Graffiti Complaints VS. Celebrated Street Art

New York, NY, USA

By Caroline
aesthetic welfare, graffiti, street art

In QGIS I tried mapping a M. Beardsley's theory of Aesthetic Welfare; in Carto I mapped graffiti complaints vs. celebrated street art.

Finding the subject matter for my final project was a little challenging, as I didn’t know the location of my thesis until the end of this semester, in addition to this, my thesis focuses on collaborative art practices – and so there wasn’t a lot of data that directly related to what I am working on in studio. However, for Miodrag’s public space lab, I have been writing about theories of aesthetic welfare and aesthetic justice and so I decided to see whether I could visualize the art theorist Monroe Beardsley’s theory of aesthetic welfare for my final project in methods.

For Beardsley, aesthetic welfare is a total sum of the aesthetic levels of a society at a given time and can be measured by the number of cultural institutions and artistic centers in a given place. Beardsley explores how aesthetic experience might be distributed more equally throughout society in his essay “Aesthetic Welfare, Aesthetic Justice and Educational Policy” (1973). Beardsley’s premise is that aesthetic experience improves our quality of our life and so opportunities for aesthetic experience should be a concern of planners and policy makers. However, in my estimation, Beardsley’s suggestions for how to measure aesthetic experience in order to distribute it more evenly throughout society are largely futile because his theory of aesthetic welfare is up holds the conventional tastes and normative aesthetic values. Although Beardsley is concerned with how to enrich more people’s lives with aesthetic experience, his examples of what constitutes this kind of experience is rooted in rather Bourgeoisie tastes; like art galleries, museums and the opera. I found that the data available in terms of art and cultural institutions also upheld Beardsley’s narrow conception of what makes an aesthetically rich experience.

The process of making this map revealed some common challenges when it comes to mapping cultural information. First of all, there isn’t actually a lot of comprehensive data on the locations of art and culture in New York City, perhaps this is partly because what constitutes art and culture is rather subjective, and so creating overarching data sets for to map all the cultural art institutions in the city could be very hard and problematic as someone who lives in Midtown Manhattan will likely have a very different conception of the spaces that should be included than someone living in Sunset Park. In addition to this, the data that is available on open data NYC spatializes the prestigious institutions and therefore the data available is very Manhattan-centric. I also found that a few of the data sets I looked at were very small. For example, the ‘cultural institutions by block and lot’ data set on NYC was created by the NYC Downtown Alliance, so the set was confined to a very small area of the city; similarly, completed Percent for Art Projects data set was pretty tiny and for some reason I couldn’t make a heat map using my theater points. I tried, but couldn’t solve that problem! In conclusion, I found that there was not enough data to make a comprehensive map of aesthetic welfare in New York City, but I really enjoyed the attempt!

Through my research for Public Space Lab, I have learnt about the term ‘aesthetic justice’ and have now understand that aesthetic justice is not achieved by making art museums and cultural centers more accessible to the public, although these efforts are beneficial. Aesthetic justice does not necessarily conform to pre-established tastes and ideas of high art; but it is attained through the creation of opportunities for art education and public participation. So I decided to see if I could find data that would list the schools with art education programs. I couldn’t find the data with locations of schools with art programing, so I wrote Inside Schools. They were really helpful and eventually sent me a CVS file with a list of the relevant schools, however I think the file they sent me was corrupt, because the points would not show up on top of my base map in QGIS, even though the projections were both in 2263 and I could see the points when I zoomed into the layer. Darn!

For the second part of the assignment, I was interested in the blurred lines that differentiates street art from graffiti and so I decided to focus my Carto Map on this dichotomy. My map spatializes 311 graffiti complaints in New York City alongside celebrated street art in New York City. The only data set I found on the topic was the data of graffiti complaints. After much searching and writing emails to various street art geo sites to see whether they could send me datasets (I never heard back from them), I downloaded an app called Street Art NYC and began manually making points and adding the artists names and websites to their pop ups. Unfortunately, due personal circumstances I lost some time on this, and so I have not completed mapping all 500 of the points yet! I’ve managed to map over one hundred and fifty at this point. However, I will continue to add to the map, and incorporate my own findings into it after this class. Though tedious, the exercise not only helped to familiarize me with how to create my own data, but also exposed me to some really great artists I’d never heard of before!