Matrix Institute for Applied Data Science – Cookie Hour Seminar, October 17

The UVic Matrix Institute for Applied Data Science is a new Faculty of Engineering initiative that brings together academia, industry and government to work on projects focused around applied data science. Many of our SENG faculty are involved in this work, as are members of various other departments on campus as well as local industry.

The Matrix Institute hosts monthly presentations related to current topics in applied data science. Check out the event list on their website.

You are invited to their next seminar on Wednesday, October 17, 2018 from 3pm to 4pm in ECS 660. Stay for tea and cookies after the presentation!

When Writing It Down is Not Enough: the Era of Computational Notebooks
Dr. Neil Ernst, Department of Computer Science, University of Victoria

Abstract: The lab book has always been an indispensable part of scientific inquiry. Although to date nearly all famous discoveries have been documented by hand, on paper, our digital data-centric age means future discoveries are almost certain to be captured digitally. Digital notebooks have produced a remarkable shift in how scientists work in the lab and the field. And yet these new media come with many unknowns and vulnerabilities. In this talk I will outline how notebooks have been used historically, illustrating the many strengths of the analog approach to capturing scientific inquiry. Then I will introduce digital notebooks like Jupyter and R Notebooks. After explaining and demonstrating their features, I will illustrate their strengths and weaknesses. I will outline some of the research my students and I are conducting into some of these challenges, including notebook provenance, notebook testing, and notebook usability.

Bio: Neil Ernst, PhD, is a tenure-track assistant professor at the University of Victoria. He is a world-leading researcher in software architecture and requirements. His research focuses on building next generation software systems. He leverages past experience consulting with large government stakeholders and empirical datasets on software development and analysis. Current projects include software composition, technical debt in scientific software, and engineering data science systems.