Karmen Thornton
4/23/24
CODE 123
Meg Smith
For this final project, we will choose and analyze a data set from the St. Louis City Open Data Portal. The data set I selected to look at was the Occupancy Permits Dataset. As stated in the “About this Data set,” the data set is provided by the building commissioner. I couldn’t find a specific source, but I’d assume that whenever a building permit is issued, that info eventually goes to the building commissioner, and that’s where they collect this data and create a data set with it. The purpose of this data set isn’t stated. However, I would assume It was likely designed to keep track of people and places with occupancy permits as a public resource for citizens, researchers, or whoever might need access to this information. It also doesn’t state explicitly how it’s being used. Still, from the type of data sets they have created in this folder, I would assume analyzing trends in property occupancy and property investment trends over time or by location within the St. Louis area.
After looking through the datasets, I found that they were distributed in five different sections based on time or place, making it easy to navigate. For instance, they have a data set called “Occupancy Permits- September 1991 to Present,” which opens a CSV folder showing each separate year’s occupancy permits. They also have a set called “Occupancy Permits by Neighborhood,” where you can see a map showing the percentage of total permits by color. This is particularly helpful for someone who might not know what exactly they’re looking for or where to start looking. Regarding the actual data, depending on the person, it can help or hurt. There are a lot of visual graphs that are pretty straightforward and easy to understand, and some generic spreadsheets may take a little more effort to understand, especially if you don’t understand the jargon.
As a building commissioner, the creator plays a part in creating this data set. From their perspective of already having and knowing the data, creating the data might come easily to them. The commissioner’s perspective on planning and public transparency could’ve guided decisions on how to make it the most accessible to citizens and researchers. They also have the will to pay more attention to specific permits or properties based on priorities and resources that can lead to data complete or incompleteness and consistency across different permit types or areas. If I were ever to use this data, I would use it to see which areas are getting occupied the quickest and the most and in association with the income of that area. If it’s a higher-income area, are more permits being issued? And vice versa with the lower-income areas. This data holds the potential for understanding property occupancy and investment trends, inspiring new research questions.
Using this data in relation to MOBOT could help in various ways. I could look at the occupancy permits and the visitor demographics in the surrounding area and compare it to the people going through the gardens. This analysis can help find potential outreach opportunities to serve the local community better. This dataset can also help me analyze the patterns of property occupancy and the vibrancy of the neighborhoods. I could use this data to determine the occupancy permits in the surrounding areas where MOBOT might consider partnering for an outside event. I can see and identify venues or locations with appropriate event-hosting permits.