If you ever asked yourself which is the best type of visualization for your data, The Data Visualization Catalogue could provide a guide to help you decide.
Severino Ribecca has begun the process of categorizing data visualizations based on what relationships and properties of data they show. With more than 50 types of visualizations, this catalog aims to be a comprehensive list of visualizations, depending on what you want to show.
The site has the potential to be a good reference for those looking to find the most efficient way to display data, or a new point of view to find different patterns or insights to understand what we need to communicate the meaning and the purpose of our data.
Atracktion is a visual representation of the evolution of music in about 60 years. It was presented on June 28 at Sonar, the International Festival of Advanced Music and New Media Art in Barcelona for its 22nd Edition.
We started with the Whitburn Project dataset, a collective effort to gather historical weekly music rankings published by the Billboard company (the project is now collected into the Bullfrog charts). Using publicly available sales data for selected weeks and years, we were able to estimate the percentage of sales for each song in the list –– that is, we converted ranking information into percentage of sales data.
The original database contained only partial information about the genre of each song. To find this, we automatically searched and parsed thousands of Wikipedia articles, collecting data about the genre (or genres) that people have assigned to each song. With this we were now able to estimate the percentage of sales of each musical genre and subgenre. (Note that the popularity of songs considered in two or more genres was split among them).
For the global number of recorded music sales in the US we use the estimations of the TsorT World Music Charts compilations.