Best Practice for Reproducible Computational Research (In-person)

Audience Level: Intermediate

This session is ideal for participants who have a foundational understanding and are looking to expand their skills. The session is also perfect for researchers, data scientists, and anyone involved in computational projects who wants to improve their practices and contribute to more reliable science. You should have a good understanding of the basics of Python, at least as far as taught in the Introduction to Python 1 course.

Session Information:

Are you looking to enhance the reproducibility of your computational research? Join us for an engaging session where we’ll explore practical strategies and tools to ensure your research is robust, transparent, and repeatable.

We will cover:

• Starting a New Project: Learn how to structure your projects with clear organization, documentation, and reproducible workflows.
• Version Control with Git and GitHub: Learn how to track changes, collaborate effectively, and maintain a history of your project files.
• Environment Management Systems: Discover how to use tools like uv to create consistent computational environments.

The course materials are available at:

• TBD
• https://bristol-training.github.io/ukrn-intro-git-github/
• https://jatonline.github.io/managing-dependencies-using-uv-and-pixi/#/title-slide

Action required before the session:

This is a demonstration session, and there is no need to run anything on your laptop. However, if you wish to explore the tools independently on your own time, please refer to the installation instructions provided in the materials.

We are running an in-person and online JGI drop-in installation session on Friday 30th May from 11:30-12:45 - if you require any help in installing any software please attend this session.

Intended Learning Outcomes:

• Be familiar with the best practices on how to organize and document your projects
• Understand the importance of version control for research reproducibility
• Know how to use git and github
• Understand the importance of using reproducible environment management
• Know how to set up an environment with uv

Code of Conduct

Please look at our Code of Conduct for all online and in-person events organised by the JGI.

Bristol Data Week 2025

This event is part of Bristol Data Week 2025, organised by the Jean Golding Institute taking place from Monday 2nd June - Friday 6th June. Bristol Data Week is a leading platform for learning, discussion, and collaboration in data science and AI. It brings together researchers, industry experts, policymakers, and community groups to explore the latest advancements in data and technology, addressing real-world challenges and shaping the future of responsible AI.

This year, we will be running a week long series of events featuring:

• Expert-led workshops and training on cutting-edge data science and AI topics.
• Thought-provoking panel discussions with leading voices in the field.
• Opportunities to network with researchers, industry professionals, and policymakers.

Keep up to date with activities happening throughout Bristol Data Week on the Jean Golding Institute website, follow us on Bluesky, LinkedIn and tag us with #BristolDataWeek2025 or #BDW2025.

Please be aware that photography and recording of the sessions may be taking place. Please let us know if you would not like to be filmed by contacting jgi-admin@bristol.ac.uk