How To

Starting our #tidytuesday hacky hours

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.

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[Sea]side Chats for data workflows

[Sea]side Chats for data workflows Seaside Chats. Bluffside Chats. Fishbowl Chats. Bayside Chats. This is where we discuss data workflows in the lab. 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.

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So you want to learn R

So you want to learn R So you want to learn R, where do you start? There are a lot of written and video tutorials and books and blogs online, but how do you navigate them? Our Ocean Health Index team put together a list of the resources we used to learn R that helped our team’s path to better science in less time. But this might still not be helpful for where you should actually start.

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How to start a coding club

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.

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Build communities

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.

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