Precision Convergence Webinar Series: December 2, 2021
Towards Sustainable Research Software
Presented by Dr. Daniel S. Katz
Humanity has a mix of overlapping goals that relate to science (and more broadly, wissenschaft). We seek new knowledge for its own purpose as well as for its potential solution to both detailed and general problems, situations, and crises. And we want to be able to verify (or disprove) such knowledge (reproducibility), then build on it (reuse), as simply and as cost-effectively as possible. This knowledge can be captured in text, images, data, software, etc. In this talk, I will focus on knowledge captured in research software, which can be both read, executed, and extended. However, software, unlike data, requires ongoing human activity to fix bugs and to adapt to frequent changes in the software and hardware environment on which it depends, as well as changing user needs. This required human activity leads to different models of software sustainability, including a mix of open source communities, industrial or government support, and commercialization, some of which are also tied to different distribution mechanisms, such as source code, executables, containers, and services. This leads to a number of overlapping challenges and corresponding efforts, including making re- search software FAIR (findable, accessible, interoperable, and reusable), publishable, and citable, as well as considering how to support the human effort needed to maintain and sustain the software, including incentives and career paths. This talk will highlight some recent activities in these areas, including FAIR for research software principles, software citation, the Journal of Open Source Software, and software career paths.
With a high-level panel of leaders in science, technology, on-the-ground action, investment, and policy including Co-Chairs Laurette Dubé and Shawn Brown
About the speaker
Daniel S. Katz is Chief Scientist at the National Center for Supercomputing Applications (NCSA), Research Associate Professor in Computer Science, Electrical and Computer Engineering, and the School of Information Sciences at the University of Illinois Urbana-Champaign. He is also a Better Scientific Software (BSSw) Fellow. He was previously a Senior Fellow in the Computation Institute at the University of Chicago and Argonne National Laboratory, a Program Director in the Division of Advanced Cyberinfrastructure at the National Science Foundation, Director for Cyberinfrastructure Development at the Center for Computation & Technology, Louisiana State University, Principal Member of the Information Systems and Computer Science Staff and Supervisor of the Parallel Applications Technologies group at the Jet Propulsion Laboratory, and a Computational Scientist at Cray Research. Dan's interest is in the development and use of advanced cyberinfrastructure to solve challenging problems at multiple scales, including in applications, algorithms, fault tolerance, and programming in parallel and distributed computing, and in policy issues, such as citation and credit mechanisms and practices associated with software and data, organization and community practices for collaboration, and career paths for computing researchers. He is a senior member of the IEEE and ACM, a founding editor and current Associate Editor-in-Chief of the Journal of Open Source Software, and Steering Committee Chair of the Research Software Alliance (ReSA).
About the series
The Precision Convergence series is launched to catalyze unique synergy between, on the one hand, novel partnerships across sciences, sectors and jurisdictions around targeted domains of real-world solutions, and on the other hand, a next generation convergence of AI with advanced research computing and other data and digital architectures such as PSC’s Bridges-2, and supporting data sharing frameworks such as HuBMAP, informing in a real time as possible the design, deployment and monitoring of solutions for adaptive real-world behavior and context.
The Precision Convergence Webinar Series is co-hosted by The McGill Centre for the Convergence of Health and Economics (MCCHE) at McGill University and The Pittsburgh Supercomputing Center, a joint computational research center between Carnegie Mellon University and the University of Pittsburgh.
