We use music to connect with others, to find solace and comfort in the absence of social support,
to focus, to attain a deeper sense of meaning or perspective in life, and to transcend reality. Most of us
induce these states by selecting music from a particular style, artist, or track. But today, more music
is at our disposal than ever before: approximately 50k new tracks are uploaded to streaming services
everyday
A wise boat captain uses a map and compass to navigate the seas. Her map shows what destinations are available
and her compass guides her towards the destination she wishs to visit. But can this be translated to music?
Yes! Specifically, we can use data visualization techniques to discover and organize both new and familiar musical styles,
artists, and tracks! Throughout this site I will be "mapping" music in an effort to make the vast body of musical work on
Spotify
One of the few constants across all cultures is music: it transcends time, location, language, wealth, social status, and more.
Research suggests that people spend between 15% and 25% of their waking lives listening to music
In the prelude, I mention that music streaming services upload approximately 50k new tracks every day
Fundementally, music is a combination of sounds, and sound is vibration
There are countless ways to combine "sonorous air" to create a musical piece
Music is often organized in an ontological or taxonomical structure. These structures will never perfectly describe music. Just like any language is inadequate to express emotions, so are ontologies/taxonomies imperfect tools to describe
music.
Yet, they are still far better than nothing, and very useful when they are designed well. The most common and well-known approach is to organize music through genre ontologies/taxonomies
The traits that define a genre are more than a similar sound or summary of technical elements: subculture, fashion, geography, mentality and period of time all qualify as possible characterists of which a genre might be recognized
Astronomers describe the Universe using a hierarchical structure with several levels: I follow a similar approach to explain the musical universe.
The first significant level is the "genre galaxy," represented by a common denominator among a "large enough"
The unresolved question is whether there are even larger structures that lie somewhere in between genre-superclusters and the musical universe as a whole. But for this work, I think it is safe to consider genre-superclusters as the second-highest level in the hierarchy.
Music Atlas comes with three "maps"
The Genre Map provides a "bird's eye view" of the music universe. This is the broadest map and most ambitious visualization in the Music Atlas. The Playlist Relationships Map will explore relationships between popular playlists on Spotify. This map also represents the music universe at a high level, albiet to a lesser degree than the Genre Map. The Artist Sound Progression Map will visualizes how an artist's sound changes over the course of their career.
I am grateful to Chris Olah and the rest of the Distill Pub team for there insightful blog posts. Also, a big thank you to Sophie Engle for formally introducing me to data visualization.
Work was complete by Kai unless noted otherwise.
Concepts & Writing: Kai introduced and wrote the central concept and structure of this article.
Figures & Code: Some figures were drafted in RawGraphs. For all figures, the final version was implemented in D3. All code was written by Kai.
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