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Webinar: Jupyter as a Gateway for Scientific Collaboration and Education

July 20, 2017

Jupyter as a Gateway for Scientific Collaboration and Education
Presented by Carol Willing, Cal Poly SLO and Jupyter Steering Council

Project Jupyter, evolved from the IPython environment, provides a platform for interactive computing that is widely used today in research, education, journalism and industry. The core premise of the Jupyter architecture is to design tools around the experience of interactive computing, building an environment, protocol, file format and libraries optimized for the computational process when there is a human in the loop, in a live iteration with ideas and data assisted by the computer.

The Jupyter Notebook, a system that allows users to compose rich documents that combine narrative text and mathematics together with live code and the output of computations in any format compatible with a web browser (plots, animations, audio, video, etc.), provides a foundation for scientific collaboration. The next generation of the Jupyter web interface, JupyterLab, will combine in a single user interface not only the notebook, but multiple other tools to access Jupyter services and remote computational resources and data.  A flexible and responsive UI allows the user to mix Notebooks, terminals, text editors, graphical consoles and more, presenting in a single, unified environment the tools needed to work with a remote environment.  Furthermore, the entire design is extensible and based on plugins that interoperate via open APIs, making it possible to design new plugins tailored to specific types of data or user needs.

JupyterHub enables Jupyter Notebook and JupyterLab to be used by groups of users for research collaboration and education. We believe JupyterHub provides a foundation on which to build modern scientific gateways that support a wide range of user scenarios, from interactive data exploration in high-level languages like Python, Julia or R, to the education of researchers and students whose work relies on traditional HPC resources.

View the slides (Slideshare)

View the slides (Speaker Deck)

There's also a repo with the talk and a file with links

Watch on YouTube


Questions asked during the webinar (and some answers posted in chat)

If you have further questions, the best way to reach Carol is on Gitter or the Jupyter mailing list.

Q: I understand Jupyter Notebook isn't just for python, but can you use other languages? Is perl one of those languages? 
A: Yes, here is a list of supported languages:

Q: Is there a list for people exploring Jupyter in education. I am going to a hackathon on the subject, but I know there have been others. Is everything on GitHub or is the a better way to find out who is doing what?
A: Here are the mailing lists Carol mentioned:  

Project Jupyter:!forum/jupyter
Teaching with Jupyter:!forum/jupyter-education  
Jupyter in HPC:!forum/jupyter-hpc

Q: How is the Jupyter ecosystem thinking about security, as code is executable on users web browser?
A: Related to security: and dated, but also:

Q: Jupyter Notebooks great for educational purposes; can you give an example or two on research/science project using Jupyter Notebook?
A: Check out nbviewer and Jupyter's gallery of interesting notebooks.


Here's the link to the JupyterLab + Real Time Collaboration presentation Carol mentioned:

Many thanks to Johnathan Rush for providing many links on the fly during the webinar!