A well-articulated piece on why Git is a useful too for open, reproducible science (by Karthik Ram):
Reproducibility is the hallmark of good science. Maintaining a high degree of transparency in scientiﬁc reporting is essential not just for gaining trust and credibility within the scientiﬁc community but also for facilitating the development of new ideas. Sharing data and computer code associated with publications is becoming increasingly common, motivated partly in response to data deposition requirements from journals and mandates from funders. Despite this increase in transparency, it is still diﬃcult to reproduce or build upon the ﬁndings of most scientiﬁc publications without access to a more complete workﬂow.
Version control systems (VCS), which have long been used to maintain code repositories in the software industry, are now ﬁnding new applications in science. One such open source VCS, Git, provides a lightweight yet robust framework that is ideal for managing the full suite of research outputs such as datasets, statistical code, ﬁgures, lab notes, and manuscripts. For individual researchers, Git provides a powerful way to track and compare versions, retrace errors, explore new approaches in a structured manner, while maintaining a full audit trail. For larger collaborative eﬀorts, Git and Git hosting services make it possible for everyone to work asynchronously and merge their contributions at any time, all the while maintaining a complete authorship trail. In this paper I provide an overview of Git along with use-cases that highlight how this tool can be leveraged to make science more reproducible and transparent, foster new collaborations, and support novel uses.