I wanted to post this last week in my excitement over week 1 of pro football season (that’s the 300 lbs. locomotives pounding into each other kind of football, not the game played with actual balls and feet), but ran out of time. So instead, in honor of football Sunday, week 2, my favorite advertisement of last year’s football season:
The ad is a phone conversation with Coca-Cola’s Katie Bayne, animated by Imaginary Forces. A couple things I like about this… First, that the attitude is so much less heavy-handed than, say, the IBM spots that seem to be based on the premise that if they jump cut quickly enough, they can cure cancer. The woman being interviewed actually laughs about “big data” truisms. Next is the fact that it’s actually a fairly smart question that’s asked:
How important is it that you get the right information rather than just a lot of information?
Well… you know you can roll around in facts all day long. It’s critical that we stay aware of that mountain of data that’s coming in and mine it for the most valuable nuggets. It helps keep us honest.
And third, the visual quality that reinforces the lighter attitude. Cleverly drawn without overdoing it. She talks about being honest and a hand comes flying in to push back a Pinnocchio nose. Nuggets of data are shown as… eh, nuggets.
OpenStreetMap is a wiki-style map of the world and this animation displays a white flash each time a way is entered or updated. Some edits are a result of a physical local survey by a contributor with a GPS unit and taking notes, other edits are done remotely using aerial photography or out-of-copyright maps, and some are bulk imports of official data.
Simple idea but really elegant execution. Created by ITO.
A couple of hours ago was the release of a project I’ve been working on with Radiohead and Google. Lots of laser scanner fun.
I released some Processing code along with the data we captured to make the video. Also tried to give a basic explanation of how to get started using Processing to play with all this stuff.
The project is hosted at code.google.com/radiohead, where you can also download all the data for the point clouds captured by the scanner, as well as Processing source code to render the points and rotate Thom’s head as much as you’d like. This is the download page for the data and source code.
They’ve also posted a “making of” video:
(Just cover your ears toward the end where the director starts going on about “everything is data…”)
Sort of wonderful and amazing that they’re releasing the data behind the project, opening up the possibility for a kind of software-based remixing of the video. I hope their leap of faith will be rewarded by individuals doing interesting and amazing things with the data. (Nudge, nudge.)
Iron Man is the fulfillment of all the computer-integrated movies were ever meant to be, and by computer-integrated, I mean just that: beyond the technical wizardry of special effects, this is a film in which the computer is incorporated, like a cast member, into the development of the plot itself.
I’ve not seen the movie but the statement appears to be provocative enough to elicit cheers and venom from the scribes in the comments section. (This seems to be common at Design Observer, are designers really this angry and unhappy? How ’bout them antisocial personal attacks! I take back what I wrote in the last post about wanting to be a designer when I grow up. Some thick skin or self-fashioned military grade body armor over at DO.)
I wish they didn’t use Black Sabbath. Is that really the way it’s done in the film? Paranoid is a great album (even if Iron Man is my least favorite track) but the titles and the music couldn’t have less to do with each other. Enjoy the music or enjoy the video; just don’t do ’em together.
Visualizing Data is my book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. Unlike nearly all books in this field, it is a hands-on guide intended for people who want to learn how to actually build a data visualization.
The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)
The book covers ideas found in my Ph.D. dissertation, which is basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.
The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).
This site is used for follow-up code and writing about related topics.