https://twitter.com/eds_book)
• Highlighted in the Supporting Pangeo: the community-driven platform for Big Data geoscience project page, https://www.turing.ac.uk/research/research-projects/supporting-pangeo-community-driven-platform-big-data-geoscience
• Highlighted in a FOSS4G 2022 workshop aiming to teach the basics of Pangeo, an open-source stack suited for big geoscience data https://pangeo-data.github.io/foss4g-2022/afterword/envds-book.html

Presentations

• European Geophysical Union 2022 (EGU22), https://meetingorganizer.copernicus.org/EGU22/EGU22-3739.html
• UK Conference on Environmental Data Science, https://wp.lancs.ac.uk/ceds/abstracts/abstracts-6th-july-22/#castro
• The Turing Way Fireside chat, https://www.youtube.com/watch?v=EeeRZZ3-Stc
• AGU22, Open Science Practices and Success Stories Across the Earth, Space and Environmental Sciences session, https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1072564