Website: Global Billboard

Combine Google Maps and APIs to visualize the most popular songs and musicians across the world.

Global Billboard site
Global Billboard is a mashup of Google Maps and the that charts the top five tracks and artists in (nearly) every country and over 300 metro areas around the world. Created in collaboration with fellow MFA Design and Technology student Alex Koplin.
Multiple charts on Global Billboard
Multiple info windows can be opened at once, allowing users to compare countries and/or cities.
Top tracks and top artists in a country listing (in this case, Brazil)
If a user selects a country both under ‘top tracks’ and ‘top artists,’ the two will stack in a single info window.
Metro Areas: Wichita, KS
Due to the popularity of the in the United States, there are 46 metro areas listed on the within the country! Shown here is Wichita, 70 miles south of the town where I grew up.

'Project' => 'Visualize music listening data based on geographical location in collaboration with fellow MFA Design and Technology candidate Alex Koplin.',

'Challenges' => 'Find a clear visualization while working within the framework of the Google Maps API, which will allow the user to see popularity of artists and music tracks, and compare them across the world.',

'Solutions' => 'Map top artists and top tracks in each country and metro area for which the API has data, and chart them in a simple horizontal bar graph inside a Google Maps ‘infoWindow,’ centered with a custom marker at the location (using the Google Geocoding API). We used a database of country names to call the API, and then used popularity of music artists and tracks (relative to the top track or artist) to determine the length of each bar in the infoWindow. We also utilized JQuery-powered drop-down list styles to unify the visual look of the site. Once an infoWindow has been opened, its marker remains on the map, in order that the user can reopen it and compare locations. Future directions that we would enjoy taking this project include logging weekly data to a) create longer-term visualization projects that compare country and city listening data across time, and b) utilize logged data to reduce the number of API calls required, since the API is occasionally subject to unexpected errors that can interrupt the user experience if they are not caught.'