Data from: Designing data science workshops for data-intensive environmental science research

Over the last 20 years, statistics preparation has become vital for a
broad range of scientific fields, and statistics coursework has been
readily incorporated into undergraduate and graduate programs.
However, a gap remains between the computational skills taught in
statistics service courses and those required for the use of statistics in
scientific research. Ten years after the publication of
"Computing in the Statistics Curriculum,'' the nature
of statistics continues to change, and computing skills are more
necessary than ever for modern scientific researchers. In this
paper, we describe research on the design and implementation of a
suite of data science workshops for environmental science
graduate students, providing students with the skills necessary
to retrieve, view, wrangle, visualize, and analyze their data
using reproducible tools. These workshops help to bridge the gap
between the computing skills necessary for scientific research and the
computing skills with which students leave their statistics service
courses. Moreover, though targeted to environmental science graduate
students, these workshops are open to the larger academic community. As
such, they promote the continued learning of the computational
tools necessary for working with data, and provide resources for
incorporating data science into the classroom.