Learning through Networks

Before this class I did not think much about networks accept as a social phenomena use to gain social mobility through new media or events. This is not to say I did not see relations between people, places, objects and interrelatedness, but I did not know how to visualize these connections especially for academic inquiry. This week I created a network graph on Palladio a digital tool made from Stanford Universities Design + Humanities Lab. As a non-specialist (to say the least) Palladio was not complex to use. The most difficult part of using Palladio was gathering data. Coming from a literature and design background I have never worked with data before so an even more complicated task for me was formulating the kinds of research questions to ask through data making.

Motivated by my love for drinking wine and reading trade deals I decided to visualize the movement of grapes from the vine to sale through Palladio. While my love for wine made the subject matter easier for me to conceptualize my fascination with trade deals fostered a curiosity concerning the kinds of international relations my preferred wine brands create during their making and distribution process. I asked what kinds of international relations do the following wine brands create Bujanda, Cooper's Creek, Domaine Bousquet, Epilogo, Les Violettes, Juve y Camps, Rhanleigh, Seghesio, Suavia. In other words, I asked if any network of wine culture could be made visible by tracing the growing process at the vineyard up to distribution. So this was not a data set that new in advance that a network was there but a way of exploring if a network was there through the data making process. Creating data to explore potential connections and networks made this exercise an explorative learning experience and lot more approachable rather than generating original research to visualize an already existing network. Although if you are well versed in data I think Palladio would be a lot more useful.

So here is a picture of my dataset. It has the name of the wine, kind of grape, region it originated from to location where it is prominently sold. The names of the wine are for me to better understand where that particular brand sells best and to better understand the distribution of the wines I prefer. I specified the various kind of grapes because I believe it is important to understand which grapes are grown where. The last two columns are the coordinates to the region where the wine is grown and widely distributed. However, my coordinates are not precise it was more so the process I was focused on and so the coordinates within the region but not at the location of each vineyard or restaurant the wine is grown and sold.

After I copied and pasted my data into Palladio's prompt I was able to generate a map. I had to rename my data once I uploaded it on the next screen. However once the data is uploaded I clicked the tab on top of the page that said map. Once I got to the mapping screen I just had to list the data in the drop down menu (the data that was already uploaded) that I wanted to be visualized. Below is the map I generated. The red represents the country of origin to sale and the blue represents sale to origin. I was attempting to show a cyclical relationship between countries and wine drinkers within those countries that are benefiting from the circulation of particular grapes. Although I do fear my graph kindles more questions than answers. The style is sleek and with more data some interesting aesthetic relationships on the map may appear. The map does show a small network happening between California, New York and Paris as well as New York and Argentina. The map makes me wonder how other objects create informal networks or trade lines through distribution and the various micro cultures that are shaped by and through the trading of objects. However, now that I understand a little clearer how Palladio works the challenge would be getting geo coordinates specific to where the objects are located. I am not sure if for my own curiosities the exactness of the location is crucial but the analysis may be in the movement of the objects itself and the connections the movements make. In that case, I am not sure how credible a network graph can be with arbitrary coordinates or how Palladio can be reimagined with the intention to focus less on geo accuracy than on relationality. I used Palladio as a method to get research questions generated and not as a method to convey research answers. I am not sure what to what extent large datasets will become useful to me in my own research endeavors but I can say Palladio is just as much a tool for exploration as it may be a medium to reveal nuanced networks.