Monthly Archives: August 2011

Information is Beautiful is the site of David McCandless, a London-based author, writer and designer. Today he is a freelance data journalist and information designer.

I’m interested in how designed information can help us understand the world, cut through BS and reveal the hidden connections, patterns and stories underneath. Or, failing that, it can just look cool!

His site contains his work which includes a variety of visualizations raging from simple static designs to interactive. His site includes other useful information such as data sources.


Another good example of data visualization providing insight on a topic that can be hard to understand only textually. Not visually stunning but data-wise shows the impact the recession had on the job market. By Slate:

The economic crisis, which has claimed more than 5 million jobs since the recession began, did not strike the entire country at once. A map of employment gains or losses by county tells the story of how those job losses first struck in the most vulnerable regions and then spread rapidly to the rest of the country. As early as August 2007, for example—several months before the recession officially began—jobs were already on the decline in southwest Florida; Orange County, Calif.; much of New Jersey; and Detroit, while other areas of the country remained on the uptick.

Visualization tool that explains how a large sum of money like a billion is spent. A great example on how visualization can provide an explanation on a topic that otherwise is hard to grasp. From Information is Beautiful:

This image arose out of a frustration with the reporting of billion dollar amounts in the media. That is, they’re reported as self-evident facts, when, in fact, they’re mind-boggling and near incomprehensible without context. But they can start to be understood visually and relatively, IMHO.

Interesting article found at

Oliver Reichenstein and his team focused on the 140 most important people on Twitter and named the Map accordingly Cosmic 140.

How it works

Concentric circles representing the years since the birth of Twitter work as the underlying refence system. The sphere is divided in topical sections to group users from different fields. The topics are Technology (unsurprizingly the biggest group), News, Journalism, Business, Politics, Humor, Sport, Music, Entertainement, Intelectuals and Art & Design. Each Username is displayed with additional data like List Rank, List Volume, Follower Volume or First Tweet

Jeff Clark is a professional programmer who’s main interests are statistical analysis and data visualization. He has several data visualization projects that use Twitter as base. Visually his work is not that interesting but the analysis of information that can be interpreted from his visualization is worth studying. Some of his projects are:

Visualizes three search terms and returns a venn diagram showing how often a term is used and how frequent terms overlap in a single tweet.

Twitter Spectrum
Compares two search terms and shows which words are mostly associated with each term and which words are used the most in tweets in both terms.

Shows a stream of a user’s tweets with arcs that link to common words betweens tweets and common retweets.

Stream Graph
Shows a search term and which are the frequent common words found with the specified term for the last 1,000 tweets.