[Online] The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce the concept of “reproducibility” and foundational strategies that can increase the reproducibility of your work particularly related to organization, documentation, literate coding techniques, version control, and archiving data and code for future access and use. We will also present a protocol, the TIER protocol, as a tool that graduate students or others can use that are first approaching reproducibility. In the second half of the workshop we will present a potential end-to-end reproducible workflow using git, RStudio, Binder, and Zenodo to demonstrate some of the concepts in practice. 

This workshop is eligible for 2 hours of Graduate School RCR Credit (GS717.06).

This event is offered virtually. A zoom link will be sent via email to registered participants to join the workshop.

The content of the workshop may be recorded. If you are uncomfortable with a recording being published, please contact the instructor at any time prior to the conclusion of the workshop.

Data Science, Data Management