Alice Rawsthorn writes about visualization in today’s International Herald Tribune, which also includes a mention of Processing:

Producing visualization required the development of new tools capable of analyzing huge quantities of complex data, and interpreting it visually. In the forefront is Processing, a software system devised by the American designers, Ben Fry and Casey Reas, to enable computer programmers to create visual images, and designers to get to grips with programming. “Processing is a bridge between those fields,” said Reas. “Designers feel comfortable with it because it enables them to work visually, yet it also feels familiar to programmers.”

Paola Antonelli on visualization:

“Visualization is not simply an evolution of graphic design, but a complete and complex design form that requires spatial, narrative, synthetic and graphic sensitivity and expertise,” explained Antonelli. “That’s why we see so many practitioners – architects, product designers, filmmakers, statisticians and graphic designers – flocking to it.”

The Humans vs. Chimps illustration even gets a mention:

Take a scientific question like the genetic difference between humans and chimpanzees. Would you prefer to plough through an essay on the subject, or to glance at the visualization created by Fry in which the 75,000 letters of coding in the human genome form a photographic image of a chimp’s head? Virtually all of our genetic information is identical, and Fry highlights the discrepancies by depicting nine of the letters as red dots. No contest again.

The full article is here, and also includes a slide show of other works.

The O’Reilly press folks passed along this review (PDF) of Visualizing Data from USENIX magazine. I really appreciated this part:

My favorite thing about Visualizing Data is that it tackles the whole process in all its blood, guts, and gore. It starts with finding the data and cleaning it up. Many books assume that the data fairy is going to come bring you data, and that it will either be clean, lovely data or you will parse it carefully into clean, lovely data. This book assumes that a significant portion of the data you care about comes from some scuzzy Web page you don’t control and that you are going to use exactly the minimum required finesse to tear out the parts you care about. It talks about how to do this, and how to decide what the minimum required finesse would be. (Do you do it by hand? Use a regular expression? Actually bother to parse XML?)

Indeed, writing this book was therapy for that traumatized inner child who learned at such a tender young age that the data fairy did not exist.

I tend to avoid reading online comments since they’re either overly negative or overly positive (neither is healthy), but I laughed out loud after happening across this comment from a post about salaryper on the Freakonomics blog at the New York Times site:

How do I become a “data visualization guru?”
Seems like a pretty sweet gig. But you probably need a degree in Useless Plots from Superficial Analysis School.

– Ben D.

No my friend, it takes a Ph.D. in Useless Plots from Superficial Analysis School. (And if you know this guy, please take him out for a drink — I’m concerned he’s been indoors too long.)