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Data Science for Biomedical Scientists: Managing Open and Reproducible Computational Projects

All Contributors

Thanks for contributing to The Carpentries Incubator! This repository is part of the Data Science for Biomedical Scientists: The Turing/Crick partnership project. This project will facilitate the development of training resources on data science practices for senior researchers, group leaders, late PhD/Postdocs and mid- to late-career biomedical scientists. Materials developed through this project will enable (1) a foundational understanding of AI and data science in the context of biosciences and (2) recommendations for managing (as well as supervising and facilitating) open and reproducible research for the wider biology community.

This is one of the two masterclasses being developed under Data Science for Biomedical Scientists: The Turing/Crick partnership project. For the first masterclass, please visit: https://github.com/carpentries-incubator/data-science-ai-senior-researchers.

For details about the project and track management related information, please the Project Management Repository.

Developers and Maintainers

  • Malvika Sharan
  • Julien Colomb

Previous developers

  • Lydia France was allocated as a developer on this project for six months in 0.5 FTE capacity.
  • Federico Nanni provided supervision for Lydia and contributed to the project planning

External Reviewer: Jo Havemann, Access 2 Perspective

The Carpentries Incubator Programme

This repository provides a blank starting point for lessons to be developed here.

A member of the Carpentries Curriculum Team will work with you to get your lesson listed on the Community Developed Lessons page and make sure you have everything you need to begin developing your new lesson.

A member of the Carpentries Curriculum Team will work with you to get your lesson listed on the Community Developed Lessons page and make sure you have everything you need to begin developing your new lesson.

What to do next

Contributing

We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way.

We'd like to ask you to familiarize yourself with our Contribution Guide and have a look at the [more detailed guidelines][workbench] on proper formatting, ways to render the lesson locally, and even how to write new episodes. Note that we are using the new workbench templates and tooling. Rendering of the lessons is now based on R, via sandpaper::serve() while the package is not (yet) on CRAN.

Please see the current list of [issues][FIXME] for ideas for contributing to this repository. For making your contribution, we use the GitHub flow, which is nicely explained in the chapter Contributing to a Project in Pro Git by Scott Chacon. Look for the tag good_first_issue. This indicates that the maintainers will welcome a pull request fixing this issue.

Citation

This lesson will be realeased on Zenodo for DOI (digital object identifier). Meanwhile, please cite this repository as: Data Science for Biomedical Scientists: Managing Open and Reproducible Computational Projects, 2022, https://github.com/carpentries-incubator/managing-computational-projects

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Malvika Sharan
Malvika Sharan

🖋 👀 📖 🔍 🤔 🧑‍🏫 📆
Lydia France
Lydia France

🖋 🤔 💡
Esther Plomp
Esther Plomp

🖋 👀
Yvan Le Bras
Yvan Le Bras

🐛
Federico Nanni
Federico Nanni

🧑‍🏫 📆 🤔
Toby Hodges
Toby Hodges

🚇 💬
Lisanna Paladin
Lisanna Paladin

🤔 💡
JAFSIA Elisee
JAFSIA Elisee

🤔 🖋
Julien Colomb
Julien Colomb

🤔 👀 🖋
Malgorzata Lagisz
Malgorzata Lagisz

🤔 👀 🖋
Sara Villa
Sara Villa

🤔 👀 🖋
Sara
Sara

🤔 🖋
Jo Havemann
Jo Havemann

🖋

This project follows the all-contributors specification. Contributions of any kind welcome!