Stanford professor and reproducible research grand master Jon Claerbout argued that "interactive programs are slavery unless they include the ability to arrive in any previous state by means of a script.” Jupyter was born out of IPython (where the I stands for “interactive”) to offer a solution for creating reproducible computational narratives. The tool is both interactive and supports reproducible research, even if there is tension between the two attributes.
Lorena Barba explores how to build the ability to support reproducible research into the design of tools like Jupyter and explains how better insights on designing for reproducibility might help extend this design to our research workflows, with the machine as our active collaborator.
Lorena A. Barba is associate professor of mechanical and aerospace engineering at the George Washington University in Washington, DC. In addition to her research in computational science and engineering, she is interested in education technology, social learning, and massively open online courses as well as innovations in STEM education, including flipped classrooms and other forms of blended learning. Lorena is a recipient of the 2016 Leamer-Rosenthal Award for Open Social Sciences and was recognized with an honorable mention at the Open Education Consortium’s 2017 Open Education Awards for Excellence.
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