Ashleigh Novak is a spatial ecologist at the University of Massachusetts Dartmouth’s School for Marine Science & Technology (SMAST), focused on integrating tagging data into stock assessments that inform fisheries management. As a technical associate with the Fay Lab, Ashleigh participated at our first in-person Openscapes Workshop at NOAA NEFSC in February 2020 and shares her experiences here. She notes below that “given the current, global situation of transitioning to at-home research, our lab is leaning on many of the tools and skills learned from Openscapes.
Starting our #tidytuesday hacky hours This is our first community blog post by Openscapes Champion Allison Horst! Hi everyone! I’m Allison. I teach data analysis, statistics and presentation skills to graduate students at the Bren School of Environmental Science and Management at UC Santa Barbara. I’m also an Openscapes Champion. In Openscapes we discuss the need to create supportive spaces, like coding clubs, for useRs to practice and grow their coding skills.
[Sea]side Chats for data workflows Seaside Chats. Bluffside Chats. Fishbowl Chats. Bayside Chats. This is where we discuss data workflows in the lab. Running list of Champions teams’ Seaside Chats One of the long-term goals of Openscapes is to change the culture about how we work with data — and that requires normalizing even talking about data. We need to be able to have meaningful conversations about data and data workflows: the strategies, the struggles, the successes.
How to start a coding club Summary: start small, be hands-on, use existing tutorials, have fun. Here is my advice for starting a coding club. An example is Eco-Data-Science at UCSB. We are currently a community of >100 people; we meet 2x/month at the UCSB Library’s Collaboratory and skill share peer-to-peer, with all resources organized and archived on the website. But we started off small, with co-founder Jamie giving tutorials to friends one-on-one.
Build communities Openscapes is built with the idea that we can model the open culture we want in science. It starts with making open data science more visible and valued in our communities. So what can you do? All of the following involve seeking out opportunities to engage and learn, including others, and amplifying your efforts. read publications about open data science in academia in journal clubs. Examples: Lowndes et al.