Digital Reflection 2

   When we were given our list of terms to reference in our second digital reflection, I immediately knew that I wanted to explore the idea of the meaningless of data without a narrative. In DTC 375 we have been working on data collection and visualization, so that is where my mind has been for a while. With this project, I wanted to further explore the culture of data sets by connecting the ideas of data without narrative, data as destiny, and quantification bias.


   The first concept I am drawing from is the meaningless of data without a narrative. It is often the case that we associate data sets with complete objectivity and pure numbers, but that is not the case. If one were to stumble upon a piece of paper in a classroom filled with simple tally marks, what would they make of it? Was it the number of questions someone got wrong on a quiz? Is it a tally of how many students attended class? Furthermore, the context of a data set is just as important as the numbers themselves. What would the implication be if one were to find the same tally marks etched into a concrete wall instead? If one is to understand the nuances of data collection and the effects it can have on public perception, they must be able to explore the narrative and context of any given data set.


   In my poster, this idea is primarily shown through the graphs in the frames. While the graphs look like they could be part of any legitimate data set, none of them have any sort of context or narrative. It is important to not that although we can seem to be looking at a large chunk of information, we really aren’t gaining anything from it without proper context or narrative.


   In conjunction with data without context, the idea of data as destiny is also represented in this poster. In a world where data drives many aspects of our lives (credit, employment, predictive policing, etc.), it is safe to say that we, as humans, place the idea of data on a high pedestal. Because of this, we allow it to fuel our decisions. While data allows us many opportunities and conveniences, it can also do more harm than good when implicit biases are perpetuated in data and algorithms. My goal was to show this idea of data as destiny with the crowd of people looking up at the data. The image of the crowd simultaneously evokes ideas of the importance we place on data as well as a scenario of lining up for your “fate”.


      The last course concept I thought about here was quantification bias as described by technology ethnographer Tricia Wang. As mentioned earlier, it is clear through the way data runs our lives that we place a high importance on it. Because of this, it only makes sense that we place an even higher value on data with larger numbers. Larger numbers, or “big data”, is often associated with objectivity (even more so than dense data, or “thick data”). In order to illustrate the importance we place on “big data”, I put the graphs (which contain large sample sizes) in frames. Frames are usually reserved for objects we find significant (artwork, antiques, important photographs, etc.), so I wanted to highlight what we thought of this data by placing it in frames.