<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sarah Supp on The Carpentries</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/author/sarah-supp/</link><description>Recent content in Sarah Supp on The Carpentries</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 20 Nov 2024 10:51:28 -0500</lastBuildDate><atom:link href="https://deploy-preview-705--carpentries-website.netlify.app/blog/author/sarah-supp/index.xml" rel="self" type="application/rss+xml"/><item><title>Sarah Supp: What I've Learned</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/2013/09/sarah-supp/</link><pubDate>Sat, 21 Sep 2013 00:00:00 +0000</pubDate><guid>https://deploy-preview-705--carpentries-website.netlify.app/blog/2013/09/sarah-supp/</guid><description>&lt;p>&lt;b>This post originally appeared on the &lt;a href="https://software-carpentry.org/">Software Carpentry website.&lt;/a>&lt;/b>&lt;/p>
&lt;p>I have to admit, that when I first decided I was going to learn programming skills, it was for academic survival. I was decidedly not excited about taking a course. As a graduate student, I was lucky that Utah State University had a &lt;a href="http://www.programmingforbiologists.org">Programming for Biologists&lt;/a> class, taught by Ethan White. Most universities still lack the infrastructure to teach these skills to scientists, outside of signing up for courses in the computer science department. Within the first week, I learned that programming is really like playing a series of logic games, and that it could actually be quite fun. Aside from practical skills, the most important thing I learned was not to be intimidated by computational problems.&lt;/p></description></item><item><title>Software Skills and Hummingbird Diversity</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/2013/09/hummingbird-data/</link><pubDate>Sat, 21 Sep 2013 00:00:00 +0000</pubDate><guid>https://deploy-preview-705--carpentries-website.netlify.app/blog/2013/09/hummingbird-data/</guid><description>&lt;p>&lt;b>This post originally appeared on the &lt;a href="https://software-carpentry.org/">Software Carpentry website.&lt;/a>&lt;/b>&lt;/p>
&lt;p>I am an ecologist. Traditionally, many ecologists spend part of the year outdoors, in the field, to collect data, and then spend the rest of the year analyzing that data and writing papers. With new sensors that passively collect audio, weather, or geolocation data, even a single field season can yield massive amounts of data. Add to that the pressing need for more long-term data (aggregating multiple years) and the problem of managing and analyzing the data becomes increasingly difficult for scientists without basic computational skill sets or strong computational collaborators.&lt;/p></description></item></channel></rss>