Two polygon shapefiles were downloaded from the New York City Department of City Planning’s open data sets. The first is of any parkland located on the water’s edge, while the second maps all open spaces, also on the water’s edge. Both shapefiles contain various data concerning these waterfront areas, such as the names of the parks and ownership, respectively.  After uploading both datasets into CartoDB, they were merged. Merging the datasets was a necessary step in order to design the initial map, and it was done so by combining the “boro_code” column, which was found in both. The map was completed, with three interactive layers, in CartoDB.

Initially, while designing the map, the size of each waterfront area was considered in hopes of creating a map that would answer questions concerning the size and location of each waterfront area. As time progressed, and the data was re-examined, it was realized that the two key factors within the source from which the data was retrieved involved accessibility and ownership of the waterfront areas, respectively. In hopes of creating a more comprehensive map, attention was shifted to the possibility of identifying and exploring relationships between the waterfront areas’ accessibility status and who owns them.

The first example influenced the initial design, which focused on the size of the waterfront areas, by acreage.

The map uses a choropleth bubble layout to visualize airline density from international flight data. This example was chosen because a choropleth map would potentially visualize the size of each waterfront area effectively.

Again, upon further examination of the data, the following example was also chosen. It is a visualization taken from the New York City Planning page, designed with a portion of the same data used in the lab.

In order to optimize the use of the data, creating a multi-layer map was necessary. The map’s first layer was designed using the category layout to visualize the two ownership types, public and private, of each waterfront area. Publicly owned waterfront areas were assigned light purple, and waterfront areas on private property were assigned dark purple. Although this is the first layer, it was the last layer created and purple was chosen because it stood out from the colors chosen from the other two layers.

The second layer also uses the category layout. This layer visualizes the accessibility status for each waterfront. There are six statuses, and a color was assigned to each one. (1) The reds: dark red is not constructed; light red is a nature preserve with no access. (2) The blues: dark blue is in progress; light blue is in progress with limited access. (3) The greens: dark green is constructed with full access; light green is constructed with limited access.

The third and final layer, which was the first layer designed, visualizes the acreage of each waterfront area. For this layer, the bubble layout was used. Unlike the intended choropleth sample, the bubbles are assigned the same blue, but there is variation in the size of the bubbles. The more acres a waterfront area is, the larger the bubble. The radius for the bubbles was set from 5 to 25, which would provide enough range for the bubble sizes to be distinguishable from a minimum zoom level of approximately 8.

Each layer was designed to have information boxes appear when the user hovers. The information in the hover box is relative to the layer. When a waterfront area is clicked, the information box that appears contains an overview of the park (e.g. the park’s name, the borough, the water body, etc.). The basemap is Positron with labels, and each layer has its own legend. It is possible to set the map to be viewable with all three layers, or various combinations between the three, but the higher the layer is, the more visible it is. That is to say, the layers are hierarchical. Also, it is not possible to view the ownership and access status layers at the same time because they both use the category layouts. Finally, a search box was included to allow users to search for specific waterfront areas.

The next, and most obvious, step in providing the most use of this map, would be to allow users to see the ownership and access status layers at the same time. The ownership layer can remain with the category layout. However, symbols may work best for the access status layer, as shown by the example below, which is map of flight data from France.

With that, the acreage layer can stay with the bubble layout. However, with the addition of symbols, the size variation may not work as well. A choropleth bubble layout, like the example for the initial design, would be best.

The data provided in both datasets is fairly extensive. It may also be worth taking it a step further by creating a dashboard with various visualizations, other than maps, that put to use other columns in the dataset. A chart, for example, can allow the user to identify waterfront areas by the body of water they are near. Additionally, the agency associated with each waterfront area, which is also included in the datasets, can be used and examined to answer questions that go beyond the data shown by the map created.