Is version control an electronic lab notebook?

Written by: C. Titus Brown

Primary Source: Living in an Ivory Basement

In my post on proselytizing version control, an underlying and implicit assumption was that version control was not fulfilling the function of a lab notebook. But I didn’t make that explicit. And then someone asked in the comments. So now I’m making it explicit.

tl; dr? Version control’s a really good idea, and should be used by everyone; but you can do science without using it, and I don’t think it’s the computational equivalent of a lab notebook.

It’s a good question: is version control an electronic lab notebook? Because if so, then it should be easy to convince practicing biologists that they should use version control for their computational work.

I’m not convinced it’s that easy to make that argument.

Having spent some reasonable part of my life in a lab, I have basic experience with a lab notebook. In my graduate lab, I used my notebook to write out what protocol I used to do a particular experiment; what animals I used, at what stages of development; and I pasted in the printouts from various machines detailing my results (e.g. DNA concentrations). It was an indispensable way to track my experimental conditions and results.

Now that I’m once again only doing computational work, I don’t really use a lab notebook at all. I don’t think I need to. Why not?

Lab notebooks seem to serve two purposes: first, they document provenance, the origin of ideas, data, and results; and second, they document protocol, the methods used to achieve a particular result. Provenance is primarily an intellectual issue — where did your ideas come from? how did you get to where you got? — while protocol is primarily about reproducibility: how did you reach the particular results?

In experimental science, it’s often very hard to re-run experiments. The lab notebook tracks the experiments and results and makes sure that when an experiment needs to be reproduced, it can be. One of the most publicized scientific misconduct cases in my memory, The Baltimore Affair, was largely about sloppy record keeping. More generally, this is why good lab notebook keeping is considered essential to academic wet lab practice.

For computational research, protocol tracking ensures reproducibility, which is rather important for all sorts of reasons. This is where scripting and version control have been critical to my lab (well, along with these being the only sane way to do software development). While version control is helpful, Sue Huse convinced me that it’s not absolutely necessary. A the end of the day, I don’t care how you got to your final analysis; I care that your final pipeline is reproducible. You don’t need version control for that.

But provenance? I see relatively little requirement for legal provenance tracking in my computational work: for IP concerns, first publication seems to matter a lot more than who had an idea, and I’m not trying to patent anything. Were I, I’m still not sure it would matter; it’s hard for me to imagine someone poring over my lab notebook (or version control system) to document the very first time we used a probabilistic de Bruijn graph, for example.

(I’m not a lawyer, and I’d welcome corrections or other perspectives.)

So I don’t see a strong requirement for version control in computational science, and, in fact, I know several people that I would consider to be quite good computational scientists who don’t use it at all. I hesitate to disbar these people doing good, reproducible computational work from the scientific establishment simply because they’re not using version control.

More, I worry that the analogy between version control and lab notebooks is a facile analogy that obscures a deeper divide between experimental and computational work. Experimental work is often slow, expensive, “hands” dependent, and context dependent, and hence hard to reproduce; most computational work requires a lot of development up front, but should be neither “hands”-y or context dependent, and should be relatively easy to reproduce. These differences should drive different methods of thinking about reproducibility.

And yes, you should still use version control. It’s simply good computational practice. But I don’t think it should be justified as the direct equivalent of lab notebooks; rather, it’s an example of good computational science hygiene, just like keeping a lab notebook is also an example of good experimental science hygiene.


p.s. An interesting question: is the challenge of strict reproducibility in experimental work one of the reasons why computational reproducibility has not been demanded in biology? If the reviewers have an experimental background, maybe they expect computational reproducibility to be tougher than it really is, so they let researchers get away with it?

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C. Titus Brown
C. Titus Brown is an assistant professor in the Department of Computer Science and Engineering and the Department of Microbiology and Molecular Genetics. He earned his PhD ('06) in developmental molecular biology from the California Institute of Technology. Brown is director of the laboratory for Genomics, Evolution, and Development (GED) at Michigan State University. He is a member of the Python Software Foundation and an active contributor to the open source software community. His research interests include computational biology, bioinformatics, open source software development, and software engineering.