MapUtopia

Springsteen Touring Heat Map - Click for Animation

My latest project has been to take a career’s worth of Bruce Springsteen tour dates (data courtesy of The Timoney Group) and try to make sense of it all.  While I admit to being just a casual fan of Springsteen, working on this project has given me an understanding of the tireless performer he is.  The data encompasses more than 1,500 tour dates over 40 years.  In the beginning of his career, in fact, he would often perform multiple shows in one night.

Behind the scenes, the main map is a just a stylized version of the familiar google map interface that we all know and love.  Data is loaded from two JSON files; concert dates and album information.  The construction of the Heat Map itself is handled by feeding the data to a Google HeatMap layer (part of the Google Visualization API).  The tricky part is the animation.  While constructing a static Heat Map is a piece of cake, Google does not provide any quick and easy built-in functions or methods to accommodate animation.  Luckily, Google does provide something called an MVC Array. By using this type of array as the data source for the Heat Map, we can add and remove concert data and have these changes dynamically reflected in the HeatMap layer.

Aside from that complex piece of javascript, it’s mostly just a matter of some simple html and css to construct the layout.  The scrolling ticker of venues is a jquery plugin.

The intensity of the heat map is based on relative popularity.  Since the East Coast is very densely populated, any band would seem wildly popular there compared to the rest of the country.  The solution is to weight the size of the concert relative to the surrounding metropolitan area.  Thus, the heat map intensity of an arena show in New York City (pop. ~9,000,000) is just a flash in the pan compared to that of any show in Iowa City (pop. ~150,000).  Still, even with this adjustment Springsteen’s popularity in the Northeast and in the Rust Belt can’t be overstated.

Click here to view the animation.  A great writeup based on this visualization can be found here.

And, if you’re curious, Springsteen is on tour right now.

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Currently, I am working with Unidos por la Salud (Unidos) to create an Asset Mapping System. Unidos’ mission is to advance the cause of Latino health and form strategic partnerships within the community.  Unidos serves all of Colorado, with an emphasis on potentially underserved, rural counties.

The idea of an Asset Mapping System (AMS) is to create a resource for community leaders to turn to when they are looking for health data, resources, facility locations or demographic information.

The available information on the AMS is divided into two main categories; Services, and Data.  The services are point datasets of resources local to Colorado, and thus far include Health Clinics, Pharmacies, and Hospitals.  The ‘Data’ heading includes information from the latest Census and American Community survey datasets, as well as age-adjusted datasets from the Center for Disease Control.

For a quick technical tour, all of the data is currently housed in a MySQL database.  Data is retrieved using AJAX calls to the server.  The data is then reassembled by Javascript, and displayed via the Google Maps API.  The menu and the sleek legend container are JQuery components created by Matteo Bicocchi.  The iconography is part of a fantastic set of Google Markers created by Nicolas Mollet.

Current improvements in the works include increasing the depth of the Census data down to the Block level, as well as adding a number of new health datasets.  Greatly aiding in this task is the recent discovery of the Health Indicator Warehouse API, which should make adding new datasets a snap.

If you haven’t already, check out the mapping site.  For a fullscreen view without the map container, go here.

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MapUtopia is a company specializing in data visualization for the web.  If you have information that has a geographic component, MapUtopia can create a compelling visual graphic or animation that illuminates the data in a way that spreadsheets and static scatterplots can’t match.

Throughout this blog, I will be spotlighting current projects I am working on, as well as fun side projects of my own that I am creating.  Stay tuned.

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