I haven't used it but git seems like the wrong framework for managing experiments. Even programmers don't especially like git, forget about data scientists. You can't meaningfully version control the data; it's usually binary, and in an object store. The code already lives in a git repository. So what does that leave, the metadata around the experiment?
A relational database like Dolt seems like a better fit. You want to be able to query by experiment name, date, test results, and other metadata.
Let me know if I'm doing it wrong! What's your use case?
> You can't meaningfully version control the data; it's usually binary, and in an object store. The code already lives in a git repository. So what does that leave, the metadata around the experiment?
Out of the box you can't. We're taking a different approach at work (XetHub). GitHub sees pointer files but we embed rendered views and diffs (supporting more file types incrementally) using a Github app from our service.
DVC stores metadata files in your git repo and the actual files somewhere else (local, S3, etc). It handles swapping around the files so they match what you've checked out. It does a lot more but that's the relevant part for your main question.
A relational database like Dolt seems like a better fit. You want to be able to query by experiment name, date, test results, and other metadata.
Let me know if I'm doing it wrong! What's your use case?