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Contribution Guidelines

How to contribute?

Thank you for taking the time to contribute to this project. 🎉

This project is being developed openly and invites contributions from anyone interested in reproducible data science who would like to get involved. You can suggest topics to include in this repository, report mistakes/bugs, create Pull Requests to fix an error, offer resources or help develop or review the training materials.

⭐️ You are acknowledged for all kinds of contributions

In this repository, we use the All Contributors Bot that helps us recognise all contributors, even when they don’t directly contribute to the repository. You can find all emoji/Type keywords representing the types of contribution.

To add a contributor, comment on Issue or Pull Request (where the contributor is involved) using this message for all-contributors: @all-contributors please add @<username> for <keyword in the Type column>

Whatever is your availability, there is a way to contribute to this GitHub repository.

👋 I’m busy, I only have 5 minute

Look through our currently open issues to troubleshoot an issue or participate in an ongoing discussion by commenting. You can also share this repository with someone who might be interested in getting involved.

⏳ I’ve got 15 minutes - tell me what I should do

You can read our README file to find details and the next milestones in the project. You can also read different issues in this repository and comment where you would like to be involved.

🎉 It’s my life’s mission to enable reproducibility in data science and research

Please share feedback on the contents proposed for setting up an online collaborative repository for data science and research. You are encouraged to review the material as we collaboratively develop it and get involved where you can. Please open a GitHub issue to suggest a new topic, contribute code, or let us know about errors/bugs.

🛠 I am ready to contribute

📫 Contact

For any organisation-related queries or concerns, you can directly reach out to Malvika Sharan by emailing malvika@we-are-ols.org.

♻️ License

This work is licensed under the MIT license (code) and Creative Commons Attribution 4.0 International license (for documentation).

You are free to share and adapt the material for any purpose, even commercially, as long as you provide attribution (give appropriate credit, provide a link to the license, and indicate if changes were made) in any reasonable manner, but not in any way that suggests the licensor endorses you or your use and with no additional restrictions.