OSF-to-Binder

OSF-to-Binder is a tool for automatically building reproducible repositories from the source code of scientific publications. It analyzes the code, adds dependencies, builds a Binder-ready repository, and executes the code in the project. Detailed results of running the tool are available in the code-inspect-binder organization.

Project Structure

osf-to-binder/
├── pipeline/          # Analysis pipeline code
├── repos/             # Created binder-ready repositories
├── results/           # Code execution results
├── logs/              # Log files from analysis runs
├── metadata/          # Metadata and analysis configurations
├── downloads/         # Storage for downloaded osf files
├── pyproject.toml     # Project dependencies
└── uv.lock            # Locked dependency versions

Prerequisites

• uv python package manager
• Git LFS (https://git-lfs.com/)
• Docker

Installation

1. Install uv (if not already installed):

# On macOS with Homebrew
brew install uv

# On Linux/Windows, follow instructions at:
# https://docs.astral.sh/uv/getting-started/installation/

2. Clone the repository:

git clone https://github.com/Code-Inspect/osf-to-binder
cd osf-to-binder

Usage

1. Configure your analysis settings in the metadata directory
2. Run the analysis pipeline:

uv run pipeline/run.py <project_id>  # Process a single project

# OR

uv run pipeline/run.py metadata/project_ids.txt  # Process multiple projects from a file

The tool will:

• Download and unzip OSF project files
• Extract dependencies from R scripts using flowR
• Create a docker container using repo2docker
• Build and run Docker containers
• Set the working directory to the script’s folder before execution
• Execute R scripts in the container
• Log all operations and results

Optional: FlowR-Enabled Repositories

This version of the repository has the flowR Addin preinstalled. flowR allows visual design and execution of data analysis workflows within RStudio, supporting better reproducibility and modular analysis pipelines.

How to Enable FlowR

Use the --flowr flag during pipeline execution:

uv run pipeline/run.py <project_id> --flowr

# OR

uv run pipeline/run.py metadata/project_ids.txt --flowr

When enabled, the pipeline will:

• Create a modified version of the repository with a -f suffix (e.g., osf_<project_id>-f/)
• Installs the flowR addin automatically in interactive RStudio sessions
• Name Docker image and container as repo2docker-<project_id>-f
• Push the image to DockerHub under the same -f suffix

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Citation

If you use this repository or refer to this work, please cite:

@inproceedings{Saju2025Computational,
  title     = {Computational Reproducibility of R Code Supplements on {OSF}},
  author    = {Saju, Lorraine and Holtdirk, Tobias and Mangroliya, Meetkumar Pravinbhai and Bleier, Arnim},
  booktitle = {R2CASS 2025: Social Science Meets Web Data: Reproducible and Reusable Computational Approaches, Workshop Proceedings of the 19th International AAAI Conference on Web and Social Media},
  year      = {2025},
  doi       = {10.36190/2025.49},
  publisher = {Association for the Advancement of Artificial Intelligence}
}

This work was funded by the German Research Foundation (DFG) under project No. 504226141.