6.2. Contributing to DataLad¶
DataLad is free and open source software. Everyone can contribute in various forms – feature requests, questions, artwork, tutorials, code patches, bug reports, … even follows, likes, or retweets on Twitter, boosts on Mastodon, or discussions in our matrix chatroom. We would be delighted to hear from you in any form.
The following resources could be helpful:
6.2.1. For the Handbook¶
Take a look at the section Contributing for more information.
6.2.2. For DataLad¶
Use it! Although it may sound nothing like a contribution, using DataLad is a fundamental contribution anyone can make. You can find further tutorials, materials, videos, and other resources in this handbook, and in a dedicated Tutorials repository. And if you like it, you can also tell your friends, system administrators, and colleagues about it, or convince your local IT department to install it on shared compute infrastructure.
Get in touch: We strive to improve the clarity of DataLad and its documentation. If you tried to implement DataLad in a specific way and the existing documentation didn’t make sense, or wasn’t clear enough or even confusing, please help us fix it. Let us know that the instructions could have been clearer, or that it didn’t cover your use case, or led you along the wrong path. And if you have suggestions for improvements, let’s incorporate them! Come chat with us about what you do on Matrix (a free, decentralized, and secure communication network), tag
dataladin an issue on Neurostars, or get in touch via GitHub.
Show your support: If you like DataLad you can show your support in various meaningful ways. You can “star” the project on GitHub. You can subscribe, like, or follow DataLad on social media: There is a Twitter Account and a Mastodon Account on which we regularly post updates, and a YouTube channel on which we post tutorials and talks. And if you write academic papers or blog posts, you can cite the paper about DataLad if DataLad assisted in your work.
Contribute on GitHub: A most valuable contribution is your time. We are interested and grateful for opinions, bug reports, feature requests, patches, larger code contributions, or simply a notice what you use DataLad for. Find the relevant repository, be that github.com/datalad/datalad (the main repository), github.com/datalad-datasets (many open datasets), or any DataLad extension, and open issues or pull requests. DataLad’s CONTRIBUTING file has tons of technical and social information to get you started with code contributions. But don’t be intimidated by the wealth of information you will find in there. We’ll be happy to help you at any stage. Also, you can take a look at technical docs (docs.datalad.org) and in particular the Design documents that shed light on the internal design principles of the software.
Write an extension! If you have unique use cases, you can write your own DataLad extension for it, that can provide any number of additional DataLad commands that are automatically included in DataLad’s command line and Python API. Our extension template is the best starting point. It contains an example command implementation, and will have test setup and packaging configurations in place already. If you want to, you can register your extension against DataLad’s extension registry at github.com/datalad/datalad-extensions – if your project is included, we can continuously check whether current versions of DataLad work with your extension.
Contribute to related projects As open source software, we proudly stand on the shoulders of giants. The DataLad project wouldn’t be possible without many other open source packages and projects. Helping them helps us, and you could do so in any of the ways described above, including documentation, tutorials, patches, support – if you have a passion for Haskell or C you could even head over to git-annex or Git themselves.
Thank you for your interest and support!