Your browser does not support the audio tag. Download: PDF | EPUB | MP3 | WATCH VIDEO [R]esource productivity can — and should — grow fourfold. … Thus we can live twice as well — yet use half as much. — Factor Four , 1997 When it comes to our sustainability problems, striving for greater resource efficiency seems like an obvious solution.
The Weecology lab group run by Ethan White and Morgan Ernest at the University of Florida is seeking a Data Analyst to work collaboratively with faculty, graduate students, and postdocs to understand and model ecological systems. We’re looking for someone who enjoys tidying, managing, manipulating, visualizing, and analyzing data to help support scientific discovery.
The Weecology lab group run by Morgan Ernest and Ethan White at the University of Florida is seeking a post-doctoral researcher to study changes in ecological communities through time.
We are very exited to announce a major new release of the Data Retriever, our software for making it quick and easy to get clean, ready to analyze, versions of publicly available data. The Data Retriever, automates the downloading, cleaning, and installing of ecological and environmental data into your choice of databases and flat file formats.
Last week Zack Brym and I formally announced a semester long Data Carpentry course that we’ve have been building over the last year. One of the things I’m most excited about in this effort is our attempt to support collaborative lesson development for university/college coursework.
This is post is co-authored by Zack Brym and Ethan White Over the last year and a half we have been actively developing a semester-long Data Carpentry course designed to be easily customized and integrated into existing graduate and undergraduate curricula. Data Carpentry for Biologists contains course materials for teaching scientists how to work more effectively with data.
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We are very excited to announce the newest release of our EcoData Retriever software and the first release of a supporting R package, ecoretriever. If you’re not familiar with the EcoData Retriever you can read more here.
If you’ve every worked with scientific data, your own or someone elses, you know that you can end up spending a lot of time just cleaning up the data and getting it in a state that makes it ready for analysis. This involves everything from cleaning up non-standard nulls values to completely restructuring the data so that tools like R, Python, and database management systems (e.g., MS Access, PostgreSQL) know how to work with them.
This is a guest post by Elita Baldridge (@elitabaldridge), a graduate student in Ethan White’s lab in the Ecology Center at Utah State University. As a budding macroecologist, I have thought a lot about what skills I need to acquire during my Ph.D. This is my model of the four basic attributes for a macroecologist, although I think it is more generally applicable to many ecologists as well: Data Statistics Math