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Reinventing the Automobile* is a book that lays out a vision for a progressive evolution of urban mobility transition that offers a robust point-to-point on-demand mobility network of 2-passenger fully electric vehicles. These vehicles would take up less parking space because not only are they small, but one proposed design folds up when parked. And they’d be able to tell you where the nearest parking spot is as you’re approaching your destination. Being fully electric they require a plug….or do they? The authors suggest that after an initial period of individual owners plugging these babies into outlets in their garages overnight, folks in city planning departments or franchise owners would trust the technology and economics enough to start installing wireless charging devices available curbside or in the road bed itself. Stuck in a bottleneck at a bridge or tunnel entrance? At least charging pads in the roadway can ensure that your 2-seater won’t run out of juice before you get where you’re trying to go. You can sit there and it will charge itself with embedded charging device in the road surface while plodding through gridlock. Even farther down the timeline, the cars might be able to drive themselves. So you can sleep through the gridlock or make calls or surf the ‘net. Just don’t post facebook status updates about your traffic problems. Nobody cares.

What I like most about the book as an object of intellectual design is that even if readers decide to skip all the words and they only look at the images, charts, maps, and diagrams, they won’t miss much. This book is stuffed with great graphics. I haven’t included them all as that would constitute copyright infringement and be too long for a single post. What you see below is just a small sample from Chapter 9: Personal Mobility in an Urbanizing World.

Daily driving in Paris

What works

This graphic is both elegant and deep. (Or it would be elegant if I had a better scanner.) It’s a simple form – Paris as concentric circles – but the more you look at it the more you learn. Rewarding that way. What sometimes happens in elegant graphics is that the details become obscured in iconography or approximations. But this graphic includes percentages as well as absolute numbers of two different kinds of trips – public transit and trips by cars. We see that Central Paris is defined as Arrondissements 1-20, the first ring is Seine Saint-Denis, Val-de-Marne, and Hauts-de-Seine, and the second ring is the rest of the Île-de-France region. There’s a summary of all the trips over in the legend so that the graphic itself can just show you the break down of different kinds of trips.

What needs work

In terms of transit, things like rivers often represent real barriers. There are only so many bridges and tunnels which creates a bottleneck effect. Paris is a city on a river so the one thing the elegance of this graphic obscures is the impact of the natural geography on transit choices. Maybe it’s not important when it comes to the cars vs. transit question, but bottlenecks are critical factors when it comes to planning mobility and I’m curious about whether bottlenecks push more people to transit or cars. In Boston/Cambridge, MA only one bridge has a train running across it and I have always assumed that pushed more people into their cars because many of them would have to go out of their way if they took the train and could only go over that one bridge.

Parking in Albuquerque

What Works

What you are seeing here is a simplified map of downtown Albuquerque, New Mexico. The white areas are buildings. The teal areas are parking – darker teal represents multi-story parking structures while the lighter teal shows us where surface lots can be found. Lovely way to show this information. One could imagine the same sort of information as a percentage-of-land-use pie chart or some far less granular collection of numbers. This schematic doesn’t bother to calculate just how many square feet of land are dedicated to parking. Nope. This is the visual equivalent of the ‘show don’t tell’ rule that writing professors are always encouraging their students to adopt when constructing essays. A table with land use percentages would be telling. This graphic is showing.

Albuquerque is like a parking lot with some buildings in it.

What needs work

I have never been to Albuquerque but I’m guessing that if you lived in Albuquerque you might like to see some sort of orienting label. Even just a single recognizable street name thrown in their somewhere to help orient. Now, the point of Reinventing the Automobile is not to provide urban planning for Albuquerque so I know they aren’t all that concerned with just precisely which neighborhood in Albuquerque this schematic represents. Still. It’s almost too cleaned up to read as a city plan right away.

Vehicle-to-Vehicle Crashes

What works

This graph does a great job of providing us with granular data and indicating a couple different trends visual. Keep in mind that they have multiple layers collapsed into a single graphic. It looks easy once it’s done but when one is faced with a pile of related numbers along multi-dimensions it isn’t always clear how to relate them to one another visually.

This graph has three levels of accident severity – minor, serious, fatal. It also shows the probability of injury. It also factors in variation in speed (which it does by creating five speed ranges). And then there’s the belted vs. unbelted division. That is a total of four different dimensions all displayed on one graph with a single measure on the y-axis. Color is used well. Grid lines are all that separates minor from serious from fatal accidents which are more or less three different graphs lined up next to one another.

