Webinar: Jupyter as a Gateway for Scientific Collaboration and Education

Key Info
URL - the landing page for the learning resource: 
https://sciencegateways.org/-/webinar-jupyter-as-a-gateway-for-scientific-collab…
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

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.

The presenter discusses the benefits and applications of Jupyter Notebooks.

Scroll to the bottom of the page to view the webinar. Presentation slides are also available on the same page. 

Authoring Person(s) Name: 
Carol Willing
Authoring Organization(s) Name: 
Cal Poly, San Luis Obispo
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Collaborative workflow
Cyberinfrastructure to enable FAIR data principles
Data access methods
Interoperable data - FAIR Data Principle
Re-usable data - FAIR Data Principle
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Education: Science and Mathematics Education
Physical Sciences and Mathematics
Published / Broadcast: 
Thursday, July 20, 2017
Publisher - organization credited with publishing or broadcasting the learning resource: 
Science Gateway Community Institute (SGCI)
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Event - time-based happening that is portrayed or covered by the learning resource, e.g., a webinar.
Contributor Organization(s): 
Name: 
Jupyter Steering Council
Type: 
Collaborator
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.
Target Audience - intended audience for which the learning resource was created: 
Research scientist
Software engineer
Early-career research scientist
Research faculty
Graduate student
Librarian
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
Up to 1 hour
Framework - A community-based organization plan or set of steps for education or training: 
FAIR Data Principles
Framework Node: FAIR: 
Interoperable
Re-usable