How can you document your research workflow with multiple collaborators?

1 Choose a common platform

The first step is to choose a common platform where you and your collaborators can store, share, and edit your data, code, and outputs. Ideally, the platform should allow version control, real-time collaboration, and easy access. Some examples of platforms that can support collaborative research workflows are GitHub, Google Drive, Dropbox, or RStudio Cloud. Depending on your preferences and needs, you can also use a combination of platforms, such as GitHub for code and Google Drive for data.

2 Establish a naming convention

The next step is to establish a clear and consistent naming convention for your files and folders. This will help you and your collaborators to find, organize, and update your files easily. A good naming convention should include relevant information, such as the project name, the date, the version, the author, and the file type. For example, you can name your data file as "project_data_2021_09_15.csv" and your code file as "project_analysis_v2_john.R". You should also avoid using spaces, special characters, or ambiguous terms in your file names.

3 Write a README file

A README file is a document that provides an overview of your project and explains how to run and reproduce your analysis. It should contain information such as the project title, the authors, the objectives, the data sources, the methods, the dependencies, the instructions, and the results. You can write your README file in plain text, markdown, or HTML format, and save it in the root folder of your project. You should also update your README file whenever you make significant changes to your workflow.