Curriculum
Data Carpentry to adopt Reproducible Research Curriculum
Authors: Karen Cranston BLOG
Communications Feedback
Curriculum
Authors: Karen Cranston BLOG
Communications Feedback
by Karen Cranston
Part of the mission of Data Carpentry is to encourage and enable reproducible research. The core Data Carpentry curriculum teaches researchers approaches and skills that are fundamental to reproducible research, such as scripting and data management. We are also adopting a Reproducible Research curriculum that explicitly focuses on reproducible techniques and some of the next steps, including version control and data publishing. This is an update on the efforts on this curriculum so far, and we expect to have it available soon as a Data Carpentry workshop option.
hashtag: #rrhack
link: hackathon repo
In fall 2014, NESCent held an initial hackathon to develop a set of materials for teaching reproducible research to computational scientists. Participants in the hackathon then taught three #rrhack workshops to unsuspecting guinea pigs students, postdocs, faculty and staff at Duke University, iDigBio / University of Florida and the Duke Marine Lab. A year after the initial hackathon, we re-convened people from the first event, along with a few locals from the University of Florida. This second hackathon aimed to expand / update the lessons based on feedback from the first three workshops.
Here is a summary of the feedback from our first three workshops:
Based on this feedback, we made the following changes to the workshop materials:
A note on R-vs-python: The materials currently use R + RStudio + knitr for all examples, and we intially had ‘translate-the-lessons-to-python’ on the agenda for this meeting. After some discussion, we decided that our time in Gainesville was better spent revising the existing lessons. This gives us a high-quality set of R-based lessons ready for teaching. But, pythonistas should not despair! We are already planning another event focused on developing a parallel set of materials on reproducibility using python (likely using Jupyter notebooks).
Interested in using this material? Go ahead! We’ve put it in the public domain under a CC0 waiver. Have questions? Each lesson has contact information in the README, or you can contact Hilmar Lapp for general questions about the #rrhack project.
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