A very nicely done visualization from NPR of the U.S. Electrical Grid:

I mostly find this fascinating having not seen it properly depicted, but the interactive version shows more about locations of power plants, plus maps of solar and wind power along with their relative capacities.

I love the craggy beauty of the layered lines, and appreciate the restraint of the map’s creators to simply show us this amazing data set.

And if you find yourself toe tapping and humming “we gonna rock down to…” later this afternoon, then I’m really sorry. I’m already beginning to regret it.

(Thanks, Eugene)

These hopes were later dashed (or perhaps only fed further) when the apparition was denied in a post on the Official Google Blog crafted by two of the gentlemen involved in the data collection for Google Ocean. The post is fascinating as it describes much of the process that they use to get readings of the ocean floor. They explain how echosounding (soundwaves bounced into the depths) is used to determine distance, and when that’s not possible, they actually use the sea level itself:

Above large underwater mountains (seamounts), the surface of the ocean is actually higher than in surrounding areas. These seamounts actually increase gravity in the area, which attracts more water and causes sea level to be slightly higher. The changes in water height are measurable using radar on satellites. This allows us to make a best guess as to what the rest of the sea floor looks like, but still at relatively low resolutions (the model predicts the ocean depth about once every 4000 meters). What you see in Google Earth is a combination of both this satellite-based model and real ship tracks from many research cruises (we first published this technique back in 1997).

How great is that? The water actually reveals shapes beneath because of gravity’s rearrangement of the ocean surface.

A more accurate map of the entire ocean would require a bit more effort:

…we could map the whole ocean using ships. A published U.S. Navy study found that it would take about 200 ship-years, meaning we’d need one ship for 200 years, or 10 ships for 20 years, or 100 ships for two years. It costs about $25,000 per day to operate a ship with the right mapping capability, so 200 ship-years would cost nearly two billion dollars.

Holy crap, two billion dollars? That’s real money!

That may seem like a lot of money…

Yeah, no kidding — that’s what I just said!

…but it’s not that far off from the price tag of, say, a new sports stadium.

Oh.

You mean this would teach us more than New Yorkers will learn from the Meadowlands Stadium debacle, beyond “the Jets still stink” and “Eli Manning is still a weenie”? (Excellent Bob Herbert op-ed on a similar topic — the education part, not the Manning part.)

So in the end, this “Atlantis” is the result of the rounding error in the patchwork of data produced by the various measurement and tiling methods. Not as exciting as a waterlogged and trident-wielding civilization, but the remainder of the article is a great read if you’re curious about how the ocean images are collected assembled.

Look at those trenches! And now you can use the Google Earth software to fly through the area in the middle of the Atlantic where some god has decided to begin peeling the globe like an orange.

I’m waiting for the day (presumably a few years from now) that this feature includes other major bodies of water, revealing the hidden shapes beneath the surface of lakes or rivers that you know well from above. The physical relief version, that is. I’ll pass on the underwater Google Street View with their privacy-invading minisubs sticking their nose in everyone’s business.

From a cited article, Wikipedia notes that:

…the world’s center of population is found to lie “at the crossroads between China, India, Pakistan and Tajikistan”, with an average distance of 5,200 kilometers (3,200 mi) to all humans…

Though sadly, the map also uses a strange color scale for the heat map, with blue the area of greatest density, and red (traditionally the “important” end of the scale) as the least populated area. Even shifting the colors helps a bit, at least in terms of highlighting the correct area:

Though the shift is of questionable accuracy, and the bright green still draws too much attention, as does the banding in the middle of the Atlantic.

Outside of musing for your own edification, practical applications of calculating a population’s center include:

…locating possible sites for forward capitals, such as Brasilia, Astana or Austin. Practical selection of a new site for a capital is a complex problem that depends also on population density patterns and transportation networks.

Check the article for more about centers of various countries, including the United States:

The mean center of United States population has been calculated for each U.S. Census since 1790. If the United States map were perfectly balanced on a point, this point would be its physical centroid. Currently this point is located in Phelps County, Missouri, in the east-central part of the state. However, when Washington, D.C. was chosen as the federal capital of the United States in 1790, the center of the U.S. population was in Kent County, Maryland, a mere 47 miles (76 km) east-northeast of the new capital. Over the last two centuries, the mean center of United States population has progressed westward and, since 1930, southwesterly, reflecting population drift.

For added fun, I’ve created an interactive version of the map, based on a Processing example. (Though it took me longer to write the credits for the adaptation than to actually assemble it — thanks for all those who contributed little bits to it.)

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.

It’s tough to find many defenders of the status quo, in which a supermajority of House seats are noncompetitive. (Congressional Quarterly ranked 324 of the 435 seats as “safe” for one party or the other in 2008.) The mathematicians—and social scientists and lawyers—who gathered to discuss the subject Thursday are certain there’s a better way to do it. They just haven’t quite figured out what it is.

The meeting also seemed to include a contest (knock down, drag out, winner take pocket protector) between the presenters each trying to one-up each other for worst district. For instance, Florida’s 23rd, provided by govtrack.us:

Which doesn’t seem awful at first, until you see the squiggle up the coast. Or Pennsylvania’s 12th, which Wilson describes as “an anchor glued to a sea anemone.”

