What are the most concretely useful, interesting, awesome or neat things about Project Jupyter?
Over here at the Lab for Data Intensive Biology, we're putting on a workshop on Project Jupyter notebooks (the notebook system formerly known as IPython Notebook). This will be a two-day hands-on workshop, Carpentry-style, with the goal of introducing students to the concept and practice of notebook-based data narratives. We also want to showcase the technology and ecosystem a bit.
This puts me in a bit of a bind, because while I am strong proponent of IPython Notebook for reproducibility and teaching, I don't have an awful lot of experience with anything beyond the default Python kernel and Notebook interface.
So my question to the blogosphere: what, beyond the basics, would you suggest demonstrating to people? Here is the menu from which I am planning to choose 5-6 topics and demos - suggestions and pointers welcome! (Note that I'm not looking for particular notebooks but rather demonstrations and concepts that show off the possibilities!)
- sharing and displaying notebooks via github;
- multiple language kernels (e.g. R in Jupyter Notebooks);
- plugin architecture and plugins (e.g. nbgrader; what else?)
- going from notebooks to publications;
- (maybe?) running within Docker: https://github.com/jupyter/docker-stacks/tree/master/datascience-notebook
Additional suggestions? Specific pointers?