593 private links
You do not need to master every aspect of git to make use of it in your daily work.
Even a little bit of git will take you a long way towards best practice with regards to reproducibility!
Enjoy these videos
- https://youtu.be/s3JldKoA0zw (science setting, also awesome soundtrack!)
- https://www.youtube.com/watch?v=CvbLVVRzJF8 (business setting)
Git introductions or tutorials
- The missing semester of your CS education, online classes on the command-line, Git, the shell and more from MIT
- Git Magic, by Ben Lynn
- Become a Git pro in just one blog. A thorough guide to Git architecture and command line interface, by Uday Hiwarale
- How To Make Life Easier When Using Git, by Shane Hudson
- Confusing git terminology, Julia Evans, 2023-11-01
- How Git Works!, Julia Evans, 2024-06-03
- Inside .git, Julia Evans, 2024
- Git en välskriven guide på svenska från IT-institutionen vid Uppsala universitet
Opinions or comments
- How to be a 'good' git evangelist?, by Sunniva Indrehus, 2021-09-02
- Git is my buddy: Effective Git as a solo developer, Mikkel Paulson, 2021. Via https://www.eamoncaddigan.net/posts/git-links
- Nobody cares about your Git history, Dan Kelch, 2024
- https://matklad.github.io/2023/12/31/git-things.html
ReproHack is a sandbox environment for practicing research reproducibility-
Why have I not heard about this before!
I should consider submitting my own paper to their general list of papers.
The website is a collaboration between two Dutch data science centers.
Should in my opinion also mention Gitea or Codeberg under suggested version control repositories, but otherwise good advice all around!
Under the title Data in Motion this track focuses on the deployment of data in research and the versatility of the domain that concentrates on this way of doing science. A panel, presentations and small pitches, illustrated by video or demo's, will sketch the fruits of escience and data science, and thus demonstrate the need for an RDA in support of research. Also the formation of a European Platform for e-science and data research centers will be highlighted during this session.
Video 1h 20 min. Presented by Patrick Aerts and Paul Groth.
Ok, so this video is a few years old, but it does not have anywhere near the views it deserves. It's never too late to do reproducible science! (Video 1m 44s)
Reproducible science not only reduce errors, but speeds up the process of re-running your analysis and auto-generate updated documents with the results.