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Contributing to the DOME Registry

Thank you for your interest in contributing to the DOME Registry. This project, hosted by the UNIPD Biocomputing Lab, aims to provide a curated, FAIR-compliant registry for machine learning methods in the life sciences.

We primarily use a GitHub-based workflow. Contributions are made via Pull Requests (PRs) which are then reviewed and merged by the UNIPD lead developer. For general enquiries or coordination before starting a large contribution, you can reach the team at contact@dome-ml.org.

On this page

How to Contribute

Reporting Issues or Suggesting Improvements

If you find a bug, want to suggest a new feature, or have an idea for improving the registry structure:

  1. Check existing issues: See if someone has already reported the same item or made a similar suggestion.
  2. Create a new issue: If not, please create a new issue (ensure you use the correct repository link).
    • Provide a clear title and description.
    • For bug reports, include steps to reproduce the issue.
    • For complex suggestions, feel free to email contact@dome-ml.org to discuss the roadmap.

Submitting Changes via Pull Requests

This is the preferred way to modify the registry code, documentation, or static resources.

  1. Fork the Repository: Create your own copy of the DOME Registry repository on GitHub.
  2. Create a Local Branch: In your forked repository, create a new branch for your changes. 
    git checkout -b feature/add-new-integration
  3. Make Your Changes:
    • Add your modifications or corrections to the relevant files.
    • Ensure each change is clear, concise, and follows the existing style.
  4. Commit Your Changes: 
    git add .
git commit -m "feat: add EPMC integration description"
    (Use clear, descriptive commit messages starting with a prefix like feat:, fix:, or docs:).
  5. Push to Your Fork: 
    git push origin feature/add-new-integration
  6. Open a Pull Request:
    • Navigate to the original DOME Registry repository on GitHub.
    • Click the "New Pull Request" button.
    • Provide a clear title and a brief description of your changes.
    • Submit the Pull Request for review.

What to Contribute

We welcome contributions that add or improve:

  • Registry Metadata: Corrections to existing method descriptions or improvements to metadata schemas.
  • Documentation: Improvements to the README, API documentation, or user tutorials.
  • Bug Fixes: Resolving issues in the registry front-end or back-end integration scripts.
  • Integration Standards: Updates to Bioschemas markup or other FAIR-related annotations.

What Not to Contribute

  • Off-topic content that does not align with the goals of promoting FAIR machine learning methods.
  • Proprietary code or resources that do not permit open-access sharing.
  • Changes to core infrastructure without prior discussion via an Issue or email.
  • Promotional material or advertisements.

Contribution Licensing

By contributing to this project, you agree that your contributions will be licensed under the project's CC-BY-4.0 license. All contributed content must respect the copyrights and intellectual property of others.

Review Process

The UNIPD lead developer will review all Pull Requests.

  • We aim to provide feedback on contributions promptly.
  • Requests for changes or clarifications may be made via comments on the Pull Request.
  • Once the PR is approved and passes any automated checks, the UNIPD lead developer will merge it into the main branch.

For any questions regarding the review process or if you need to report an urgent issue, please contact contact@dome-ml.org.

We appreciate your effort in helping the UNIPD Biocomputing Lab build a robust and FAIR ecosystem for machine learning methods.