The Pronto Data Challenge received a whole lot of heavy statistics and graphs from insightful people trying to figure out what Seattle bike share users can teach us about cycling in the city, and more. We touched on this a bit in Part One, and we will dive deeper later in this series.
But today, we’re going to take a step back with Daniel Muldrew, who decided to take bike share station data and turn it into music. Before we explain how it works, let’s listen to Independence Day, 2015:
Here’s how Muldrew explains his process:
The number of bikes at the start of the day at each station is set to middle C. When bikes are added or removed throughout the day, the repeated notes for each station goes up or down on the Diatonic scale according to the change in the number of bikes. I scaled the data so that each note represents 15min and each 4 note measure corresponds to an hour. Thus, there are 24 measures in each song.
Each instrument represents one of the 7 stations below, which have generally have high numbers of daily trips and are all located downtown:
It’s so cool to hear the patterns of people’s movements through the city on different days in these songs. And for aesthetics, holidays work so much better than standard commute days because they aren’t so calm in the early morning hours and they crescendo at different times of day. And summer holidays like Independence Day take the cake because you can hear how much more active people are on such long summer days.
You can also hear how the system keeps pulling notes back towards C, whether due to rebalancing efforts by staff or by the self-balancing nature of the system users.