What I find most interesting about this map is the level of abstraction. While the ordered circles offer the same data relationship of area to value as a system like Worldmapper (though the “area” of CAF’s unitless “giving index” is somewhat mysterious), the presentation is simpler and far more flexible.

It is surprising how well the placement of a circle in rough proximity to its neighbors succeeds in providing orientation. Without the need to show contiguous borders, regions can be easily isolated, or even repositioned. It’s an elegant system, within its own parameters.

Here, the increasing energy of powerful quakes is shown as an animation (the color coding refers to tsunami potential, based on NOAA’s data and key):

Compare the animation to this graph from Matlab Geeks:

The animation tells a story at the expense of comparison and data density. Even with the zoom out, the animation maps magnitudes to areas, which are notoriously hard for the human mind to compare. Each point on the Richter scale indicates an increase of magnitude of 32 times. Using a screenshot from the animation, I’ve confirmed this ratio:

Another visualization that uses areas to show magnitudes is The Hive Group’s interactive Earthquake treemap:

This application is a rich data-mining tool, but it doesn’t necessarily negate the animation. The animation tells a story. It is focused on making a dramatic point. The application allows multiple stories to be discovered, in non-dramatic fashion.

So says Wisconsin Department of Tourism spokeswoman Lisa Marshall.

“We’re not the Mitten State. Michigan, they can own that. We want to be known as the Fun State,” she said. The department used a leaf shaped like Wisconsin for its fall tourism campaign and will move onto something new for spring, but for now, the mitten stays.

For now, Wisconsin looks like this:

(via Ann Althouse)

Like Munroe’s Radiation Dose chart, the attempt to show geometric scale through changing units ultimately fails as a visual device. You can work through the Money chart point by point, but to find an overarching message  – other than “that’s a lot of money” — you have to replace visual intuition with a mental scale.

Corresponding to the scale problem is a comparison problem. Munroe assembles his square building blocks into all manner of shapes, including time-series charts and maps. The mosaic that results thoroughly fills the page while simultaneously making simple comparisons very difficult. Nothing lines up.

Yet the chart repays the effort it takes to meander about with a wealth of facts, some valiant attempts at creating context and broad connections, and numerous humorous asides.

From the individual’s point of view, a location may have boundaries, barriers, corridors, or an orientation that a street or geographical map doesn’t reveal.

Make sure to look at the project’s PDF presentation for some additional explanation and a series of interesting analytical maps that correspond to the issues listed above.

What does the mental map of your locale look like?

“Mapping spatial information reveals part of human history that otherwise we couldn’t possibly know,” said Anne Kelly Knowles, a geographer at Middlebury College in Vermont. “It enables you to see patterns and information that are literally invisible.” It adds layers of information to a map that can be added or taken off at will in various combinations; the same location can also be viewed back and forth over time at the click of a mouse.

The real joy of this feature is the portfolio of projects that accompanies the main overview. Here, for example, is a section from Ms. Knowles’ viewshed analysis of what General Robert E. Lee could actually see in the Battle of Gettysburg:

The pale ovals represent areas that historians have previously assumed to be visible to Lee. In Ms. Knowles analysis, all the light areas of the map could have been visible, depending on tree lines.

While Dynamic Diagrams’ digital orrery include Uranus (and Neptune), it is inaccurate in a way common to almost all maps of outer space: that of relative distance. Uranus is more than twice the distance from our sun as Saturn. The distance to the stars is ever more impossible to project. While Herschel was one of the first astronomers to conceive of deep space, not even he guessed at its vastness. In a footnote Holmes writes:

No astronomer yet had the least idea of the enormous distances involved, so huge that they cannot be given in terms of conventional ‘length’ measurements at all, but either in terms of the distance covered by a moving pulse of light in one year (‘light years’), or else as a purely mathematical expression based on parallax and now given inelegantly as ‘parsecs.’ One parsec is 3.6 light years, but this does not seem to help much. One interesting psychological side-effect of this is that the universe became less and less easy to imagine visually. (Holmes’ emphasis, p. 88)

Here is a challenge to champions of visual explanation and yet I fear Holmes is right. An example can be drawn from the use of parallax to measure astronomical distances. In another footnote, Holmes writes:

As with road directions, a diagram is a much better way to explain parallax than a written sentence. But it is interesting to try…. Stellar parallax is a calculation which is obtained by measuring the angle of a star from the earth, and then measuring it again after six months. The earth’s movement during that interval provides a long base line in space for triangulation. (p. 90)

Could Pantheon Books not provide Holmes a designer? Let me try a sketch:

The difference in angles A and B allow a simple trigonometric calculation with a baseline of about 300 million kilometers (left). However, astronomical distances are so great, the actual angles are nearly equivalent (right).

William Herschel and other 18th-century astronomers did not have the instruments to measure that difference. It wasn’t until 1832 that Thomas Henderson used parallax to calculate the distance to our closest star, Alpha Centauri. It wasn’t until the 1920s that Edwin Hubble was able to calculate distances between galaxies using the red-shift method (p. 90).

Holmes describes one other picturesque scene, a “human orrery” played by the poet John Keats as a schoolboy:

Keats did not recall the exact details, but one may imagine seven senior boy-planets running round the central sun, while themselves being circled by smaller sprinting moons (perhaps girls), and the whole frequently disrupted by rebel comets and meteors flying across their orbits. (p. 113)

One must assume that like mechanical orreries and the dD Orrery, the position of the planets was calculated in reference to the sun, not to each other.

Click through for full-size map, more data, and editorial content (whose thesis I find entirely unconvincing).

I’m more intrigued by the effectiveness of the visualization as an informational device. The juxtaposition is what matters, not the “true size”. If you mapped the true size of Canada, the United States, Mexico, and Central America against the continent of North America the result would be entirely pointless.

What makes Krause’s map intriguing is the contrast between large countries and a continent comprised mostly of small ones. To make a North American map of equivalent interest I would replace the large land masses of Canada, the United States, and Mexico with numerous small countries (to reverse the conceit we could replace Central America with Madagascar — a number of small countries with one large). Thus, we learn about the size of the selected countries as well as the size of the continent.

Roger Doiron of Kitchen Gardeners International has produced this image of what the White House garden would look like “if it were planted to reflect the relative costs of the main crops subsidized by US taxpayers”:

The data is from the Farm Subsidy Database.

At SocialFlow we analyzed 14.8 million public Tweets, and bitly links, posted between news about an unplanned presidential address (9:46 p.m. EST) and Obama’s address (11:30 p.m. EST) to see how dynamics of rumor creation played out during those critical hours on Twitter. Out of the dominant information flows observed in the data, we focus on the largest flow, engaging tens of thousands of users, validating speculation around Bin Laden’s death.

This jellyfish star chart presents a lot of data, but as best as I can guess, there is no coordinate system. It shows us constellations, not distance nor direction. There is no depth to it.

Still, hubs are interesting. Click through to see zoomed views.