Maya posted a really interesting question on Miro today: “this article very clearly states that numbers don’t always speak for themselves, but to play devil’s advocate, can we ever think of a situation where they DO speak for themselves. Or is interpretation/context/subjectivity always imbued underneath?”

I think back to the instance of Terry White court case as a parallel situation where instead of numbers speaking for themselves, we were asking: does the film speak for itself? By looking at the Terry White case, yes! Interpretation, context, subjectivity is always imbued. Thus, I guess when we say when [blank] speaks for itself what we really mean is that there is only one interpretation that should be held as more “true” or “real” than other interpretations. The problem, then with numerical Big Data, is the lack of considering other contexts when making an interpretation.

That leads me to wonder how we can add more context into numerical Big Data and perhaps this question will open the door to new kinds of ethnographic work. I am speculating that when interpreting numerical Big Data, the context that is probably normally left out is the actual, qualitative everyday lived experiences of the people who the numerical Big Data represents. The Big Data represents the what happened but not necessarily the why. Thus, perhaps ethnography can help us to better understand the meaning and purpose that drives these lived experiences that are captured and in turn shape the interpretation of Big Data. I guess what I’m asking is: can we use ethnography to begin to collect “small, thick data” to create the categories and definitions that are used to interpret Big Data to come up with a more complete understanding?