maps

What Works

First, the elegant sophistication of this graphic is breathtaking. I love watching it and I have watched it for long enough to start asking questions about it. Maybe I am different than other people, an outlier of some sort, but in this case I don’t think so and that’s why my own fascination indicates a larger virtue of the graphic. If it draws people in and gets them asking questions, it is doing something right. Holding eyeballs in this media saturated world is a triumph in itself. Having answers to the questions that are posed is a secondary but even more critical step. To figure out what you’re looking at, here’s what the folks who made it have to say for themselves: “Cabspotting traces San Francisco’s taxi cabs as they travel throughout the Bay Area. The patterns traced by each cab create a living and always-changing map of city life. This map hints at economic, social, and cultural trends that are otherwise invisible. The Exploratorium has invited artists and researchers to use this information to reveal these “Invisible Dynamics.” The core of this project is the Cab Tracker. The Tracker averages the last four hours of cab routes into a ghostly image, and then draws the routes of ten in-progress cab rides over it.”

Second, they are right that just knowing where cabs go is more than knowing where cabs go. It’s knowing about urban space over time. It’s certainly knowing where the airport is (and that airports are far away). Looking at this we get to see the grid of the city and the longer stretch of highways and bridges bringing people in/out. It would be nice to see what this sort of ghostly cab mapping technique would reveal about cities I know a little better than San Francisco. Keep this site tucked in your back pocket for later this year, all you ASA meeting-goers.

What Needs Work

I just wish there were a simple way to say a little more about the cabbies themselves, who end up looking like infrastructure or phantoms, rather than actual people. In New York, 91% of the cab drivers are immigrants and only 1% are women (2006 Schaller Consulting). Is there a way that this cab-tracker could become a little more about the humans in the city?

Relevant Resources

Richards, P. and Schwartzenberg S. Snibbe S. and Balkin A. cabspotting San Francisco.

Schaller Consulting. Repository of Reports on Cabs in New York and beyond

Plaut, M. (2007) Hack: How I Stopped Worrying About What to do with my life and started driving a yellow cab. New York: Random House.

Buddhacab blog written by a New York yellow cab driver

Link rot note

This post used to source a population growth animation from zachofalltrades.net but that website is no more. The University of Kentucky Appalachian Center is better, so count yourselves lucky if you missed the original post in favor of this update.

What Works

First, you must click through and watch the animation. Praise #1: yay for gifs.

Like the previous post that looked at China, this animation is trying to tell a story about population growth over time. The major difference is that the Chinese example was strictly demographic – looking at variables like gender and age but not at all concerned with geography. This one shows both geography and population growth though it does not include information about gender, age, race, etc.

What Needs Work

If this graphic were three dimensional, if density piled up, it would start to ‘feel’ heavier over time so that the same way that the westward expansion of the population just appears without you having to puzzle it out, the density of population in cities would be simply obvious. This is not meant to be a dig to the graphic’s creator. I just offer this critique as a way to think about just why and how ‘seeing is believing’. Watching the population move west is certainly a ‘seeing is believing’ moment because viewers do not have to think, they just have to watch. Realizing that the population of the US is now hugely larger than it was back in the 1880’s actually takes a little thought. You have to realize that not only did people move west, but they continued to live in the east in greater densities which is indicated by the size of the yellow circles, but would be even more obvious if the cities were like little hillocks on the landscape. Big yellow dots equaling density requires a move from the ‘seeing is believing’ to something else. If, however, the map grew in the third dimension as a more direct representation of the mass of humanity sitting on the face of the earth at these locations, we’d be back in ‘seeing is believing’ territory.

A graphic that is a ‘seeing is believing’ creation is instantly legible and can free your brain to think about other things which is a good thing. On the other hand, a graphic that achieves a ‘seeing is believing’ mechanism will end up obscuring complexity. This is good when that complexity does not add to the ability to think through the next set of concerns, but can be a serious drawback. It is good to be able to get a diversity of people able to quickly grasp an argument, but there is a danger in presenting an hermetically sealed glossy image.

Relevant Resources

University of Kentucky Appalachian Center. US Population Growth from 1790-1990

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.

The Story From Across the Pond

There are so many stories that get played out on the legal stage and the stakes are highest when death is involved. I found two graphics each of which attempted to provided an overview of the death penalty in America. We start with the view from London (though the writer of the article was in New York while he was writing).

The graphic they’ve come up with over at The Independent does a great job of summarizing the story of the death penalty in the US. The best part of this graphic is the right-most graph showing that the states with the death penalty started with lower murder rates and *still* have lower murder rates than those states that have the death penalty. Murder rates in both types of states change over time, but those changes seem to be largely independent of the death penalty. Great way to show that the death penalty does not make a good deterrent.

