Reading Commentary for 9/24 1) “Big? Smart? Messy? Clean? Data in the Humanities” by Christof Schöch

I was surprised by how much this piece challenged my existing thoughts. Even in the first page, I had to rethink which resources and objects I consider ‘data,’ which I found to be a valuable exercise. I’m also excited to read more about Drucker’s idea of ‘capta,’ as it seems necessary for the framework we’re establishing here. That said, I didn’t find it entirely necessary for the two ‘kinds’ of data to be spelled out as separate ideas, as the eventual conclusion was that there needs to be a type of data that can be bigger and smarter. I do see how it is important to consider those two aspects of data, and which aspect we prioritize when we create a tool or work with data. I especially liked, in the elaboration of big data, when he wrote “What really counts, however, from my point of view, is less the volume than the methods used for analysis. And these can be successfully applied to smaller sets of data as well…” This point helped to emphasize the actual important aspects of big data. When he writes “I believe the most interesting challenge for the next years when it comes to dealing with data in the humanities will be able to transgress this opposition of smart and big data,” I was curious about whether this is a challenge specific to the humanities, or whether Schöch would consider this a necessary step for other fields as well.

2) “Humanities Data: A Necessary Contraditiction” by Miriam Posner

I appreciated the way in which Posner felt very honest about the ways in which humanists work- for example, she writes “humanists have a very different way of engaging with evidence than most scientists or even social scientists. And we have different ways of knowing things than people in other fields.” She elaborates that humanists are often able to draw conclusions by deep immersion in source material, instead of with traditional notions of ‘data.’ Frequently, I’ve found that humanists will try and explain their work in other fields’ terms or in terms that make their work appealing to others in their fields. Of course, Posner made her case for humanistic inquiry very well, but doing so did not necessitate portraying her work through the lens of others’ fields. I really appreciated her very accessible example that centered around silent film; I think it demonstrated very clearly how humanists (tend to) think, which I feel points to her conclusion (about another example) that “it’s quantitative evidence that seems to show something, but it’s the scholar’s knowledge of the surrounding debates and historiography that give this data any meaning. It requires a lot of interpretive work.” I also found it important that she emphasized not only the strengths humanists can provide to data science, but also the help that they will need- not only from data scientists, but also from librarians! I thought she very clearly and accurately laid out (some of) the problems facing humanists who work with data, and I’m curious to see if we consider any of them to be addressed in any way in the last three years or solvable in the future. Her final paragraph begins with “It requires some real soul-searching about what we think data actually is and its relationship to reality itself; where is it completely inadequate, and what about the world can be broken into pieces and turned into structured data?” I think this is an important question for us going forward.