When trying to develop a research question for the mapping project, I knew I wanted to utilize a dataset from an institution that is participating in the Collections as Data project. It is a project that is prioritizing making clean collection data accessible, so that scholars can apply computational analysis to them. One dataset I found that had spatial metadata attached to it was the J. Willard Marriott Library’s dataset for their matchbook collection, which features matchbooks that were collected from business in Utah. I was curious what could we learn from seeing a map of the collection that we wouldn’t see from merely looking at the digital collection. Were there any patterns based on the types of businesses, and where they were located?
As mentioned before, the main data for this project came from the Marriott Library’s GitHub page. I also used a shapefile of Utah’s county boundaries, as well as one for Salt Lake City in order to highlight it on the map. I then used Carto to create my final map.
Luckily because my data was very good quality, I didn’t need to do any major work to clean it up. It included information about the business type, the location, a transcription of any text on the matchbooks, as well as links to the collection page for each item, which is the information I was interested in.
After adding all of my files into Carto I decided that what was most important to my map was being able to see the locations of the different types of businesses. I made the styling prioritize that by using color to help differentiate the business types, and by the background be more muted in greys and black. Since a majority of the businesses were in Salt Lake City or its vicinity, I styled the shapefile to be lighter than the rest of the map so that the boundary was clear and the density could be highlighted without being distracting from the points on the map. And since the priority was to highlight the types of business I created a filter so that the user could search and display the categories they are interested in.
While the focus was on the locations of the types of businesses, I didn’t want the fact that the data is representing physical objects to be lost. So I styled the pop-ups for the points to include information about the objects themselves. I thought that allowing users to to see the name of the business, descriptions of text and graphics on the matchbooks, and a link to the object in the library’s catalog, would help connect users to the physicality of what is being represented and create a path for them to learn more about individual points.
As mentioned, one of the things that became apparent once the map was fully visualized was that, as expected, the vast majority of the businesses were located in Salt Lake City and the near vicinity. These matchbooks were collected by Harold “Stan” Stanley Sanders, who lived in Salt Lake City. One imagines he picked these up as he went about his day to day business in Salt Lake City.
Otherwise, the matchbooks that weren’t located in the city were mostly from businesses located along Interstate 15. While I had expected those to be car related businesses, gas stations, repair shops etc., they were mostly restaurants and hotels. There are many national parks and forests along this route, so hospitality businesses would be a good fit to cater to potential tourists. The one matchbook listed as being outside of Utah is a hotel located in Zion National Park. So perhaps Sanders was a fan of visiting Utah, and Utah’s neighbors, national parks and the businesses located near them.
Notably there are only three matchbooks that are located outside of the Interstate 15-Salt Lake City corridor: a bar in the north-west corner of the state, and a restaurant and hotel in the south-west corner. One is located in Moab, right by Arches National Park, one in Monticello which it at the edge of the Manti-La National Forest, and the last is in Manilla which is just north of that Ashley National Forest, which includes Kings Peak, the highest point in Utah. It does seem as though Sanders was an avid tourist to all of the natural sights Utah had to offer.
When I was building I thought that highlighting Salt Lake City and the other counties of Utah would be the most important way to understand the locations of the businesses. However after studying the map, I think it may have been more beneficial to highlight where these businesses were in relation to national parks, and potentially major highways. It makes sense that Salt Lake City has the highest density of business, but it may be more interesting that all of the others are located near national parks or other major attractions.