City Symphonies

by Brian House

Creating instrumental and electronic music from collective OpenPaths data.

In my work, I explore the musical interpretation of data. Previously, I used OpenPaths and a year of my own location data to produce Quotidian Record, a sonification of my movements. The sound suggests that our habitual patterns have inherent musical qualities, and that daily rhythms might form an emergent portrait of an individual.

I am interested now in extending this work to the collective. Specifically, I want to explore how it might be possible to literally identify the "rhythms of the city" by algorithmically comparing and aggregating the daily pulses of its individual inhabitants. There is a long historical tradition of the city symphony in orchestra music and in film -- I want to hear what the equivalent would be in our contemporary era of big data. This might involve instrumental music, but also electronics, and might be presented in the form of a traditional performance or as a web-based, interactive project.

This work may play some part in my dissertation research in music and media theory at Brown University.

All OpenPaths data from participating individuals will be run through machine learning algorithms to determine common rhythmic structures within various city bounds. I am primarily interested in the temporal aspects -- specific latitude and longitude information will be discarded.

All work will be performed on my personal laptop or Amazon EC2 instances to which only I have access. No web-based content will ever feature individual data.

Hopefully, this project will result in a series of performances, web-based content, and recorded music, all available to the public. There might also be some academic writing involved.