Last Friday, I attended a workshop hosted by Geoff Cunfer, an agricultural historian, concerned with the agricultural history of the Great Plains, on the topic of Graphic Information Systems (GIS). Of particular importance, is the focus Dr. Cunfer places on the importance for GIS on “assembling, storing, manipulating, analyzing, and displaying geographically referenced information.” Yet, the information GIS offers is not merely geographical, even if geography is the “mode” by which information is conveyed by GIS. Rather, the user’s research agenda and the availability of data determines what “attributes” the maps used in GIS possess. Thus, it’s helpful to think of GIS as an archaeological tool whereby one may “dig” into the way maps change in order to create data-driven narratives.
As such, GIS is a great friend to historicist critics of literature. The interface of the GIS software used was very intuitive and graphically-focused (GUI) and the map attributes are ready-made for use in a statistics packet such as STATA or SPSS. It seems remarkably easy to map a novel with this software. Further, in addition to statistical analysis, GIS can be overlapped with a Network Cluster Analysis, allowing the maps to be layered in terms of attributes and methods.
Yet, GIS is not flawless – it requires some financial resources to get a project off the ground and the data-entry process is very labor-intensive. As a result, many existing GIS projects are team-based, collaborative, and tied to institutions, making GIS less open than it could be. However, GIS’ interface requires no coding like STATA does, meaning its learning curve is much less steep. Within an hour, and with some simple algorithmic instructions, most everyone at the workshop could assemble, label, and design a graph using operations the software is capable of.