References

Mitchell, William; Boroni-Bird, Christopher; and Burns, Lawrence. (2010) Reinventing the Automobile: Personal Urban Mobility for the 21st Century Cambridge, MA: MIT Press.

* The book specifically credits Ryan Chin, Chih-Chao Chuang, William Lark, Jr., Dimitris Papanikolaou, and Ruifeng Tian with “Illustration Production”.

What works

This visually arresting graphic does a great job of presenting data about national spending in an apolitical but altogether fascinating way. It’s interactive, by the way, but I’m not commenting on the interactive part, just the static graphic. I find that getting the static graphic clear is an important first step towards making a functional interactive graphic. If ever I hear someone say ‘but it’s interactive’ as an excuse for having a weak static graphic, I cringe. See my post about the USDA mypyramid food guide for a case study on the importance of a strong relationship between the static and interactive iterations of graphics as tools.

Each dot represents a different department or governmental program with the size corresponding to the funding level. Smart.

If you link through to the originating site, you’ll be able to follow blog posts that take readers through the development of the graphic. They ask for input and do their best to incorporate it. I like that approach. Good use of technology, OKF.

What needs work

I can’t quite tell why the circles are arranged the way they are or why their hues are the shades they are. Graphics, especially the beautiful ones, are the best when their simple clarity gives way to an elegant complexity. In other words, when I pose the question: “why does the hue vary within given funding types?” I’d like the graphic to lead me to an answer. I’m sure there is a reason for each hue, I just haven’t been able to figure it out.

One tiny, American-centric request: Add ‘UK’ to the page or the graphic somewhere. Maybe change “Total spending” to “Total UK spending”. Or “Where does my money go?” could be “Where do UK taxes go?”. These here interwebs are global. Yes, of course, the £ symbol tends to give it away. Maybe I’m just being too picky.

References

Open Knowledge Foundation. (2009) “Where does my money go?” United Kingdom. Data available

What works

Oversimplification makes this a surprisingly legible collection of tiny dots.

What needs work

I have no idea how to trust this graphic. The labels seem arbitrarily applied – that could just as easily be food blogs, design blogs, and gossip blogs. Or maybe if you left the labels blank it could be a Web 2.0 Rorschach test.

The article is built around these key findings:
+ “The Web sites of legacy media firms are the strongest performers. The top 10 mainstream media sites, led by nytimes.com, washingtonpost.com, and BBC.com, account for 10.9 percent of all dynamic links.”

+ “By contrast, the top 10 blogs account for only 3.2 percent of dynamic outlinks.”

In other words, old media (still) rules. Not exactly sure why, if those two points are the primary arguments, the story ran with a graphic about politics and tech blogs dominating the blogosphere.

[As far as I can tell, the author agrees with me that it’s not even all that interesting to talk about why politics and technology dominate the blogosphere. Tech geeks are comfortable in cyberspace (they may even prefer it). So that’s a no-brainer. Blogs are perfectly designed to facilitate the dissemination of opinions what with the casual tone and the comment features. Politics is heavily rationalized opinion. Thus: blogs + politics = eureka.]

I would love to see someone write about the relationship between recipe trading and the development of the internet. THOSE are the blogs that are inexplicably everywhere. And the early users of the internet were happy to use primitive bulletin boards for trading recipes.

Bottom line

Just because it’s pretty doesn’t mean it’s relevant.

References

Kelly, John. (2009) “Mapping the Blogosphere: Offering a Guide to Journalism’s Future” The Nieman Reports. Nieman Foundation for Journalism at Harvard University.

What works

I like the inset map. Architects often include a small site map in the main exterior section of a new building to help the viewer understand where the building is in relation to the rest of the world. News programs often start out international stories with maps. I love that this line graph comes with an orienting map. I might have included just a shadow of some neighboring states simply because many Americans have only a fuzzy idea of where Wisconsin is. Sad but true.

The lines show a great deal of information, some of which is not addressed in the article. Quoting the main thrust of the article:
“Here in Dane County, Wis., which includes Madison, the implausible has happened: the rate of infant deaths among blacks plummeted between the 1990s and the current decade, from an average of 19 deaths per thousand births to, in recent years, fewer than 5. The steep decline, reaching parity with whites, is particularly intriguing, experts say, because obstetrical services for low-income women in the county have not changed that much.”

