Yet another “best of” list

Everyone else does a “best of the year” list, so why shouldn’t I? Here are links to my picks for recent years:


Music Library Visualization

September 5, 2008

I remember the first time I flipped through The Visual Display of Quantitative Information by Edward Tufte. My initial skim of the book was a kind of coffee-table experience — I was captivated by the aesthetics of the graphics without taking the time to appreciate their informational value. After a more thorough reading during my graduate coursework, chartjunk, small multiples, and other theoretical and practical concepts began to sink in. I remember disagreeing with more than a few of Tufte’s claims (and I still do), but I was enamored with his academic dedication to technical communication. It inspires me still today. I’ve been wondering lately…could I learn something about my musical preferences by visualizing my music’s metadata?

Even though I sometimes worry about Apple’s stranglehold on digital music, iTunes is the best digital media application available. I’ve been a loyal iTunes user for the past three years. Katie and I share our Mac, but I am responsible for 98% of the music uploaded. At a minimum, she deserves an understated tip of the hat: my wife is a good sport when it comes to my music-listening/buying/downloading habits. Since 2006, I’ve been able to collect and organize my music in ways that stacks of Case Logic albums could never accommodate. On the one hand, I miss liner notes and inserts. On the other hand, I’d prefer to filter and sort data fields click-by-click anyday over flipping through plastic sleeves in a book.

Last month, I decided to delve deeper into my (and Katie’s) music library. I began with a loosely-defined purpose and one particular variable. I wanted to analyze my song aquisition habits since the beginning of 2007 by genre. In other words, how have my musical tastes changed over the past year and a half? Of course, genre is an extremely subjective way to categorize. For example, I draw a clear line of distinction with my mind and ears between R & B, Soul, and Funk. For example, if the average person were asked to sort Donny Hathaway, Jill Scott, Poets of Rhythm, Bo Boral, and Mary J. Blige into these two genres, their results would likely be different than mine. Some artists (e.g. Rufus Wainwright, The Avett Brothers, Beirut, Air France) are pretty darn difficult to force into one bucket, but they can’t be duplicated and put into two buckets or divided among multiple buckets. I keep reminding myself that it’s okay if the genres are subjective — I’m the only one interested in dissecting my library anyway.

In most of the cases where genre blurs the boundaries of visualization, I used the category Alternative & Punk as a bit of a catch-all. As any ontologist will attest, homogeneity is crucial to characteristics of division. If genre is a characteristic of song division, then a couple of my labels don’t fit the bill. As a category label, Soundtrack is problematic because it is not homogenous with the others. Finally, the category called Blanks (also not homogenous) consists of music that has not yet been assigned a genre label.

Here’s a snapshot of my music library in July of 2008. The full data set, or all the music I own, is about 10,100 songs. The pie chart below depicts songs by genre.

Music Library, by Genre