Many researchers want to work reproducibly, but it is not easy. Considerable time is required to acquire the skills required for reproducible research, and the path is lined with pitfalls. This workshop gets researchers up to speed on how to create reproducible data analyses in R (and beyond). Specifically, researchers learn to automate the whole process from raw data to publishable manuscripts. This automation is possible by combining dynamic document generation (via R Markdown/Quarto), version control (via Git), workflow orchestration (via Make) and software management (via Docker). These tools and, therefore, automatic reproduction of results are available on any machine with Docker installed. The resulting workflow is, hence, highly transferable across machines and time. These core properties of reproducibility are demonstrated for any reader by automatically reproducing the manuscript online.

Instructors: Dr. Aaron Peikert (Website) and Hannes Diemerling (Website) from the Max Planck Institute for Human Development.

Participants: The targeted audience consists of researchers or graduate students working with R (students are welcome too). A very rough understanding of Git, RMarkdown, and the command line can be helpful to follow this tech-savvy workshop. Participants must bring their own laptop and have a working eduroam setup.

The workshop is supported by the Open Science Ambassador program of the Berlin University Alliance. 

Registration: https://www.formr-uni-siegen.de/repro-workshop-bua