Mapping the Pratt Townhouses

Opening its doors in 1887, Pratt Institute has long been a physical and cultural presence in the Clinton Hill/Fort Greene neighborhood of Brooklyn. Erected in 1907, the Pratt Townhouses have weathered over a century of campus changes and development, consistently providing stable and relatively affordable housing for members of its community. To help investigate the history of the institution, I sought to provide researchers and knowledge-seekers with another tool to conceptualize and better understand the lives of the educators, administrators, and working people whose efforts have been essential to the school’s operation since its founding. To this end, I created a map of the Townhouses, linking them with various supporting visualizations and data points to promote exploration and provide opportunities to learn about the Pratt community members who lived in these spaces.

The Data

The original source for the data used for this project came from the archival holdings of the Pratt Institute Archives. The addresses, lease-holders, and rent amounts were compiled by a previous researcher, Patrick Kingchatchaval, from residential ledgers and leases generated by the Real Estate Department of Pratt Institute. To expand the available information on the residents, I consulted with Pratt Institute course catalogs from 1907 to 1971, which frequently listed their role at Pratt Institute (faculty-member, staff member or administrator, etc.) as well as identified the Department or Office that they were associated with during their employment.

Figure 1: “Lease Record Notebook, 1905-1917.” Real Estate Department of Pratt Institute. Buildings and Grounds Collection, PI-022. The Pratt Institute Archives, Pratt Institute, Brooklyn, New York.

Building the Map

After collecting historical and biographical details, I then gathered the necessary information to build my mapping element. To map the addresses of the townhouses, I utilized Google Maps to identify the geographical coordinates of the twenty-seven individual buildings that comprise the Townhouses. Given the close proximity of the buildings to one another, I sought out a mapping profile that could depict the building at a fairly granular level, providing building shapes and other geographic details at a lot level. Following the suggestion of the professor, I downloaded and imported data into Tableau from New York City’s Primary Land Use Tax Lot Output (PLUTO) dataset which offered a shapefile capable of mapping the townhouses at the level I wanted.

Initial Efforts

At the outset, I had difficulty linking my datasets correctly in a way that allowed them to be interpreted and read by Tableau. This process was complicated by data-cleaning errors such as an incorrectly converted zip code and a single misspelled row out of thousands of entries which led to the map not loading at all. After more careful review and correction, I was able to load and connect the data via the common “Address” fields. Once this initial hurdle was cleared, I had a map of the Townhouses that permitted visitors to click on the individual addresses and learn more about the tenure of the building’s residents.

Figure 2: Plain Map view with all addresses highlighted, surrounding streets labeled, and buildings outlined.

To facilitate further exploration of the map, I added two filters: one which allowed users to select an individual year, and the other which would highlight individual addresses. These filters can be used independently, or they can be used in conjunction with one another to isolate a specific address and year, identifying the individual who lived there at the time within the maps’ tooltip.

Figure 3: Address and Year of Residency filters activated with single address highlighted and text box listing the address and resident of that year.

Supporting Elements

While outside the purview of this mapping report, it is important to note that the Gantt Chart/timeline and the Sunburst visualizations currently interact with the map and navigation filters. Due to the linked datasets, interacting with the filters or clicking on address points within the map will also filter those elements. Selecting a single or multiple addresses changes the displays of both the timeline and the Sunburst graph, returning a list of all the residents over time for that building as well as providing a breakdown of the year count of each resident at that location.

Figure 4: Broader dashboard view, showing map with single address selected, as well as a timeline showing the progression of residents. Sunburst graph indicating how many years individual residents lived at that address.

Initial Reflections on Existing Functionality

One particular limitation that I encountered with Tableau is the ability to display information within the tooltip for the Map View. One broader issue is that of the “Resident” field where there are multiple individuals/data points associated with the address at the highest level (no filters engaged). As observed below, this resulting value for the “Resident” is an asterisk in this scenario. Speaking with a colleague familiar with Tableau, this inability to display or parse multiple values might be an overall issue with the platform, and so I need to reconsider that field, if there is not an existing work-around.

Figure 5: Map View when all years and all addresses selected. Text box or tooltip displays single address, but has an asterisk as the “Resident” value.

Another area or functionality that is currently lacking or is unsupported is that of multiple selection of addresses within the map. After reviewing and testing out the map , a colleague pointed out that he was unable to select individual, non-contiguous buildings by simply clicking on the map points. His intention was to review the information within the tooltips side-by-side for comparison as well as to see the timelines of the buildings’ residents within the same viewer. He was ultimately able to use the shape selection tool to do so, however, it was unwieldy and may not be intuitive to most users.

Figure 6: Multiple Addresses selected using the custom shape selection tool. The regular cursor does not allow users to select multiple individual addresses to view.

Future Steps and Developments

Despite the existing issue with the “Resident” display within the Map’s tooltip, it does work well with the map navigation filter when individual years are selected. When the filter is activated, users can view the resident for that year within the maps’ tooltip for all of the buildings. While potentially useful, I am considering getting rid of the “Resident” field of the Map tooltip as the Timeline/Gantt chart accomplishes a similar function, is visually compelling, and offers a different type of engagement for users.

In place of the “Resident” field, I will investigate generating calculations from other data points to provide “higher” level statistics or data regarding that location. This could include the total number of residents, the resident with the longest tenure at the location, and number of departments represented by the residents, and so on.

Another option besides these calculations within the tooltip could be to incorporate links to relevant archival records to connect the information and visualizations back to the source materials themselves, when possible. Site visitors and researchers could view historical images of the area, digitized versions of the leases, or digitized prints and negatives of the residents giving them additional routes of exploration and investigation, expanding their search beyond the dashboard itself.

Information Visualization

Student work at the School of Information, Pratt Institute