Canadians Land on Jupyter

The proliferation of mobile devices, social networks and sensor networks, the massive data streams they generate, and increasing computational power generate research challenges and provoke widespread interest in mathematical sciences expertise and insight. Democratizing access to this expertise and insight catalyzes meaningful change. Higher education institutions are launching interdisciplinary programs in digital humanities, data science, scientific computation, mathematical modeling, bioinformatics and epigentics to address these challenges. To achieve success, these programs require easy access to state-of-the-art computing environments to support research, teaching and training activities.

The Pacific Institute for the Mathematical Sciences (PIMS), in partnership with Compute Canada and Cybera, launched a cloud-hosted scientific computing and data science platform for Canada. The service,, delivers Jupyter to faculty, staff and students at Canada’s universities using single-sign-on (SSO) via their university user account. By eliminating the requirement to install customized software on personal computers, makes it easier for research teams to collaborate using the right tools for their investigations. The platform delivers an interactive coding environment for literate programming in Python 2, Python 3, R (and sometimes Julia, Octav, Sage and other languages).


The data8 program at Berkeley, the open source quantitative economics course, and computational fluid dynamics course are inspirational examples showcasing the potential for Jupyter. PIMS is leveraging and other tools to develop expertise in scientific computing, data science, machine intelligence, optimization, etc.

Jupyter service is available today at several universites (UBC, SFU, UofT, Waterloo, Queen’s, Victoria, Saskatchewan, Manitoba, Calgary, Lethbridge). A few hubs have been deployed that can be accessed using other identity authentication providers (Google OAuth; GitHub; GitHub Enterprise). Colleges, universities, and other prospective partners can request Jupyter service via by clicking here.

PIMS developed some support resources: e-book introduction; Discourse forum.

The platform has been used for seminars on Python and Git, machine learning with SciKit Learn, neural networks and deep learning, undergraduate courses on mathematical computing, computer science, and statistics, and graduate courses on mathematical modeling for industry, seismic inverse problems, and computational finance.

Academy-industry partnerships are forming to investigate data science challenges arising in business through a workshop built atop

The platform democratizes access to digital research infrastructure. PIMS and our partners advance Canada’s research capacity by connecting human talent to curated tools from the mathematical sciences, diverse data sources, excellent documentation and training programs.