I’m not going to be able to make it to THATCamp but I’m not letting that stop me from proposing a session…
Recently there has been a bit of a kerfuffle over the use of the term “data” to describe the people and traditions religious studies scholars study. On one side, some scholars find this term to be dehumanizing. On the other side, some scholars think it is a useful term for cordoning off one’s object of study. The debate can be found here, here, here, and here.
Yet, it strikes me that the use of the term “data” in this debate is not the same “data” that many digital humanists use. Or is it? That’s what I’m wondering. How do digital approaches to religious studies alter our notions of “data” and what counts as “data?” Is a digital religious studies de-humanizing? What is our data?
In addition to Amanda French’s workshop on Omeka, Lincoln Mullen, a Ph.D. candidate at Brandeis University, has also agreed to offer a hands-on workshop on using statistical programs to analyze data sets relevant to humanities scholars. Mullen has also agreed to hold a kind of THATCamp office hours after his workshop, where he’s agreed to work one on one with interested campers. Thanks, Lincoln!
Humanities scholars now have access to a range of data sets and techniques for analyzing them that were previously regarded as the province of scholars in other disciplines. In this workshop, we’ll try our hands at a couple forms of analysis, using data sets of interest to scholars of religion. We will make maps from the missions of the Paulist Fathers and do some quantitative analysis of religious demographic data. By bringing these common kinds of data analysis together, we will learn the basic practices and theories which underlie all of them. Of course we will have occasion to discuss what data analysis means from a humanistic perspective. During this workshop we will get hands-on with the statistical programming language R. While there are many tools to make maps, mine texts, and analyze numbers, R is especially powerful because it can perform all of these types of analysis. R is a favorite tool of academics, Google, and the New York Times, so it has strong support. You are encouraged to install R (the programming language itself) and the desktop version of R Studio (a tool to help you use R) in advance. Self-starters can watch some of Google’s video introductions to R to acquire the basics. While you will benefit from learning some of the theory behind the analysis even without using R, there is no substitute for performing the analysis yourself, and you’ll pick up the basics of a powerful digital humanities tool.