Posts Tagged visualization
This week the Echo Nest is extending the data returned for an artist to include the active years for an artist. For thousands of artists you will be able to retrieve the starting and ending date for an artists career. This may include multiple ranges as groups split and get back together for that last reunion tour. Over the weekend, I spent a few hours playing with the data and built a web-based visualization that shows you the active years for the top 1000 or so hotttest artists.
The visualization shows the artists in order of their starting year. You can see the relatively short careers of artists like Robert Johnson and Sam Cooke, and the extremely long careers of artists like The Blind Boys of Alabama and Ennio Morricone. The color of an artist’s range bar is proportional to the artist’s hotttnesss. The hotter the artist, the redder the bar. Thanks to 7Digital, you can listen to a sample of the artist by clicking on the artist. To create the visualization I used Mike Bostock’s awesome D3.js (Data Driven Documents) library.
It is fun to look at some years active stats for the top 1000 hotttest artists:
- Average artist career length: 17 years
- Percentage of top artists that are still active: 92%
- Longest artist career: The Blind Boys of Alabama – 73 Years and still going
- Gone but not forgotten – Robert Johnson – Hasn’t recorded since 1938 but still in the top 1,000
- Shortest Career – Joy Division – Less than 4 Years of Joy
- Longest Hiatus – The Cars – 22 years – split in 1988, but gave us just what we needed when they got back together in 2010
- Can’t live with’em, can’t live without ’em – Simon and Garfunkel – paired up 9 separate times
- Newest artist in the top 1000 – Birdy – First single released in March 2011
In a couple of weeks I’m giving a talk at SXSW called Finding Music with pictures : Data visualization for discovery. In this panel I’ll talk about how visualizations can be used to help people explore the music space and discover new, interesting music that they will like. I intend to include lots of examples both from the commercial world as well as from the research world.
I’ll be drawing material from many sources including the Tutorial that Justin and I gave at ISMIR in Japan in October 2009: Using visualizations for music discovery. Of course lots of things have happened in the year and a half since we put together that tutorial such as iPads, HTML5, plus tons more data availability. If you happen to have a favorite visualization for music discovery, post a link in the comments or send me an email: paul [at] echonest.com.
This looks like it’d be fun to play with:
Take a look at Kurt’s weekend hack to make a visualization of the Echo Nest artist similarity space. Very nice. Can’t wait for Kurt to make it interactive and show artist info. Neat!
Justin and I have been working hard, preparing our tutorial: Using Visualizations for Music Discovery being presented at ISMIR 2009 in Kobe Japan. Here’s a teaser image showing 85 of the visualizations that we’ll be talking about during the tutorial. If you’ve created a music visualization that is useful for music exploration and discovery, and you don’t see a thumbnail of it here, let me know in the next couple of days.
Radio Labs now has a new visualisation called Radio Waves that shows the kind of music that is played on the various BBC stations. The visualization shows info about what genres, artists, year of release, which DJs play which music. There’s lots of info presented in an interesting way. Read all the details at the Radio Labs blog and then check it out: Radio Waves
Justin and I have been working on our tutorial on using visualizations for music discovery to be presented ISMIR 2009. One part of this tutorial will be a survey of current commercial and research-oriented systems that use visualization to help people explore for and discover new music. Ultimately we hope to build a comprehensive web directory of these visualization as part of the supplementary material for the tutorial. We could use your help building this directory. If you know of an interesting visualization that is used for music discovery (or even a technique that you think *could* be used for music discovery), add a link/description in the comments on this post or send me an email at firstname.lastname@example.org. Thanks much!