Team Members: Jessica Schwartz, Boren Li, Hao Hu Zhao

Design Rationale

Our data consists of different categories of information about each county in the United States. We decided that the most straight-forward and effective way to display the data was to create a colored map that reflects the values of one category of information for each county. In order to allow the user to explore more than just one category, we have a drop-down menu on top of the map.

The color scale chosen for the four currently available categories was a linear lightness scale from white to red, due to the continuous nature of percentage data. Each variable's scale is customized to show contrast in their respective value ranges. Some variables have narrower ranges and some have wider ones. For example, all the values for "Percentage of adults with diabetes" range from 3-19%, while the ones for "Percentage of obese adults" range from 13-47%.

Looking forward in the project, we are considering more categories of data to display to the user, along with different carefully chosen color scales. We also plan to add more interaction techniques like layer interpolation to visualize relationships between categories. We hope this will emphasize the relationships between diabetes, obesity and a variety of different statistics. Counties for which no data exists for a variable are colored black. We will add this to our legend in the future as well.

Development Process

Our team has 3 members. We worked together to choose the dataset and specify which parts of it we wanted to use. Together, we decided we wanted to visualize the data on a map. We split the development among the three of us. Jessica created the initial map visualization and chose to do so using TopoJSON. She then added visualization of one variable to move the process along which all took about a total of 8 hours. Boren added the remaining variables and added a dropdown menu for interaction so the user can visualize different variable on the map which took about a total of 10 hours. Hao worked on getting our data into a JSON, beautifying our design and helped fix a few bugs that arose which took about 10 hours total. We all collaborated on the write-up. The most timely part of this was getting all the variables on the map and debugging.