The goal of the challenge was to use open data and crowdsourcing to engage the growing data science community within Charlottesville and the surrounding area to help the city better understand pedestrian use of the Downtown Mall. The Mall is one of the most successful pedestrian malls in the nation and is a vibrant collection of more than 120 shops and 30 restaurants and the city wants to ensure that capital infrastructure plans are prioritized effectively.
The challenge required registered teams of data scientists to analyze a year of anonymized time series data on free WiFi usage, create a predictive model forecasting pedestrian usage, and to identify influential factors on pedestrian usage through visualization. Teams were encouraged to use other open data, including any relevant data found on the City of Charlottesville Open Data Portal.
Data sources primarily focused on the time series data provided, holiday data, Charlottesville event data, and weather data. We explored what would happen if we layered in additional open data sources such as the weather and events taking place on the Downtown Mall. From there, a clear story began to form around what draws pedestrians to the mall. With the story complete, we were able to summarize our findings into a website and make recommendations to the City of Charlottesville.
Visit https://haleemason.github.io/hackd-web/#/ to view our story.