One of the most common complaints I hear from people with large music collections is that browsing through songs as if scrolling through a spreadsheet is tedious. For these file-hoarding music fanatics, aimlessly browsing through their music library holds the same appeal as flipping through the card catalog of the Library of Congress.
The problem is: there comes a point when the iTunes paradigm of presenting your music collection as a column-sorted list of files is just absurd. Thankfully, Anita Lillie from MIT's Media Lab has based her thesis around a new way to visualize song data and she's called it MusicBox. The application is an academic exercise and unlikely to be developed into a commercial application, but it opens more than a few doors of perception when it comes to thinking about your music collection.
Lillie's MusicBox goes far beyond the conventional sorting strategies of ID3 tags and file types, expanding the vocabulary to include factors such as tempo, timbre, and even data summarizing the acoustical properties of a song, pulled from another project of Lillie's called Soundsieve. After dialing-in the particular view of your collection you're interested in, you can plot a path across your songs to create an intelligent playlist capable of, say, playing songs in escalating tempo, or grouping songs with similar acoustic fingerprints across multiple genres (think Lionel Hampton alongside gamelan music).
Of course, from a practical standpoint, I already have a hard enough time explaining to my parents how iTunes works. Demonstrating interrelated acoustical nodes will likely melt mom and dad's brains. For advanced users hungry for new and novel ways to navigate monolithic collections, however, Anita Lillie's MusicBox project points to hope on the horizon.