I’m new to using GitHub for academic work. I want to set up a repository for my research paper that I hope to publish. But I’m not sure how to begin. There’s not much expertise on this at my workplace, so I can’t get help there.
Can anyone give me some tips on what to consider when starting this project? I plan to include four scripts: one for preprocessing, one for the main analysis, another for additional analysis, and one for sensitivity analysis.
What’s the best way to organize these scripts in the repo? Should I add a README file? Are there any best practices for academic papers on GitHub? Any advice would be really helpful!
Creating a GitHub repository for your research paper is an excellent idea. Start by initializing a new repo and setting up a clear directory structure. I recommend folders like ‘scripts’, ‘data’, and ‘docs’. Place your four scripts in the ‘scripts’ folder, naming them clearly (e.g., ‘01_preprocessing.py’).
A README.md file is essential. Include a project overview, instructions for running scripts, and any dependencies. Consider adding a ‘requirements.txt’ file for easy environment setup.
For academic papers, it’s crucial to document your methodology clearly. You might want to include a ‘methods’ folder with detailed explanations of your analyses.
Remember to use Git effectively. Commit frequently with meaningful messages. This helps track your progress and allows you to revert changes if needed.
Lastly, consider the visibility of your repo. If you’re worried about being scooped, you can keep it private until publication.
As someone who’s been using GitHub for research projects, I can share some insights. First, definitely create a README file. It’s crucial for explaining your project, data sources, and how to run your scripts.
For organization, I’d suggest creating separate folders for your scripts, data (if shareable), and results. Name your scripts descriptively, like ‘01_preprocessing.R’, ‘02_main_analysis.R’, etc. This helps with workflow clarity.
Consider adding a ‘requirements.txt’ file listing necessary packages. It’s also good practice to include a license file, specifying how others can use your code.
For version control, commit changes regularly with clear messages. This helps track your progress and revert if needed.
Lastly, be mindful of data privacy. Don’t upload sensitive or copyrighted material. Use .gitignore to exclude files you don’t want public.
Remember, the goal is reproducibility. Make it easy for others (and future you) to understand and run your analysis.
hey grace, github’s great for research! start by makin a new repo. put ur scripts in a ‘scripts’ folder, name em like ‘01_preprocess.R’. def add a README - explain wat ur doin and how to run stuff.
for academic stuff, maybe add a ‘methods’ folder to explain ur analysis. commit often with clear messages. oh and watch out for sensitive data - use .gitignore for that.
good luck with ur paper!