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Open Science Framework

Platform for open and reproducible research project management

Open Science & Data Sharing Intermediate Recommended Tool
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Quick Info
  • Category: Open Science & Data Sharing
  • Level: Intermediate
  • Type: Recommended Tool

Why We Recommend Open Science Framework

OSF provides a comprehensive platform for managing research projects openly. It supports preregistration, data sharing, and connects with many other tools (GitHub, figshare, Dropbox). It's designed specifically for research workflows and promotes transparency.

Common Use Cases

  • Preregister studies before data collection
  • Share research data and materials openly
  • Collaborate on research projects
  • Create DOIs for datasets and preprints

Getting Started

The Open Science Framework (OSF) is a free, open-source platform for managing research projects. It supports the entire research lifecycle from project planning through publication, emphasizing openness and reproducibility.

Why OSF?

  • Free & Open: Completely free for researchers worldwide
  • Integrated Workflow: Connects with GitHub, Dropbox, Google Drive, and more
  • Permanent Storage: Long-term preservation of research materials
  • Preregistration: Register study plans before data collection
  • DOIs: Create citable, permanent identifiers for your work

Key Features

Project Management

  • Organize research materials in hierarchical projects
  • Add collaborators with granular permissions
  • Track changes and maintain version history
  • Add wiki pages for documentation

Open Sharing

  • Make projects public or keep them private
  • Generate DOIs for permanent citation
  • Set embargo periods for timed release
  • License your work appropriately

Integrations

  • Connect GitHub repositories
  • Link cloud storage (Google Drive, Dropbox, Sciebo)
  • Use add-ons for specialized tools
  • Export to data repositories

Getting Started

  1. Create a free account at osf.io
  2. Create a new project for your research
  3. Add components for different parts (data, code, materials)
  4. Connect external services (GitHub, etc.)
  5. Share with collaborators or make public

Use Cases

  • Preregistration: Document your hypotheses and analysis plan before collecting data
  • Data Sharing: Make datasets available with permanent DOIs
  • Supplementary Materials: Host materials that don’t fit in paper supplements
  • Collaboration: Central hub for multi-institution projects

Tips

  • Use clear, descriptive names for projects and components
  • Add detailed README files to explain your materials
  • Use tags to make projects discoverable
  • Consider making projects public after publication
  • Link related projects together

Resources

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