Then it goes on to quote a local doctor and professor: ““This kind of dramatic elimination of the black-white gap in a short period has never been seen,” Dr. Philip M. Farrell, professor of pediatrics and former dean of the University of Wisconsin School of Medicine and Public Health, said of the progress in Dane County. “We don’t have a medical model to explain it,” Dr. Farrell added, explaining that no significant changes had occurred in the extent of prenatal care or in medical technology.””

The graph suggests an explanation that the article (and the doctor) may not have considered. Presenting information visually is about more than presentation; rearranging data to reveal patterns is a research tool in itself.

What needs work

This is a critique of the article, based on the line graph: isn’t it possible that the at-risk folks in Dane County ended up moving to Racine for some reason? Right at the time the infant mortality rate in Dane was plummeting, the rate in Racine was spiking. From the line graph it seems that this happened in the vicinity of Clinton era welfare reform. Maybe there were some reasons for the most at-risk folks to get out of Dane and into Racine at this time.

If there is no medical explanation, let’s have a look at other possible explanations.

References

Eckholm, Eric. (2009, November 26) Trying to Explain a Drop in Infant Mortality The New York Times US Section, reporting from Madison, WI.

These graphics accompanied a great article about water shortages in episode of The Economist which arrived last week. The article was well written and comprehensive, handily summing up the way water resources are related to the growth of urban centers, climate change, the rising affluence of the world’s poorest people (and their conversion from vegetarianism to omnivorousness) and the question of whether or not fresh water is a global or a local problem. I highly recommend reading it. Unfortunately, I think you would do almost as well reading it without the accompanying graphics as with them.

The first one is so confusing I still don’t know what I am seeing here. Table data usually has the attribute that the longer you look at it, the more you get, with an occasionally painfully long initialization period in which you can’t make out any pattern whatsoever. I spent a good bit of time on this one and I still don’t know how to make sense of it. The article rightly points out that fresh water is unevenly distributed across the globe–some places have a lot, some places hardly have any. No big surprise. Also not surprising: some continents use more fresh water than others based on overall population size and agricultural production practices. So when I looked at this graphic, I was kind of hoping to get a sense of both how efficient each continent was with their resources and how dire their straits were. The graphic sort of does that. Sort of. We’ve got a measure of total renewable water resources but it doesn’t take into account total land area. It does take into account population, sort of, and maybe population is more relevant than total land area in this case.

The second graphic does not stand well on it’s own. I can see here that it appears that these selected countries seem to have been becoming more efficient with their water use. Since 1995, all of these countries have lowered the number of cubic metres of water used per dollar (or dollar equivalent) of GDP. This graphic does nothing on its own to help me understand why that might be true. Have these countries moved out of water intensive agricultural production? Have they made their agricultural production more efficient? If so, is it technological change leading to increased efficiency or did they just shift to more efficient crops? Or maybe the change is in the GDP variable, not the water variable. The graphic really just doesn’t clear any of these things up.

What Works

I like the third graphic. It’s clear and adds to the text in the article. This isn’t the first time I have read about water shortages and one of the biggest and possibly easiest changes we could make to prevent the water shortage from becoming any more of a problem than it already is, would be to introduce drip irrigation in places that do not already have it. Yes, it costs some money. But it is far more cost effective than many of the other strategies introduced to combat climate change. Drip irrigation technology is not overly complex nor does it require extensive training or equipment to install. Tubing perforated along its length with small holes, buried under the surface of the earth, delivers water directly to plant roots. Much less water is lost to evaporation or seepage into non-crop areas. Control over water resources is better – during rains cisterns collect and store water for later distribution through the drip tubing during dry periods.

Relevant Resources

The Economist. (2009, 8 April) Water shortages go global: Sin aqua non. Istanbul.

Necessary Background

This visualization is going to take a bit of explaining. Mapping the internet is a question that has intrigued folks who are worried about internet security, the digital divide, robustness, even artists who just wonder about all those bits of information flowing around us.

This visualization attempts to describe the structure of the internet as a network, not to map its black holes, censorship holes or describe actual geographic nodes like Akamai in yesterday’s post. This is a different sort of map and it requires some background reading. The authors set up a strategy for exploring the network terrain of the internet that generated these three areas – the central nucleus area consisting of the most highly connected nodes, a fringe around the edges of a whole bunch of pages that would be cut off completely if the nucleus were removed, and then a sort of spongy area in between these extremes full of nodes that could connect to each other if the nucleus were removed but not nearly as efficiently. Call it the peer-to-peer zone.

