https://github.com/alan-turing-institute/data-safe-haven
https://github.com/alan-turing-institute/data-safe-haven
data-safe-haven hacktoberfest hut23 hut23-1304 hut23-190 hut23-448 hut23-612
Last synced: 22 days ago
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- Host: GitHub
- URL: https://github.com/alan-turing-institute/data-safe-haven
- Owner: alan-turing-institute
- License: bsd-3-clause
- Created: 2018-07-04T11:05:36.000Z (almost 7 years ago)
- Default Branch: develop
- Last Pushed: 2025-03-11T09:22:50.000Z (about 2 months ago)
- Last Synced: 2025-03-28T19:09:11.435Z (29 days ago)
- Topics: data-safe-haven, hacktoberfest, hut23, hut23-1304, hut23-190, hut23-448, hut23-612
- Language: Python
- Homepage: https://data-safe-haven.readthedocs.io
- Size: 155 MB
- Stars: 64
- Watchers: 17
- Forks: 16
- Open Issues: 78
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Codeowners: CODEOWNERS
- Security: SECURITY.md
- Roadmap: ROADMAP.md
Awesome Lists containing this project
README
# 👀 What is the Turing Data Safe Haven?
The **Turing Data Safe Haven** is an open-source framework for creating secure environments to analyse sensitive data.
It provides a set of scripts and templates that will allow you to deploy, administer and use your own secure environment.
It was developed as part of the Alan Turing Institute's [Data Safe Havens in the Cloud](https://www.turing.ac.uk/research/research-projects/data-safe-havens-cloud) project.
[](https://pypi.org/project/data-safe-haven/)
[](https://pypi.org/project/data-safe-haven/)
[](https://github.com/alan-turing-institute/data-safe-haven/releases)
[](https://data-safe-haven.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/alan-turing-institute/data-safe-haven/actions/workflows/lint_code.yaml)
[](https://github.com/alan-turing-institute/data-safe-haven/actions/workflows/test_code.yaml)
[](https://join.slack.com/t/turingdatasafehaven/signup)
[](https://github.com/alan-turing-institute/data-safe-haven/blob/develop/CITATION.cff)
[](#contributors-)
## 🧑🧑🧒 Community & support
- Visit the [Data Safe Haven website](https://data-safe-haven.readthedocs.io) for full documentation and useful links.
- Join our [Slack workspace](https://join.slack.com/t/turingdatasafehaven/shared_invite/zt-104oyd8wn-DyOufeaAQFiJDlG5dDGk~w) to ask questions, discuss features, and for general API chat.
- Open a [discussion on GitHub](https://github.com/alan-turing-institute/data-safe-haven/discussions) for general questions, feature suggestions, and help with our deployment scripts.
- Look through our [issues on GitHub](https://github.com/alan-turing-institute/data-safe-haven/issues) to see what we're working on and progress towards specific fixes.
- Send us an [email](mailto:[email protected]).
## 👐 Contributing
We are keen to transition our implementation from being a [Turing](https://www.turing.ac.uk/) project to being a community owned platform.
We have worked together with the community to develop the policy, processes and design decisions for the Data Safe Haven.
We welcome contributions from anyone who is interested in the project.
There are lots of ways to contribute, not just writing code!
See our [Code of Conduct](CODE_OF_CONDUCT.md) and our [Contributor Guide](CONTRIBUTING.md) to learn more about how we work together as a community and how you can contribute.
