Cal Poly, UC Berkeley Receive $6 Million for Collaborative Computing

Cal Poly, UC Berkeley Receive $6 Million for Collaborative Computing

California Polytechnic State University and the University of California, Berkeley have announced a three-year, $6 million grant to further develop an open-source software package that makes data science more collaborative and interactive.

Awarded as part of a partnership involving the Leona M. and Harry B. Helmsley Charitable Trust, the Alfred P. Sloan Foundation, and the Gordon and Betty Moore Foundation, the grant will support efforts to give technical and non-technical users easier access to collaborative computing through a software package called Project Jupyter. Led by Fernando Perez of UC Berkeley and the Lawrence Berkeley National Laboratory and Brian Granger of Cal Poly, the project evolved from work on the IPython Notebook, a popular user interface developed by Perez and Granger that enables interactive computing across multiple programming languages. The project's main tool is the Jupyter Notebook, a web-based platform that enables users to integrate code, plots, text, data, and video in one document and share that document interactively. Enhancements will include the ability to reuse content, including visualizations such as charts and graphs, in a range of settings, from websites and blogs to mobile apps and interactive dashboards.

"Project Jupyter serves not only the academic and scientific communities but also a much broader constituency of data scientists in research, education, industry, and journalism," said Perez. "Given the importance of computing across modern society, we see uses of our tools that range from high school education in programming to the nation's supercomputing facilities and the leaders of the tech industry."

"Jupyter Notebook is a tool that embodies the current shift in science toward more reproducible research, which in turn enables more effective science," said Chris Mentzel, program director at the Moore Foundation. "It will enable data exploration, visualization, and analysis in a way that encourages sound science and speeds progress."