Collaboration on Open Data Science Projects

This lesson will be delivered as a part of WiDS Saudi Arabia. It is a collection of materials from the Molecular Sciences Software Institute (MolSSI), the software carpentries, the turing way, coderefinery and many others to introduce Open Science practices to data scientists with an emphasis on version control.

This lesson should provide data scientists with the knowledge and tools necessary to apply their new skill set immediately to collaborate with other scientists in any project. In the beginning, the workshop will introduce open science practices. It will then describe how to develop and collaborate on code with another scientist, keep code synchronised, and solve conflicts that arise from that collaboration, licencing their works and making it citable.

None of these materials was prepared by the repository owner. It’s a collection of lessons taken directly without any modification from these authors. This lesson is under continual development, please report issues to the workshop repository. If you see a subject you would like to contribute to, submit a pull request!

Schedule

Setup Download files required for the lesson
00:00 1. The reproducibility crisis and open science What is the reproducility crisi and how can be solved?
00:25 2. Become a champion of open (data) science How data scientist can apply open science practices in their work?
01:55 3. Intro to Version Control with Git How do I use git to keep a record of my project?
02:30 4. Using GitHub How do I use git and GitHub?
03:05 5. Code Collaboration using GitHub How can others contribute to my project on GitHub?
How can I contribute to the projects of others?
03:40 6. Licensing and citation What licensing information should I include with my work?
How can I enable others to cite my work?
03:50 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.