The dog and I were having a philosophical conversation about data on our walk this morning. (I do tend to bounce ideas off of her while we are staring at squirrels.)
During our first week of Doing Digital History, I have been a bit uncomfortable about the relationship between data and research. Talking it over with the beagle, I came to understand why that is. My research process is not terribly systematic. I begin with a general question. In my case, that is often framed as something I want to understand. For example: I want to understand what it means to practice history as a form of public service. Next, I make decisions about where I might begin to approach that understanding. So: Federal workers are “civil servants;” how have historians in the federal service conceptualize their work? Finally, I go to primary sources. I allow those sources to re-frame my questions, to open up new questions, and to shape my understanding in ways I did not predict.
I have no idea if this process is an adequate reproduction of “the historical method,” and I’m not sure that really matters to me. I suspect it is a method that marks me as an interdisciplinary humanist. It probably also figures in my own sense of what it means to define myself as a public historian.
In any case, the beagle and I are discussing these questions of identity and process because I am framing a student-driven research project. I can see that it will be useful for them to assemble data in a tidy fashion so that we can create digital environments for study and interpretation. At the same time, planning for students to mine data leads me to at least three anxieties: 1. Is it possible, on the cusp of a new research project, to create a data spread sheet that will actually work; that will represent what I want students to find AND will actually predict accurately what they can find. 2. To what extent will framing a data spread sheet in advance limit what students actually DO find? Will the tyranny of the spread sheet encourage students to disregard or simply fail to recognize the value of sources that don’t fit our data parameters? 3. Is there a difference between approaching sources as producers of “data” and approaching sources as windows to understanding?
The beagle wasn’t sure…. SQUIRREL!