The Wall: A Next Generation Retail Experience | Artefact | Blog

MacRuby is now v0.4 and HotCocoa::Graphics gets a little better too.

Inspiration for this project was derived from Processing and NodeBox. These excellent Java- and Python-based graphics programming environments are mature and full-featured, but HCG offers similar functionality using the elegant Ruby programming language and the power of native graphics processing on Mac hardware.

Many more examples at the HotCocoa::Graphics site.

We are visual animals. But before we can see the world in its true splendor, our brains, just like our computers, have to sort and organize raw data, and then transform that data to produce new images of the world. Beginning Python Visualization: Crafting Visual Transformation Scripts talks about turning many types of small data sources into useful visual data.

The about page adds some bullets, in particular this one: “Write ten lines of code and present visual information instead of data soup.”

Yes! We’ll never get rid of lists and columns of numbers but a simple visualization is often all you need. Sparklines? Little additions. Make Tufte proud.

I think this data soup problem is responsible for me wanting to spend more time with Mathematica. Mathematica makes it relatively easy to do visual data analysis. Check out the Flag Analysis with Mathematica post from the Wolfram blog for a good example.

And catch a glimpse of Karsten Schmidt’s sketchbook as he works out the details.

Amble Time / “A shortcoming of standard maps is their inability to convey a sense of temporal scale. Can I stroll to the park for lunch, or would it take me all day? Amble Time adds an element of time to a PDA-based tourist map. By using a GPS system and your average walking speed, it creates a bubble that indicates everywhere you could walk in an hour.” This could be a lot of fun.

Don’t bother clicking, the url is kaput. One quick Google finds Amble Time alive and well:

A steadily shrinking area of a city map shows where you can walk as time ticks by. The bubble shows everywhere you could go within timing constraints that you provide. Researchers used this “travel-sensitive alarm clock” to explore ways that location-based information and ad-hoc networking could support participation in interactive stories.

There’s even a nice PDF available, Time, Voice, and Joyce, that discusses the project Amble Time was built to support:

We present a design for recapitulating walks through Dublin’s City Centre by characters in James Joyce’s Ulysses. Our computationally supported walkers will avail themselves of a “map with a sense of time” and a system that translates their hand lettering gestures as attributes of colourful typographic forms.

Now I definitely have to see it working again. Amble Time has iPhone written all over it.

[…] an illustrated manual on planning and designing for “good” density, and a catalog of more than 250 diverse neighborhoods across the country, noting density in housing units per acre for each site. Four photographs of each location are included—close-up, context, neighborhood, and plan views—to provide an impartial and comparative view of the many ways to design neighborhoods.

The website provides access too all those book images in a simple searchable database. Pick your region, your density and your setting and see what the density looks like. For instance, show me something from the West, low density and I don’t care about the setting. First two results are Beverly Hills and Hollister, CA. Compare and contrast Beverly Hills & Hollister with only 0.2 units/acre to San Francisco’s 222 units/acre. That’s a pretty profound demonstration of “density”:

So what, you have some interesting pictures to show folks. How do they help?

[…] many people have difficulty estimating density from visual cues or distinguishing quantitative (measured) and qualitative (perceived) density. We tend to overestimate the density of monotonous, amenity-poor developments and underestimate the density of well-designed, attractive projects, thereby reinforcing the negative stereotypes.

Some reality to counter the misperceptions in other words.

(As an aside: I’m very bullish on the use of visual explanations to educate these days and I’m not talking about the run of the mill business charts and junk like that. We have smart people putting together projects like Gapminder and Swivel, pushing the notion that data is best when it’s actually used to educate & debunk. Our tools for turning all this great data into visual answers are getting better too. Mathematica 6’s “integrated data sources” enable all sorts of crazy math mashups and symbolic programming visualizations. Might have to redefine what “math” is after Mathematica 6 gets done with it. Shame there’s only 24 hours in a day.)