Food is stuff. By stuff I mean items we could quantify and classify with qualitative interpretations. In theory, it sounds pretty easy to categorize them, monitor them, and then discuss them–through visual representations; however, it’s not so simple when you break things down.
In this vibrant, alluring visual above, you could see each state displays the relationships between foodstuff imported and exported in the United Sates. It looks simple, yes, but if you look closely, you may get lost. In an interesting article published in the Environmental and Science Journal, researchers explored the relationships between the 50 states when it comes to foodstuff commodities trade. These relationships, referred to as “edges,” by Scott Weingart, allow us to conceptualize how food stuff moves from one to sate to another. If you look at the states on the upper right heading clockwise, you will see states, such as Illinois, Louisiana, and California occupying the three largest areas. According to the study, these states generate the most traffic-flow of foodstuff. Additionally, if you compare Louisiana with Illinois, you will see a larger white/disconnected gap between Louisiana and the colors sprouting out. What that indicates is the amount of imported commodities vs. exported. While California has a well-balanced representation of imported and exported goods. What does this mean and why does it matter? Well, one way you could interpret this would be to say that the Midwest region, with the exception of California, plays a large role in our American food system dominating about 50% of the visual. The Midwest is know to have vital landscapes and climate for favorable food production. This could go into further, deep discussions ranging from politics, to history, economics and so forth.
The “dense” network, what we see above, illustrates what Scott Weingart explains as “[a] network of nodes where almost everything is connected to everything… ” (Demystifying Networks). Weingart describes nodes as stuff, generally speaking. The nodes we see, or rather don’t see embedded in this visual, are food commodities categorized in the following manner: “cereal grains, other agricultural products, animal feed and products of animal origin, nec, meat, fish, seafood, and their preparations, and, other prepared foodstuffs and fats and oils” (A Network Analysis of Food Flows within the United States of America). Vague categories, I know. Nonetheless, all foodstuff fits nicely into all of those categories. Weingart goes on to state that we need to make our networks “sparse” to maximize efficiency, from a humanistic perspective. The network analysis I provided in this week’s example is not necessarily humanistic, in fact, it’s scientific. To say that this network analysis needs to be less edged is incorrect, nor do I wish to propel that argument. Put simply, the data visualization I present is to give an example of a network analysis that displays complexity without “artificially cutting out” any edges.” This goes back to past readings where we discussed the relationships between Humanities scholars and Science scholars in the digital humanities realm.