Here’s how the authors described the process that generated the three classes of nodes:

First, we decompose the network into its k-shells. We start by removing all nodes with one connection only (with their links), until no more such nodes remain, and assign them to the 1-shell. In the same manner, we recursively remove all nodes with degree 2 (or less), creating the 2-shell. We continue, increasing k until all nodes in the graph have been assigned to one of the shells. We name the highest shell index k max. The k-core is defined as the union of all shells with indices larger or equal to k. The k-crust is defined as the union of all shells with indices smaller or equal to k.

Even if you don’t spend your days dividing networks into k-shells, I hope you now understand that this model’s strength comes from the fact that the structure was generated rather than imposed by initial assumptions. There were no initial assumptions.

What Works

Success here is that people who do not study networks can understand what these researchers did at all. Most highly specialized research (and pretty much all research is highly specialized) only makes sense to the people occupying the sub-sub-discipline actively working on those questions, equipped with the right language, fully immersed in the discourse of the niche. That would have been true if I had just tried to read this article without the accompanying image.

I also think it helps immensely to see the sketchy, comparatively unglossy schematic along with the polished final image. The glossy version adds in enough detail that I might have missed the big picture without having the schematic there to remind me that it isn’t about color or distance – that the contribution is all about the three types and their relationship to one another.

What Needs Work

Similar problem with this image as I had with yesterday’s image: the final image is so glossy and sealed that I feel like it’s hiding something. The more gloss on an image, the more it becomes impenetrable to critique. It presents itself as hermetically sealed – how can anyone get under the skin and assure themselves that this is a trustworthy image? This glossiness of the final image is probably why the schematic has so much appeal. It’s easier to see how the two were put together and *why* it is the way it is.

Aesthetically, I am not sure I like the colors and I think I would have tried to achieve the look of a solid core, a very fringe-y outer layer that has more volume but is almost insubstantial in its lacy-ness, and then a middle layer that sort of looks like a network made of jello. It is so easy to say these things when you don’t have to kill yourself in photoshop and illustrator making them happen.

Note

[There is another post on Graphic Sociology about mapping the internet about visualizing the map of an individual site which is here.]

Relevant Resources

Carmi, Shai; Havlin, Shlomo; Kirkpatrick, Scott; Shavitt, Yuval; and Shir, Eran. (2007) “A model of Internet topology using k-shell decomposition” Proceedings of the National Academy of Sciences of the United States of America.

Moskowitz, Clara. (11 April 2008) Black Holes Charted on the Internet. msnbc.com, Technology and Science.

Reporters Without Borders (2007) Internet Black Holes.

Wachowski brothers (directors, writers) The Matrix.

Internet Traffic

This week we’re going to have a look at the internet. Here are two reasons why:

• 1. The not entirely superficial reason is that there are many great visualizations out there dealing with the internet, internet traffic, internet usage patterns, and so on. Many are interactive so you can play around with them yourselves.
• 2. The larger theoretical question about studying the internet and online behavior goes something like this: How much is people’s online behavior reflective of their offline behavior? Are people role-playing when they’re online, trying out personas they may not fully embrace offline (see Sherry Turkle)? Or is online behavior seamlessly integrated with offline behavior? We IM the people we’re about to have dinner with indicating that the people we talk to online are just about the exact same people we talk to offline? And if the relationship between online and offline behavior is somewhere between these two, how can we figure out just what is going on?

What Works

The graphic above is just a screen capture from Akamai’s site. In order to get the full impact, you have to click through and play around with it. Akamai has a slew of other visualizations you can play with that deal with network attacks, latency/network failure, retail data, news traffic, and so on.

Just to be clear, Akamai is a private company providing web-optimization services. In their shareholders’ quick facts, they say they serve up 10-20% of global internet traffic. What does this mean? It’s easy to forget that the internet requires physical structures, but this is part of what Akamai does. They maintain “40,000 servers in 70 countries within nearly 950 networks” all over the world slurping up electricity and information at about equal rates. The reason they do this is because if you are, say, a blogger in New York and you store your files on a server just down the hall (which is unlikely, but play along), if someone in Singapore wants to read your blog, the request is going to have to come all the way from Singapore to the server down the hall from you in New York and then the files will have to be sent all the way back to Singapore. This takes time, there might be network congestion along the way and if you are serving your readers in Singapore something a bit more bandwidth intensive than text (say a little clip of a new car racing around a track or a high quality music download) the person in Singapore may just lose interest before they even get the whole file. Akamai gets around this in part by duplicating files and storing them on servers all over. So if your reader in Singapore wants to access your site and you’re an Akamai customer, they will end up pulling those files from a server much closer to them, maybe in Singapore, but at least somewhere much closer than New York. Akamai’s clients tend to be Fortune 500 companies with global client bases and companies that rely on being able to transfer heavy files reliably and quickly (like music and software downloads). They do more than just the physical infrastructure, they mobilize their resources to detect net attacks, congestion, and then to re-route and avoid those things. The bottom line for us is that they make some of their knowledge of the ‘net available in these visualizations like the one above.

