Nike Plus Visualization
Data Visualization
2011
Our class was given access to a Nike Plus data set for 1,000 runs in New York City. Having explored Processing and Google Refine earlier in the semester, we had 3 weeks to play around with the data and present our visualizations to guest critics.

At first, I mapped the runs in succession, creating a layered map of the city. Next, I targeted each individual run by building a click-thru map, noting run distance. As I played with the data a bit more, I wanted to explore form over function. I then scrubbed the data for outliers, finding 920 runs and separated distance (yellow), time (orange), and pace (teal). Using a pie chart as my base, length and time determined the radius of each pie slice, and circle area represent pace, with each run's circle bisecting its arc.
  • Date / Spring 2011
    Class / Information Visualization with Nicholas Felton
    View / Posters

    Our class was given access to a Nike Plus data set for 1,000 runs in New York City. Having explored Processing and Google Refine earlier in the semester, we had 3 weeks to play around with the data and present our visualizations to guest critics.

    At first, I mapped the runs in succession, creating a layered map of the city. Next, I targeted each individual run by building a click-thru map, noting run distance. As I played with the data a bit more, I wanted to explore form over function. I then scrubbed the data for outliers, finding 920 runs and separated distance (yellow), time (orange), and pace (teal). Using a pie chart as my base, length and time determined the radius of each pie slice, and circle area represent pace, with each run's circle bisecting its arc.
  • Detail from one of the visualizations
  • Sorting data for outliers
  • Initial map exploration in Processing
  • Identifying individual runs and distance
  • First attempts using sin and cos
  • Working in Processing
  • Detail from one of the visualizations
  • Detail from a revised visualization