Introduction

For this project, I used several datasets to explore relationships between community boundaries, “empowerment zones,” public art, and public parks, in Chicago, IL, as of 2011 (the most recently updated data that I found outlining Chicago’s “empowerment zones”). I approached my visualizations with the following questions in mind:

1/ What is the relationship between community boundaries and “empowerment zones,” in Chicago?

2/ Is there a correlation between the location of public art, open spaces and the areas that have been identified as economically distressed (i.e. “empowerment zones”), in Chicago?

Materials

I used the following 4 datasets for this project:

• The City of Chicago’s “Boundaries – Community Areas (current)” shapefile (2016)
• The City of Chicago and The Empowerment Zones/Enterprise Communities (EZ/EC) program’s “Empowerment Zones” shapefile (2011)
• The City of Chicago and The Chicago Park District’s “Parks” shapefile (2012)
• The City of Chicago’s “Parks – Public Art” Excel file (2012)

While I did not have to manipulate this data at all, I did experiment with separating “latitude” and “longitude” into 2 columns, as it seemed to come up in many other datasets during my search for these files. For this, I used Excel (“Data” – “Text to Columns” – set “comma” as the limiter). Then, for my visualizations, I exclusively worked with “Carto” and “Carto Builder.”

Methods & Discussion

First, I layered all 4 of the datasets by adding them into Carto. I frequently saw this done, when looking for examples of visualizations working with similar data, and appreciated the effect.

Then, I brought the “empowerment zones” layer to the top, renamed each layer so that the titles represented the content, and colored each dataset as such: parks – green, empowerment zones– red, communities – blue, and public art – orange. While I realized that this would not be the most useful design for users who may be color-blind, I chose these colors for content reasons; green seemed like the most logical color for parks, red seemed like a good choice for “highly distressed” zones, blue was a harmonious selection for communities, and orange allowed the points to pop. My hope was that this approach to color selection would aid in the understanding of the map, as opposed to some of the more hectic examples that I had come across.

Next, I added a “Layer Selector,” allowing potential users to remove or, add any of the layers that I had included. Originally, in order to draw attention to this feature, I also added a “Text Item” (via “Add Element”), stating: “Select Layers to View.” Then, I changed the font size from “20” to “12,” changed the “Max Width” to “250,” and placed this text box directly above the “Visible Layers” box. I liked the look of this text element in Carto; however, when I tested the “Share Link,” I saw that the element shifted down, behind the “Layer Selector,” making it difficult to read, so I decided to delete it.

Finally, inspired by public art maps like the one below, I decided to make accessible some of the details about Chicago’s public art.

In the “Public Art” layer, I added the title of each piece of art, and the name of each artist, to the “Info Window,” making it visible with both “click” and “hover.” At this point, I also allowed “scroll wheel zoom,” to better accommodate the view and analysis of clusters of art. Later, in Carto Builder, I also experimented with the inclusion of these details in widgets, which re-calibrated with the zoom function, but ultimately, I went in a different direction with that visualization.

Share Link (Interactive Map): https://trobinson.carto.com/viz/753bd0bc-ab6f-11e6-a6c2-0ef24382571b/public_map/

With this visualization, I noticed that all but 1 of the “empowerment zones” crossed community boundaries, but the 1 “empowerment zone” that completely encompassed a community boundary was located in the Lower West Side. I found this intriguing because the Lower West Side contains an area of Chicago called Pilsen, where there is a tightly knit immigrant population (mostly Mexican American), and a strong sense of community. This discovery informed me that an “empowerment zone,” by no means, highlights an area with a lack of community.

Also, it became clear that parks and public art exist in “empowerment zones,” but at a much lower concentration than any other areas of the city. In many cases, the public art even seems to dance around the “empowerment zone” boundaries. To further illustrate this observation, I decided to continue with the map in “Carto Builder,” as it offers more analysis options than “Carto.”

To start, I added, layered, re-named and colored the datasets. Then, I did all of the following:

• In the “communities” layer, I added “Intersect Second Layer” analysis with the “public art” layer, and colored the results by “value.”
• For the sake of the map’s legend, I re-named the “communities” layer “Public Art Density,” because when I tried to name the legend, the title did not appear with the published share link (a “Carto” bug exposed).
• In the “public art” layer, I brought the “fill” and “stroke” transparency to “0,” in order to eliminate the points.
• In the “empowerment zones” layer, I brought the “fill” transparency to “0” and increased the “stroke” value to “3.” I chose purple as the color for these “strokes” because it highly contrasted with the yellow/orange color used to illustrate “public art density.”
• I hid the “parks” layer, as it was less relevant in this visualization.

Share Link (Interactive Map): https://tracyrobinson.carto.com/builder/6f71989c-ab79-11e6-bcce-0e3a376473ab/embed

This visualization further supported my conclusion that the areas with the highest density of public art exist outside of the city-identified “empowerment zones.”

Future Directions

When I first started with this project, I thought that I would be examining “rougher” areas of Chicago that could be selected for beautification initiatives, in an effort to build stronger communities; however, the results of these visualizations, especially those surrounding the Pilsen neighborhood, have me thinking critically about what it means to be an “empowerment zone,” and what qualifies as public art. Historically, the citizens of Pilsen have struggled to preserve their cultural presence against targeted redevelopment, so is there really an absence of public art in this area or, do only certain artistic expressions qualify for this city-produced dataset? If I were to move forward with this project, I would challenge the idea of public art by using reported graffiti data in contrast to city-identified public art, and layer those results with the community and “empowerment zone” boundaries, to see what trends may emerge.