## Contributors
Alvaro Cabrejas Egea
💻 🖋
Arielle Bennett
🔍 🤔 📆
Benjamin Walden
📖 🤔 🐛 📆 📓
Brett Todd
💻 🤔
Callum Mole
🐛 💻
Carlos Gavidia-Calderon
🐛 🤔 📖
Catalina Vallejos
🖋
Catherine Lawrence
🖋 📖 🐛 🤔
Christopher Edsall
💻 📖 🐛
Daniel Allen
💻 🐛
Daniel Delbarre
🐛
David Beavan
📖 🖋
David Salvador Jasin
🐛 📖 🤔
David Sarmiento Perez
📖 📋 🔍 🤔 📆 📣 📢
Diego Arenas
💻 🤔 🖋
Ed Chalstrey
💻 📖 🐛 🤔 📋 👀 ⚠️
Evelina Gabasova
🖋
Federico Nanni
💻 🐛 📖 🤔
Franz Király
🖋
George Holmes
💻 🤔
Guillaume Noell
📖 🐛 🤔
Hari Sood
📖 🐛 🤔 🔍 📋 📆 📣 💬 📢 🛡️ 📓
Helen Duncan Little
🐛 👀 🤔
Helen Sherwood-Taylor
🤔 🖋
Ian Carter
💻 🖋
Jack Roberts
💻 🐛
James Cunningham
💻 📖 🐛 🤔 🖋
James Geddes
🖋
James Hetherington
📖 🐛 🤔 🔍 📆 📣 📢 🖋
James Robinson
💻 🖋 📖 🐛 🤔 🔍 📋 🚇 📆 📣 💬 👀 🛡️ ⚠️ 📢
Jim Madge
💻 📖 🐛 🤔 🔍 📋 🚇 📆 📣 💬 👀 🛡️ ⚠️ 📢
Josh Everett
🐛
Jules Manser
📖 🤔 🐛 🖋
Kevin Xu
📖 🤔 🛡️
Kirstie Whitaker
🖋 📖 🐛 🤔 🔍 📋 📆 📣 📢 📓
Martin O'Reilly
💻 🖋 📖 🐛 🤔 🔍 📋 🚇 📆 📣 💬 👀 🛡️ ⚠️ 📢
Matt Craddock
💻 📖 🐛 🤔 🔍 📋 📣 💬 👀 🛡️ ⚠️
Matt Westby
🐛
Miguel Morin
💻 📖 🤔 ⚠️
Oliver Forrest
📖 🤔 📆 📣 🖋
Oscar T Giles
💻 📖 🤔
Rachel Winstanley
📖 🤔 📆 🛡️
Radka Jersakova
🖋
Rob Clarke
🤔 🐛 💻 📖 🖋
Sebastian Vollmer
📖 🐛 🤔 🖋
Steven Carlysle-Davies
💻 🖋 🤔
Tim Hobson
💻 🐛 📖 🤔
Tom Doel
💻 📖 🐛 🤔 🖋
Tomas Lazauskas
💻 📖 🐛 🤔
Warwick Wood
💻 🤔
## 🍰 Releases
If you're new to the project, why not check out our [latest release](https://github.com/alan-turing-institute/data-safe-haven/releases/latest)?
You can also browse [all our releases](https://github.com/alan-turing-institute/data-safe-haven/releases).
Follow the link from any release to view and clone this repository as at that release.
Read our [versioning scheme](VERSIONING.md) for how we number and label releases, as well as details of releases that have been used in production and releases that have undergone formal security evaluation.
When making a new release, open an issue on GitHub and choose the `Release checklist` template, which can be used to track the completion of security checks for the release.
## 📬 Vulnerability disclosure
We value those who take the time and effort to report security vulnerabilities.
If you believe you have found a security vulnerability, please report it as outlined in our [Security and vulnerability disclosure policy](SECURITY.md).
## 🙇 Acknowledgements
We are grateful for the following support for this project:
- The Alan Turing Institute's core and additional EPSRC funding ([EP/N510129/1](https://gtr.ukri.org/projects?ref=EP%2FN510129%2F1), [EP/W001381/1](https://gtr.ukri.org/projects?ref=EP%2FW001381%2F1), [EP/W037211/1](https://gtr.ukri.org/projects?ref=EP%2FW037211%2F1), [EP/X03870X/1](https://gtr.ukri.org/projects?ref=EP%2FX03870X%2F1)).
- The UKRI Strategic Priorities Fund - AI for Science, Engineering, Health and Government programme ([EP/T001569/1](https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T001569/1)), particularly the "Tools, Practices and Systems" theme within that grant.
- Microsoft's generous [donation of Azure credits](https://www.microsoft.com/en-us/research/blog/microsoft-accelerates-data-science-at-the-alan-turing-institute-with-5m-in-cloud-computing-credits/) to the Alan Turing Institute.
## ⚠️ Disclaimer
The Alan Turing Institute and its group companies ("we", "us", the "Turing") make no representations, warranties, or guarantees, express or implied, regarding the information contained in this repository, including but not limited to information about the use or deployment of the Data Safe Haven and/or related materials.
We expressly exclude any implied warranties or representations whatsoever including without limitation regarding the use of the Data Safe Haven and related materials for any particular purpose.
The Data Safe Haven and related materials are provided on an 'as is' and 'as available' basis and you use them at your own cost and risk.
To the fullest extent permitted by law, the Turing excludes any liability arising from your use of or inability to use this repository, any of the information or materials contained on it, and/or the Data Safe Haven.
Deployments of the Data Safe Haven code and/or related materials depend on their specific implementation into different environments and we cannot account for all of these variations.
Safe use of any Data Safe Haven code or materials also relies upon individuals' and their organisations' good and responsible data handling processes and protocols and we make no representations and give no guarantees regarding the safety, security or suitability of any instance(s) of the deployment of the Data Safe Haven.
The Turing assumes no responsibility for updating any of the content in this repository; however, the underlying code and related materials may change from time to time with updates and it is the user's responsibility to keep abreast of these updates.