Openscapes Champions Lesson Series
Chapter 1 Welcome
This book is a lesson series for the Openscapes Champions program. It is under heavy development; some chapters are only notes at this point.
Openscapes Champions is a mentorship program that empowers scientists with open data science tools and grows the community of practice. We mentor early career researchers in leadership roles – faculty, lecturers, program managers, and others who want to establish open data science practices in their labs and on their campuses. It is designed to meet scientists where they are and help identify incremental steps to make their data workflows more efficient and open. We’ve been building Openscapes from an open data science angle, but along with that comes the mindset of openness, collaboration, good intentions, and creating the culture we want in science. Note: “lab” is broadly defined.
The Series is framed around Lowndes et al. 2017, Nature Ecology & Evolution: Our path to better science in less time using open data science tools. That paper is a retrospective of how a team’s data workflow changed over four years; the Openscapes Series aims to help guide other labs to incrementally make similar progress themselves, no matter where they are starting from.
The first half of the Series focuses on efficiency and open culture within the lab, and the second half is about sustained learning and bringing these practices to the broader campus community. This Series is taught over a five-month period, with two Cohort Calls each month with Champions and their lab members. Calls are designed to be engaging, requiring discussion and participation through Google Docs and Zoom (group and breakouts).
Call agendas and slides are all available in a Google Folder, and identified individually in the following table. Additionally, we end each lesson by learning hands-on efficiency tips, compiled here as an Efficiency Tips Doc and Spreadsheet.
The Series is written (and always improving) to be used as a reference, to teach, or as self-paced learning. And also, awesomely, it’s created with the same tools and practices we will be talking about: R and RStudio — specifially bookdown — and GitHub.