📍 Online-only event
🗓 November 18, 2020, 15:30-17:00 CET
Communities and funding sources are increasingly demanding reproducibility in scientific work. There are now a variety of tools available to support reproducible data science, but choosing and using one is not always straightforward. In this tutorial, we present RENKU (https://renkulab.io/): an open-source platform integrating git, Jupyter/RStudio Server, Docker, analysis workflows linked with a queryable knowledge graph.
Christine Choirat is the Chief Innovation Officer of the Swiss Data Science Center and an Adjunct Lecturer on Biostatistics at the Harvard T.H. Chan School of Public Health and at the Harvard Extension School. Her research interests are data science and high-performance computing, reproducible research, and environmental policy and health policy.
Emma Jablonski is a doctoral researcher in the History of Science Program at UC San Diego, CA, USA. Previously, she worked on systems to facilitate computational molecular dynamics research at D. E. Shaw Research and on exoplanet climate modeling in the astrobiology group at NASA GISS, both in New York City. Her research interests include networks and complexity as applied to life in the universe and also to the flow of scientific information through academia and society.