What Needs Work

I would love to have more granularity and access to the actual numbers and the methodology. All these shiny interactive graphical toys run the risk of being too glossy, not data-transparent enough.

Not as Shiny, Quite Helpful

These two graphs give a quick overview of who is using the internet by geographical location. You’ll see that rates of traffic can be a bit misleading – not all continents have the same population. That’s why I included the rate of internet penetration within the continents. A low rate of penetration tells you a lot about how the digital divide which is a very real problem. More on that later this week when we will address the digital divide directly. For now, it’s enough just to notice the difference in looking at the flashy, glossy Akamai graphic and the simple bar graphs. I don’t know about you, but I quite enjoyed playing with the Akamai graphic and encourage interactivity. Still, the combination of these two bar graphs above gave me a clearer answer to the big question about who in the world has access to the internet in the first place.

Relevant Resources

Akamai – Data Visualizations

The Berkman Center for Internet and Society at Harvard University School of Law.

Deibert, Ronald, Palfrey, John; Rohozinsky, Rafal; and Zittrain, Jonathan (2008) Access Denied: The Practice and Policy of Global Internet Filtering Cambridge, MIT Press.

Internet World Stats

Turkle, Sherry. (1984) The Second Self: Computers and the Human Spirit Cambridge, MIT Press.

Book Recommendation

Donald Norman’s “The Design of Everyday Things” is currently my commuting book which I’ve had ample opportunity to read because the F train here in NYC is the most capricious multi-ton object I’ve ever encountered. This is a good book if you want a straightforward introduction to basic design principles. Norman is an engineer by training which means he comes from a different tradition than, say, an architect. He goes through all sorts of examples of commonly encountered objects – keyboards, sinks, ovens, telephones – to help demonstrate that good design would benefit from prototyping and user-testing because, in the end, humans are fairly adept at taking clues about how to use an object from their first glance. When things aren’t obvious, it’s the fault of the design, not the fault of the person who has trouble figuring out how to put someone on hold or transfer a call with a phone system that can likely ONLY be used by a robot or an algorithm. He opposes beautiful design for the sake of beauty – glass doors stripped of plates and hand bars in service to the sleek glossiness of glass’s amazing material properties are no good if people end up pushing on the hinged side of the door when they should be pulling on its swinging side.

Norman offers users a set of criteria by which everyday design can be critiqued as well as some rules of thumb for figuring out particularly obtuse design challenges. He absolves humans their occasional mechanical buffoonery, “Humans, I discovered, do not always behave clumsily. Humans do not always err. But they do when the things they use are badly conceived and designed.” Norman doesn’t go so far as to suggest that the objects themselves possess agency, it’s not the fault of the things, but of the people who designed them, “When you have trouble with things…it’s not your fault. Don’t blame yourself; blame the designer. It’s the fault of the technology, or more precisely, of the design.” This part of his theory is the weakest. It’s rather simplistic to blame the designers without interrogating why they produce shoddy designs. He hints that designing for the sake of beauty is part of the problem and that user testing happens in the market place where negative reactions are likely to kill the product line altogether rather than resulting in intelligent, sensitive redesign. Luckily, other books (Harvey Molotch’s “Where Stuff Comes From” for example) do a better job of revealing the motivations and constraints on designers.

Where Norman is at his best is in the many detailed examples of everyday objects gone screwy with clear, diagramatic prescriptions for improvement. Norman never rants about bad design just to sharpen his teeth. His examples are accompanied by constructive suggestions that are so clearly spelled out that readers are capable of critiquing his suggestions, a sure sign that the book succeeds as a teaching tool. Furthermore, Norman illustrates his discussion with photos, sketches and diagrams throughout which enriches the legibility of the project and subtly introduces readers to the practice of learning through drawing that is common in design practice, but not all that common outside of it.

Relevant Resources

Norman, Donald A. (1998) “The Design of Everday Things” Cambridge, MA: MIT Press.

Molotch, Harvey. (2003) Where Stuff Comes From: How Toasters, Toilets, Cars, Computers and Many Other Things Come to Be As They Are. New York: Routledge.