Praxis of Reproducible Computational and Data Science

Among the top challenges of reproducible research are: (1) creation, curation, usage and publication of research software and data; (2) acceptance, adoption and standardization of open-science practices; (3) misalignment with academic incentive structures and institutional processes for career progression. I will address only the first two, proposing a praxis of reproducible computational and data science. It rests on a core set of standards, technologies and preferred tools-of-the-trade that, combined, form the basic curriculum of reproducible research. The talk aims to be practical, including concrete examples of how we work, what tools we use, and what norms we have adopted. Our lab practices are deeply rooted in the open-source software development model, and the open-science movement. Our essential tools are git for version control, GitHub for sharing and collaboration, Zenodo for archiving, the Journal of Open Source Software (JOSS) for publishing, and Jupyter for documenting research and teaching. These are augmented by more specialized tools like containers and cloud computing. The praxis is becoming standard now—what rests is adapting our culture, education, and institutions

Lorena A. Barba is an associate professor of mechanical and aerospace engineering at the George Washington University in Washington, DC. She holds a PhD in aeronautics from the California Institute of Technology and BSc/PEng degrees in mechanical engineering from Universidad Técnica Federico Santa María, Chile. Her research includes computational fluid dynamics, high-performance computing, computational biophysics, and animal flight.

An international leader in computational science and engineering, she is also a long-standing advocate of open source software for science and education, and she is well known for her courses and open educational resources. She was a recipient of the 2016 Leamer-Rosenthal Award for Open Social Sciences, and in 2017, was nominated and received an honorable mention in the Open Education Awards for Excellence of the Open Education Consortium.

Prof. Barba received the NSF Faculty Early CAREER award (2012), was named CUDA Fellow by NVIDIA Corp. (2012), is an awardee of the UK Engineering and Physical Sciences Research Council (EPSRC) First Grant program (2007), is an Amelia Earhart Fellow of the Zonta Foundation (1999) and a leader in computational science and engineering internationally. She is a member of the Board of Directors for the NumFOCUS non-profit, and a member of the editorial board for IEEE/AIP Computing in Science and Engineering, The Journal of Open Source Software, and The ReScience Journal.