Project Jupyter: From Computational Notebooks to Large Scale Data Science with Sensitive Data with Brian Granger
Project Jupyter is an open-source project that exists to develop software, open standards, and services for interactive and reproducible computing. The main application developed by the project is the Jupyter Notebook, a web-application that allows users to create documents that combine live code with narrative text, mathematical equations, and visualizations. Since its creation in 2011, the Jupyter Notebook has become a widely-used, open standard for developing, sharing, communicating, and reproducing computational work in scientific computing and data science.
In this talk I will give an overview of Project Jupyter and its open-source software and open standards for interactive and exploratory computing. Examples of its usage across a broad range of industries, disciplines and organizations will be used to illustrate the main ideas upon which Jupyter is founded. I will end by sketching our current work on JupyterLab, JupyterHub, and Binder and show how it is leading to 1) new challenges with large scale data science within complex organizations and 2) legal, ethical and technical questions regarding sensitive data.
Brian Granger is an Associate Professor of Physics and Data Science at Cal Poly State University in San Luis Obispo, CA. His research focuses on building open-source tools for interactive computing, data science, and data visualization. Brian is a leader of the IPython project, co-founder of Project Jupyter, co-founder of the Altair project for statistical visualization, and an active contributor to a number of other open-source projects focused on data science in Python. He is an advisory board member of NumFOCUS and a faculty fellow of the Cal Poly Center for Innovation and Entrepreneurship. Along with other leaders of Project Jupyter, he is a winner of the 2017 ACM Software System Award.