Organising research projects with git

In this post I list some of the standards and conventions I have developed over the course of my PhD to organise research project data. I use git to version control the relevant files and host them on Github.

Project naming convention

I name my research projects uniformly across all applications: file system, task management, Github, etc. I use the naming convention of <my-last-name><project-start-year><keyword>.

Project directory structure

My research projects have the following directory structure. Here is an example from a prior project I worked on:

~/phd/shome2022qualitative/
├── bin
├── data
├── docs
├── report
├── src
└── vendor
    ├── biswas2021fair
    └── zhang2021ignorance

Typically, research projects have several scripts for the data collection, data pre-processing, training ML models and running experiments. Put these scripts in the bin/ directory. If you have a more mature code base, you can organise your files in the src/ directory. This way your scripts in bin/ are still able to import modules or helper functions from src/.

Put all datasets for the project in the data/ directory. I typically put existing datasets (such as benchmarks introduced in prior papers) and the data created during the course of the project in separate folders within the data/ directory.

If you have a simple static website consisting of html and css pages, put them in the docs/ directory. Then you can use Github Pages to serve your website.

Put all your latex files, images and additional resources such as *.cls and *.bst files in the report/ directory. You may write several papers that originate from the same core project idea. Name the latex files using the <conference-name><year>.tex template. This prevents the need for duplicating all the accompanying files for each submission. Use version control to track the progress of your papers. For instance, use git tags to mark the major drafts and final submission. This makes it easy to retrieve prior versions of the paper if required.

If replication packages from prior papers are available on git, use git submodules and put them in the vendor/ directory. If they are hosted on other platforms such as Zenodo or Figshare, check in the source code files you need as reference. Use folders within vendor/ to organise replication packages from multiple papers.

Recommendations for .gitignore patterns

Github has an excellent repository of .gitignore patterns for various filetypes. Consider importing them into your own global .gitignore file (for instance, Latex and Python). At the project level, do not check in the pdf version of your papers since these are typically high churn files and git cannot produce meaningful diffs for binary files. Instead use the latexmk command to generate the pdf. You can also consider putting the command in a Makefile to reduce keystrokes.

latexmk -pdf -outdir=report report/<your-paper>.pdf

If you use Overleaf, connect your document to the Github project so that everything remains in sync.

Recommendations for git commit messages

Follow the general best practices for writing good git commit messages. I use the following template which was recommended by Tim Pope. You can also paste the following snippet into ~/.config/git/message. Then the text is automatically displayed in your text editor, whenever you write a commit message. See the git configuration documentation for more details.

# 50-character subject line
#
# 72-character wrapped longer description. This should answer:
#
# * Why was this change necessary?
# * How does it address the problem?
# * Are there any side effects?
#
# Include a link to the ticket, if any.

Additionally for the subject line

For instance, say you want to commit a first draft of your paper. Use a subject line as follows:

feat(report): init icse24 paper draft # <1>

Where feat is an abbreviation for “feature”. The braces specify the folder within which the changes were made, and the title provides a quick description of the change.

In contrast, say you refactor the data processing pipeline script. The subject line could be as follows:

refac(bin): remove magic numbers in data-process.sh

This makes it very easy to track down prior commits that introduced changes in the paper versus in the code. For instance, you can target all refactoring commits within the report/ directory using the following git grep command:

git log --grep 'refac.*report.'