Heading towards the 2012 Olympics in London, Quayola and Memo Aktenvia translate athletic movement, which in itself is often considered beautiful, to generative animations. Collectively, the piece is called Forms, which is on exhibit at the National Media Museum.

Forms is a digital artwork that responds to the human body in motion. It focuses exclusively on the mechanics of movement, using footage of world-class athletes to illustrate human movement at the extremes of perfection.

Videos of athletes were processed through custom software to create evolving abstract forms that explore the relationships between the human body and its movements through time and space.

There’s also a short Q&A with the artists on the Creators Project that’s worth a read.

[via The Creators Project]

Kirk Goldsberry, an assistant professor of geography at Michigan State, applies his skills to the basketball court.

In the quest to better understand the “average” NBA shooter I have begun making composite shooting charts for each position in the league. My eventual goal is to establish a spatially informed baseline and to map every shooter in the league against an average shooter. These charts are not good for that task, but they’re interesting nonetheless. Here are composite shooting charts for each of the 5 conventional basketball positions. I combined the shooting data for every player in positional groups. There are some bizarre trends including some fascinating asymmetries.

Above shows points per field goal attempt for all NBA field goal attempts from 2006 to 2011. Red means more points and blue means fewer points, so as expected it’s orange-red outside the three-point line and dark red in the high percentage key. It starts to get interesting as Goldsberry breaks things down by player and position. Read the full paper [pdf] to really get into it.

For the record, my personal basketball scoring map would be all red. Don’t let my one-inch vertical leap or my low fantasy basketball ranking this season fool you. I can light it up.

[via Slate | Thanks, Kevin]

As a complement to Shan Carter’s exit poll dancing boxes, The New York Times provides another view with an interactive triangular scatterplot.

In the dancing boxes, you can see how states are inclined to vote based on exit poll groups. In the scatterplot, on the other hand, the groups within each state are plotted, with an added dimension towards candidates other than Santorum and Romney. The navigation bar on top and clicker on the left let you see tendencies of each state.

Like the dancing boxes, the transitions make the chart. As you browse by state or by category, you’re able to see differences between groups when shapes move across the screen.

In somewhat related news, The New York Times graphics department is looking for summer interns. Send your interest to Steve Duenes (duenes [at] nytimes [dot] com) and Amanda Cox (coxa [at] nytimes [dot] com). I interned there a few years ago, so I can tell you first-hand that you’ll learn a lot — probably more than in any class you’ve taken — while working with the best in the business.

[New York Times]

Kitchen Budapest explores local news coverage in Hungary with sound and a bubbling map.

Ebullition visualises and sonificates data pulled from one of the biggest news sites of Hungary, origo.hu. In the 30 fps animation, each frame represents a single day, each second covers a month, starting from December 1998 until October 2010.

Whenever a Hungarian city or village is mentioned in any domestic news on origo.hu website, it is translated into a force that dynamically distorts the map of Hungary. The sound follows the visual outcome, creating a generative ever changing drone.

Next step: show the news causing those bubbles.

[Submap | Thanks, Attila]

Stephen Wolfram examines his archive of personal data from emails to keystrokes to phone calls, going all the way back to 1990. Above shows the hourly distribution of his activities.
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Data exists in digital form, on our computers and spreadsheets, but the exciting part about data is what it represents in the real world. Bits are people, places, and things. This is especially true with social data from places like Twitter and Facebook, where ideas flow and people talk to interact with each other in different ways. It’s not just retweets and likes. Bloom Studio, the folks who brought you Planetary, embrace this idea in their just released iPad app, Biologic.

The basic concept: choose a social network from the Twitter, Facebook or LinkedIn blobs on the opening screen. You will have to authenticate each one you try (only the first time) and then you will transition into a view of the people you follow represented as microbiological cells.

Glowing shapes inside the cells are activities (tweets, pictures, etc). The bigger the activity, the newer it is. The more the activity is moving, the more retweets/favorites/likes it has. Once you have read an item it gets darker so you can tell what’s new.

It looks like another great blend of data, generative art, and game dynamics. I don’t have an iPad though, so I’ll live vicariously through your comments. Grab Biologic (for free) on iTunes.

[Bloom Studios | Thanks, Tom]

James Cheshire ponders the difference between fast and slow thinking maps, and the dying breed of the latter.

So do the renowned folks at the NY Times Graphics Dept. prefer fast or slow thinking visualisations? I asked them what they think makes a successful map. Archie Tse said what I hoped he would: the best maps readable, or interpretable, at a number of levels. They grab interest from across the room and offer the headlines before drawing the viewer ever closer to reveal intricate detail. I think of these as rare visualisations for fast and slow thinking. The impact of such excellent maps is manifest by the popularity of atlases and why they inspire so many to become cartographers and/or travel the world.

A graphic that takes a little while to understand doesn’t always mean it was a failure in design. It might mean that the underlying data is hard to understand. Likewise, a graphic that isn’t what you expect might let you answer different questions than from the usual standby.

[Spatial Analysis]

Gregor Aisch wanted a better way to make maps online that allowed something other than the Mercator projection, so he developed his own. The result is Kartograph, a lightweight framework “for building interactive map applications without Google Maps or any other mapping service. It was created with the needs of designers and data journalists in mind.” No more tiles.

The framework is still in its infancy, with not much documentation, but the map-making process seems to be straightforward. It’s basically a two-step process. First you generate an SVG map with Kartograph’s Python component, and then you load the SVG with the JavaScript component, which is built on top of Raphael.

Check out the showcase for a sense of what it can do. You’ve got your choropleth, chart symbols, and 3-dimensional projections. The star however is clearly the map of Italy, complete with a cute little ferry that follows a geo path.

[Kartograph]

I missed this one a while back, but The New York Times had a look at the growth of government benefit programs, such as Medicare, Medicaid and Social Security, in the United States. On the surface, it looks like your standard choropleth map that shows percent of income from government benefits, but there’s a lot going on here that makes the piece really good.

First, the arrows on the top right let you browse through decades, going back to 1969. Roll over counties to see a time series for the corresponding region against the national average. The sidebar on the left lets you view breakdowns for different programs. And finally, the guide to key trends provides a narrative for noteworthy regions and patterns.

Now that’s some good data journalism.

[New York Times | Thanks, Jordan]