I walked into a super market the other day and immediately noticed that the food was divided by type. The vegetables were in one area near the fruit, the dairy had its own refrigerator and the frozen food was kept in two aisles worth of freezers. While most things are hard to classify and even when they are those classifications are arbitrary, it makes sense to classify food because of their differing shelf lives. But even in the simple categorization of food there are some problems and even with “n” amount of categories there are still an infinite amount of categories not included, as mentioned in the McQueen article. A tomato is in the vegetable section but it has seeds like any fruit would, but there was no “vegetables with fruit-like qualities” sign adorning the top of an aisle. Citrus fruit is grouped together but they aren’t arranged by sour-ness. This line of thought is definitely nit-picky and unrealistic but it just shows that there is an infinite number of possible ways to categorize something as simple as food.
The level to which we categorize data and how categorize it effects how our reader interprets said data. When we leave out the infinite amount of categories we are leaving out an infinite amount of interpretations. It’s up to presenters to decide how the data gets organized and what message they want to send. One-dimensional schemes are often the simplest to understand but leave out a lot of information. N-dimensional schemes are the most informative but as n increases the difficulty of categorization increases for the presenter and it is harder for the reader to understand as well. Because categories highlight differences between things the most legible scheme is the simplest one with only two groupings that have clear boundaries, for example: true or false, legal or illegal, 0 or 1. This static grouping is effective when the differences are based in science but become ineffective when analyzing data from the ambiguous humanities realm. Linnaen taxonomy works because it’s based on morphology and DNA but the gender binary is arbitrary because it is based on loose social constructs.
I think this is the central crux of digital humanities. Like the super market, we have to arrange our data so it’s understandable to the reader and can be easily sorted through. But we are presented with a challenge because data from the humanities does not always fit into a nice, neat category. How do we arrange our data and what are we saying with whatever classification scheme we end up using?
Works Cited: Haliburton, Andrew. Bicycle Needs. 2010. 2010 EVC, Palm Springs. Andrew Haliburton. Web. 13 Oct 2014.