Fixing the problem is difficult, but sometimes there are elegant and straightforward metrics that get you closer to a solution:

The most interesting proposal of the afternoon came from a Caltech grad student named Alan Miller, who proposed a simple test: If you take two random people in a district, what are the odds that one can walk in a straight line to the other without ever leaving the district? (Actually, it’s without leaving the district while remaining in the state, so as not to penalize districts like Maryland’s 6^th, which has to account for Virginia’s hump.) This rewards neat, simple shapes. But it penalizes districts like Maryland’s 3^rd, which looks like something out of Kandinsky’s Improvisation 31.

This turns the issue into something directly testable (two residents and their path) for which we can calculate a probability — the sort of thing statisticians love (because it can be measured). Given this criteria (and others like it) for congressional district godliness, another proposal was a kind of Netflix Prize for redistricting, where groups could compete to develop the best redistricting algorithm. Such an algorithm would seek to remove the (bipartisan) mischief by limiting human intervention.

The original article also includes a slide show of particularly heinous district shapes. And as an aside, the images above, while enormously useful, illustrate part of my beef with mash-ups: Google Maps was designed as a mapping application, not a mapping-with-stuff-on-it application. So when you add data to the map image — itself a completed design —you throw off that balance. It’s difficult to read the additional information (the district area), and the information that’s there (the map coloring, specific details of the roads) is more than necessary for this purpose.

The blue is to be expected, given that the size of the win for Obama, but the red pattern is quite striking.

Also note the shift for candidate home states, in Arizona with McCain on the ticket, and what appears to be the reverse result in parts of Massachusetts, with Kerry no longer on the ticket. (The shift to the Democrats in Indiana is also amazing: without looking at the map closely enough I had assumed that area to be Obama’s home of Illinois.)

I recommend checking out the actual application on the Times site, the interaction lacks some of the annoying ticks that can be found in some of their other work (irritating rollovers that get in the way, worthless zooming, and silly transition animations). It’s useful and succinct, just like an infographic should be. Or just the way Mom used to make. Or whatever.

Includes links to PDF reports for each area which detail overall congestion and the worst bottlenecks.

Indiana Jones and the Fonts on the Maps

For the most part, the type usage in each of the movies is correct for the period depicted. With one exception: The maps used in the travel montages.

My theory is that this is because the travel maps are produced completely outside the standard production team. They’re done by some motion graphics house, outside the purview of the people on-set who are charged with issues of consistency. A nastier version of this theory might indict folks who do motion graphics for not knowing their typography and its time period—instead relying on the “feel” of the type when selecting. The bland version of this theory is that type history is esoteric, and nobody truly cares.

(Also a good time to point out how maps are used as a narrative device in the film, to great effect. The red line extending across the map is part of the Indiana Jones brand. I’d be curious to hear the story behind the mapping—who decided it needed to be there, who made it happen, who said “let’s do a moving red line that tracks the progress”—which parts were intentional, and which unintentional.)

Identifying the period for the faces reminded me of a 2005 profile of Matthew Carter, which described his involvement in court cases where date was in doubt, but typography of artifacts in question gave away their era. Sadly the article cannot be procured from the web site of The New Yorker, though you may have better luck if you possess a library card. Matthew Carter designed the typefaces Verdana and Bell Centennial (among many others). Spotting his wispy white ponytail around Harvard Square is a bit like seeing a rock star, if you’re a Cantabridgian typography geek.

From A to Z, font designer knows his type – a Boston Globe interview with type designer David Berlow (one of the founders of Font Bureau), some of the questions are unfortunate, but a few interesting anecdotes:

Playboy magazine came to me; they were printing with two printing processes, offset and gravure. Gravure (printing directly from cylinder to paper), gives a richer, smoother texture when printing flesh tones and makes the type look darker on the page than offset (indirect image transfer from plates). So if you want the type to look the same, you have to use two fonts. We developed two fonts for Playboy, but they kept complaining that the type was still coming out too dark or too light. Finally, I got a note attached to a proof that said, “Sorry. It was me. I needed new glasses. Thanks for all your help. Hef.” That was Hugh Hefner, of course.

Or speaking about his office:

From Oakland, Calif., to Delft, Holland, all the designers work from home. I have never been to the office. The first time I saw it was when I watched the documentary “Helvetica,” which showed our offices.

The strange allure of making your own fonts – Jason Fagone describes FontStruct, a web-based font design tool from FontShop:

FontStruct’s interface couldn’t be more intuitive. The central metaphor is a sheet of paper. You draw letters on the “sheet” using a set of standard paint tools (pencil, line, box, eraser) and a library of what FontStruct calls “bricks” (squares, circles, half-circles, crescents, triangles, stars). If you keep at it and complete an entire alphabet, FontStruct will package your letters into a TrueType file that you can download and plunk into your PC’s font folder. And if you’re feeling generous, you can tell FontStruct to share your font with everybody else on the Internet under a Creative Commons license. Every font has its own comment page, which tends to fill with praise, practical advice, or just general expressions of devotion to FontStruct.

Though I think my favorite bit might be this one:

But the vast majority of FontStruct users aren’t professional designers, just enthusiastic font geeks.

I know that because I’m one of them. FontStruct brings back a ton of memories; in college, I used to run my own free-font site called Alphabet Soup, where I uploaded cheapie fonts I made with a pirated version of a $300 program called Fontographer. Even today, when I self-Google, I mostly come up with links to my old, crappy fonts. (My secret fear is that no matter what I do as a reporter, the Monko family of fonts will remain my most durable legacy.)

The proliferation of bad typefaces: the true cost of software piracy.