Scientific Open Source Software: meat and bits but not papers. Is it real work?
Open source software is now the backbone of computation across the sciences and increasingly education. Yet the creation of scientific software is not well recognized as part of the enterprise of science in terms of training, career paths, intellectual recognition, organizational support, or funding. In this talk, I’ll explore the challenges of this contradictory situation, from the perspective of someone who has spent almost 20 years building open source software and communities. I have lived (often precariously) a dual life of “real academic” and of open source developer and advocate, working on IPython, Project Jupyter and the Scientific Python ecosystem since 2001.
I will provide an overview of Project Jupyter, including its intellectual core, the open source community context that surrounds it, and some of its impact. This will help frame the second part of the talk, where I'll try to open a conversation on the social and organizational challenges of creating and sustaining open, collaborative communities in the structure of research and education. The scientific, technical and community dynamics of projects like Jupyter presents interesting challenges in the context of traditional scientific incentives (funding, publishing, hiring and promotion, etc.) I’ll briefly outline some of these but will mostly focus on some ideas that I hope can move the conversation forward in productive ways.
Host: Center for Data and Computing
Fernando Pérez is an associate professor in Statistics at UC Berkeley and a Faculty Scientist in the Department of Data Science and Technology at Lawrence Berkeley National Laboratory. After completing a PhD in particle physics at the University of Colorado at Boulder, his postdoctoral research in applied mathematics centered on the development of fast algorithms for the solution of partial differential equations. Today, his research focuses on creating tools for modern computational research and data science across domain disciplines, with an emphasis on high-level languages, interactive and literate computing, and reproducible research. He created IPython while a graduate student in 2001 and co-founded its successor, Project Jupyter. The Jupyter team collaborates openly to create the next generation of tools for human-driven computational exploration, data analysis, scientific insight and education.
He is a National Academy of Science Kavli Frontiers of Science Fellow and a Senior Fellow and founding co-investigator of the Berkeley Institute for Data Science. He is a co-founder of the NumFOCUS Foundation, and a member of the Python Software Foundation. He is a recipient of the 2012 FSF Award for the Advancement of Free Software, and of the 2017 ACM Software System Award.