I think the idea of the humanities moving from a document-centric ideology to a data-centric ideology is an interesting one. Perhaps what the author of the text is getting at is that examining ideas in microcosm could be an equally reductive form of investigation as just looking at a large data set. Traditional anthropological field work, for instance, that takes into account first hand interviews and case studies is a document-centric form of research can only go so far in understanding the practices of a particular culture. When data collection and statistical analysis come into play in a field that has previously neglected quantitative ways of knowing, the scale and scope of the investigation broadens too. I got kind of excited about the assertion the author makes that “if print culture foregrounds answers and pushes questions into the background, then perhaps data culture may do the opposite: it privileges queries and treats answers as if they are ephemeral”. At first I was resistant to this idea but I think there is some truth to it. I am all for privileging queries- I think ways in which we acquire knowledge should be messy and creative- if that makes any sense. There is a lot of pressure on the part of someone conducting research, in creating something like an ethnography (to use the example of Anthropology again), to draw immediate conclusions or create conclusive findings based on a small set of data. The same thing could be said of the minutiae of literary analysis: looking at the work of one author or one poem in its historical context. This seems to be how systems of knowledge and education in the humanities are set up- a kind of defensive strategy based on specificity and rhetorical prowess. In response to some of the questions put forward at the end of Emily’s post, I think that placing data culture at the forefront of research can broaden the scope of a researcher’s investigation and therefore allow new pathways of knowledge to open up. This is what might allow fields of study in the humanities to receive more time and attention (which I think they deserve).
I think the pressure “to draw immediate conclusions or create conclusive findings based on a small set of data” that you point out here is a real danger, especially in DH. When you have several charts and graphs of data at your disposal, for example, it’s really easy to start drawing out conclusions without stopping to reexamine the method of aggregating that data or the real significance of the data itself. This is one of the dangers, I think, of the kinds of research that Mark Algee-Hewitt explained in his lecture yesterday, and I admire Dr. Algee-Hewitt’s rigor in vetting his data. DH is not an end unto itself; the digital has to be combined with the human in order to yield significant research results. That’s why I think it’s important to ask the right questions of our data and to think just as carefully about questions themselves as we do about our answers to those questions.
Sarah, you made several great points, and I want to talk about learning being messy. This probably aligns with what the author is saying about privileging questions instead of privileging answers. Certainly many secondary schooling experiences are standardized — teacher talks, students reciprocate answer on selected response test, students move on to next grade, and repeat. As I heard Dr. Tom Wilson say yesterday to one of the attendees of the Digitorium, “All of these kids come to us having gone through 90% standardized K-12 schooling. When they get to us, we tell them all that standardized stuff you learned in K-12, forget that s***.” DH can help us move from such standardization that privileges answers into deeper scholarship that privileges questions.