Champions Case Study: Horst Lab

By Horst Lab | May 30, 2019

Champions Case Study: Horst Lab

We have just concluded our inaugural cohort of Openscapes Champions. While sad to conclude, all Champion labs have so many exciting accomplishments and so much momentum for open data science, and it is truly just the beginning. Here we are posting individual case studies of accomplishments from Champions labs.


The Horst Lab teaches stats & data analysis to environmental science grad students at the Bren School for Environmental Science and Management at the University of California at Santa Barbara. Participating in Openscapes is lecturer Dr. Allison Horst and PhD candidate and lead teaching assistant Jessica Couture.

  • Allison: My favorite part of teaching is seeing initially (data) intimidated students grow throughout the quarter(s) to become confident and curious R-users who can responsibly wrangle and analyze their own real-world data, then successfully communicate results.

  • Jessica: I study marine aquaculture and sustainable food systems and incorporate open science practices in my work. I love teaching data and open science methods with Allison because it is great to be able to lower the barriers to these practices and move more scientists towards open and collaborative work.


Tidyverse nebula by Allison Horst


The Horst Lab Case Study shares our accomplishments for streamlining how we teach two courses. The introductory course, ESM 206, is ~100 graduate students from Bren and other departments, and additionally the optional advanced course, ESM 244, reached enrollment of 68 students from departments across campus in 2019! In both courses, we emphasize open practices and tools (R, RStudio, GitHub) for reproducibility and collaboration, along with data analysis concepts and methods. As a preview, we learned that:

“being a champion for open data science doesn’t always mean being an expert in R or GitHub (or data science more generally). It means that I can be a champion by helping other people (like my students!) realize the value of open, reproducible, collaborative data analysis and give them the confidence and curiosity to learn useful tools so they can do it on their own.”

Our key accomplishments are:



Congratulations Allison, Jessica, and all future TAs and students that are lucky enough to take your classes!



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