A registry of tutorials, workshop material, videos and other educational resources to help you learn more about DataLad.
- 🔗 Quick links
- 🚀 Entry-level
- 🤓 In-depth
- 🎤 Talks
- 👩🎓 Contribute
| Title | Content | Binder |
|---|---|---|
| An introduction to DataLad at the MPI Berlin | 💻 | - |
| DataLad tutorial at the MPI Leipzig | 💻 | - |
| An introduction to DataLad for the ABCD ReproNim course week 8b | 💻 | - |
| An introduction to DataLad for Yale | 💻 | - |
| Explore DataLad - an intro | 💻 |  |
| Exploring the StudyForrest dataset with DataLad | 💻 | |
| A short guide to accessing OpenNeuro datasets via DataLad | 💻 | - |
| Title | Presenter | Video | Content | Binder |
|---|---|---|---|---|
| OHBM Brainhack TrainTrack: DataLad | Adina Wagner | 🎥 | 💻 | |
| Title | Presenter | Video | Content |
|---|
| Research Data Management with DataLad - An online course - 2022 | - | - | 💻 | | A hands-on introduction to DataLad | Adina Wagner | 🎥 | - | | An introduction to DataLad with a focus on machine learning | Adina Wagner | 🎥 | 💻 | Workshop on Research Data Management with DataLad | Adina Wagner & Lennart Wittkuhn | 🎥 session 1 | - | | Workshop on Research Data Management with DataLad | Adina Wagner & Lennart Wittkuhn | 🎥 session 2 | - | | Workshop on Research Data Management with DataLad | Adina Wagner & Lennart Wittkuhn | 🎥 session 3 | - | | Workshop on Research Data Management with DataLad | Adina Wagner & Lennart Wittkuhn | 🎥 session 4 | - |
| Title | Presenter | Video |
|---|---|---|
| DataLad - Decentralized Distribution and Sharing of Scientific Datasets | Yaroslav Halchenko | 🎥 |
| DataLad vs Git/Git-annex for modular data management | Michael Hanke | 🎥 |
| How to introduce data management technology without sinking the ship? | Michael Hanke | 🎥 |
| Perpetual decentralized management of digital objects for collaborative open science | Michael Hanke | 🎥 |
| DataLad - Decentralized Management of Digital Objects for Open Science | Adina Wagner | 🎥 |
| Data versioning and transformation with DataLad | Adina Wagner | 🎥 |
Contributions to this repository are very welcome. They can be in the form of feedback, creating issues, or making pull requests to add/update content.
In order to create new notebooks for this repository, please clone it first and then install the development requirements (ideally in a new virtual environment):
git clone https://github.com/datalad/tutorials.git
cd tutorials
pip install -r requirements-devel.txt
python -m bash_kernel.install
New notebooks can then be created using either the standard IPython kernel or the bash kernel. An http server is also available to be launched from within the Jupyter Notebook environment.