The visualization of historical and literary data has become a common practice in digital humanities, drawing on older traditions of visualizing in these disciplines. A variety of out-of-the-box tools exist for easily jumping in to data and information visualization, but when we use these tools we run the risk of research questions being wedged into a tool rather than the tool fitting the research. This course introduces students to humanities visualizations, using a programming language that let researchers prioritize their questions over the requirements of ready-made tools. Students will learn how to iteratively create plots and maps using the R statistical programming language, as well as how to manipulate data so that it can be visualized. Students will become familiar with the entire pipeline of visualization---from data manipulation to exploratory graphics to online interactive visualizations. In addition, the course will offer an introduction to Shiny, a framework for writing interactive websites with analysis in R.
Preparing for this class
There are several things that you can do to prepare for this course.
First, come prepared by installing R and RStudio. You can find instructions for installing R for your operating system at CRAN, and for installing RStudio Desktop at RStudio's website. While a version of RStudio will be available for participants via a server, it will be far better to have R installed on your own platform. Help will be provided on the first day.
Second, pick a dataset in your field that you would like to visit, or better yet, several. We will go over how to prepare the data for visualization, but you should acquire the data before coming to the course.
Third, try to gain a basic familiarity with R as explained in the suggested readings. We will provide an introduction in the class, but you will get much more out of the course if you work through the readings in advance.