Musings, Explorations, and Announcements

*Today, Carl Boettiger gave a tutorial on the ROpenSci project and how to use their many packages to connect to online data repositories to retrieve and up deposit data. Here’s our screencast of the talk. All the code from this talk is available at this github repository, and you can download it as a *.zip file here. Thanks to Carl for for a great session and the ROpenSci team for their work!

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Today, Tim Bowles gave this presentation on the vegan package to the Davis R Users’ Group. The screencast and slides are below. You can also download Tim’s RStudio project with all the code, data, figures, and slides presented here. Thanks to Tim for a great session!

In my first pass at text analysis of the ESA program, I looked at how the frequency of words used in the ESA program differed from last year to this year. There are much more sophisticated ways at looking at word use in text, though, and I began to dive into the text-mining literature to find other ways to draw insight from ESA abstracts. One method I found is topic modeling using latent Dirichlet allocation (LDA).

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After my last post text-mining ESA Annual Meeting abstracts, Nash Turley was interested in the presence of the term “natural history” in ESA abstracts. I decided to collect a little more data by including programs back to 2010, giving a five-year data set. Thankfully the program back to 2010 remains in mostly the same format, so it’s easy to pull the data for these additional years. Now, not all talks that include natural history concepts will include the term “natural history”1 in their abstracts, but it’s frequency may be an indicator of importance, and variation in use of the term is may yield some insights.

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ESA is just around the corner, and many of us are gearing up and trying to figure out a schedule to cover all the talks and people we can pack in. ESA is a big conference and there’s far too much for any one person to see. In the end, everyone experiences a different part of the elephant. However, I thought it would be interesting to take a look at the big picture, and examine the ESA program as a whole to see what could be learned from it.

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