For this hackathon, we wanted to push the boundaries of the way people interact with data. Our hack combines Oculus Rift and Leap Motion technology with data from DC’s Open Data Catalog to provide a tangible and geographically meaningful experience while considering statistics on such diverse topics as median household income, crime rates, and unemployment rates. The viewer encounters a map of Washington, D.C. with divisions for each of D.C.’s 8 wards.
How it works
Using Leap Motion gestures, the viewer then chooses her preferred data set from menu options displayed at the ends of her fingers. Upon choosing, bars on each of the wards grow or shrink to represent the information in this data set. Numbers displayed beside these bars help to quantify the statistics they represent. The user can choose from different view angles and see more granular data such as specific types of crime or specific subsets of census data.
Challenges I ran into
One of the largest challenges was the need to get an intuitive and easy to use UI incorporated. We eventually found a promising github project but with poor support for the version of unity we were using and had to delve into it and patch bits to make it work out. Another challenge was deciding how to integrate leap motion to maximize the interactions with the data and make the program comfortable for all users. We tried several designs including one where you threw datasets (depicted as spheres) at the map to make different charts appear but this was distracting and confusing for users.
What's next for Bitcamp-Data-Viewer
This program has a lot of potential to evolve into a more modular data viewer, we use wrappers for deserializing csv into classes that can be directly displayed in the application meaning that tons of existing data sources could be used with this program with relatively little additional work. We focused on Open Government historical data from DC because it's where we live all year and we are interested in the wealth and privilege disparities sometimes embodied in city geographies.
Visit us at table 27C to check it out!