Analyze & Collaborate – LMU Open Science Center

Create self-contained project folder. Include data, code, documentation, and outputs in a single structured environment, ensuring the project remains understandable, reproducible, and portable across systems and collaborators. If you use the free and open source software RStudio to manage your R project, your project directory (or folder) should contain a .Rproj file (see R tutorial). Use relative paths (i.e. “./subfolder”, where . represents the root of your .Rproj directory) or the library here, so the project stays portable to another environment
Use a standard folder structure. Your code repository should include a standard folder structure that make sense for your type of research, ideally shared amongst your team members. You can for instance use the OSC research project template.
Stop clicking, start coding. Automatize all possible steps, including data acquisition (see Data Collection), data processing and transformation, data analyses, data visualization, and results reporting (see Reproducible Reporting)
Structure, comment, and standardize your scripts. R scripts themselves should follow current standards to increase their readability(see Readable Code Lecture). Use meaningful names for variables, functions, and scripts. Add comments to your code explaining why you made a decision, and define your own function rather than copy and pasting pieces of code which makes it hard to maintain error-free.

Version control tracks changes to files over time. You can see what changed, when, and why. You can revert to previous versions. Collaborators can work without overwriting each other.

Important

Difference between Git, GitHub and GitLab

Git is a version control system that tracks changes in text files (e.g. CSV, plain text, R, Python). The Git software and your git repositories should be, respectively, installed and located in your local environment (i.e. on your computer, not on a drive, see Git tutorial).
GitHub is the most popular, but proprietary and US-based cloud-based platform for software development with Git, providing collaboration features like pull requests and issues. You should not have any sensitive information on GitHub even in a private repository.
LRZ GitLab is a cloud-based hosting platform that works exactly the same as GitHub but is free and open source and is installed on the LRZ servers for LMU Munich and can therefore be considered secure when the repository is private.

While your LRZ GitLab account is associated with your LMU Munich affiliation, your GitHub account can be associated with your private email, be included in your CV, and be used for public sharing of your data and code (see 3. Analyze & Collaborate).

In a version controlled workflow, you back up your local git repositories on either GitHub or LRZ GitLab through a secure SSH connection (see GitHub tutorial) and share access to your repositories with your collaborators through the cloud-based platform GitHub or LRZ GitLab.

Manage your computational environment by explicitly recording the software, package versions, and dependencies required for your analyses, ensuring results can be reproduced across systems and over time. Tools such as packages managers (e.g. Renv for R pacakges, Conda for Python packages) or broader containers (e.g. Docker or Binder) help stabilize workflows and prevent inconsistencies caused by packages or software updates.

For a R project repository:

Activate Renv to keep track of all packages versions (see renv tutorial). This way, you or someone else can reproduce your results on another computer or at a later time using the same R packages versions.

Before 4. Preserve and share:

Record your dependencies in your README file for possible reconstruction with repo2docker or binder see Code Publishing tutorial

readme from code publishing? a bit too intense for this stage tho but something about internal, work in progress read me

Analysis & Collaboration Checklist