One last notable point from this article is that the graphic seems to do a better job at representing “just the facts” than the text. From the other side of the pond, the continued use of the death penalty in the US looks, well, barbaric beyond anachronism.

From Usborne writing in The Independent: “China tops the world’s executions league table (officially it used the death penalty 470 times last year, though Amnesty International believes the true figure is far higher), followed by Iran and Saudi Arabia. Among developed industrialised nations, only the US, Japan and South Korea persist in retaining capital punishment. None of the United States’ European allies entertain it nor do its neighbours, Mexico and Canada.”

In case you aren’t accustomed to decoding dry British writing, it is most certainly not a good thing to fall into the same category as China or Iran when it comes to human rights.

The Story from the Backyard

Not to be outdone, the New York Times has also run a number of graphics about the death penalty which is a recurrent topic of popular and academic debate.

Here’s where the difference between the US depiction and the UK depiction starts to stand out. The UK added up all the executions since 1976 which tends to imply a great magnitude of death. There’s a big red 409 over Texas in their graphic and ‘just’ 20 in the NYTimes graphic, because the Times took a statistician’s more favored approach of looking at the number of death sentences per 1,000 murder convictions. This makes it easier to compare state by state data because it acts as a control for population size and murder rate. In this version, Oklahoma, Nevada, and Idaho appear to be more invested in the death penalty than Texas. Don’t mess with Texas becomes don’t mess with Nevada. (I guess what happens in Vegas really does stay in Vegas…but not in a good way).

The NYTimes graphic also looks at the sentencing rates when the race of the victims and perpetrators are the same and when they’re different. The way they’ve simply represented the facts speaks clearly to the continued machinations of racism in America. When whites are the victims, the perpetrators are more likely to be sentenced to death, especially if those perpetrators are black. Look at that part of the chart for a while then think about why the writer from The Independent has such strong negative feelings about America’s death penalty.

The Story from the US – 2003

This post is not about how the general population in America feels about the death penalty – check out some of the death penalty blogs listed below for more on public opinion. I was beguiled by this next graphic because it so simply illustrated ambivalence which is not all that easy. Each block is a case, every case has to have only one outcome with respect to death sentencing, and the designer manipulated this binary to produce a picture of declining conviction. Bravo.

The article’s text offered about five competing reasons for the decline in the rate of death sentences applied, including poor representation. They ended with this one:

“Alan Vinegrad, a former United States attorney in Brooklyn, said the recent statistics represented something larger.

”It reflects that the tide is turning in this country with regard to attitudes about the death penalty,” Mr. Vinegrad said. ”There has been so much publicity about wrongfully convicted defendants on death row that people sitting on juries are reluctant to impose the ultimate sanction.” ”

Relevant Resources

About.com’s list of the Top Ten Death Penalty Blogs. Most are not big on graphics or visuals of any kind.

Amnesty International’s Human Rights Now blog which hosts their posts on the death penalty.

The Death Penalty Information Center

Liptak, Adam. (18 November 2007) Does the Death Penalty Deter Murders? in The New York Times. National Section.
–Including this, ““You have two parallel universes — economists and others,” said Franklin E. Zimring, a law professor at the University of California, Berkeley, and the author of “The Contradictions of American Capital Punishment.” Responding to the new studies, he said, “is like learning to waltz with a cloud.””

Liptak, Adam. (15 June 2003) Juries Reject Death Penalty in Nearly All Federal Trials. National Section.

Usborne, David. (7 August 2008) Why is the United States still imposing the death penalty? in The Independent.

What Works

This map uses a two color pie chart scheme to represent increases and decreases in violent crime respectively. It also breaks the pie into pieces for added granularity of detail – one for murder, one for forcible rape, one for armed robbery, one for aggravated assault. (also known as mincemeat pie, right?)

What Needs Work

I still think there’s got to be a better way to represent gains and losses on a spectrum. Changing from one color pie to another at zero is a little arbitrary. Three dimensions might help – states with increases in crime could bulge while states with decreases could sink.

I included this graph not so much as a particularly good or bad example of building an info graphic but as a contrast to the previous post. This is a typical depiction of crime mapping. It depicts violent crime by victimization. Most crime coverage focuses on this salacious category – rapes and murders and beatings.

Relevant Resources

Ford, Steve. (2006) Map of Violent Crime in the USA 1978-1998

What Works

The beauty of these graphics is that, given their captions, they are instantly legible. On the left, the map shows where crimes are committed in 1998. It’s a diffuse pattern with a few warm spots. On the right, the map shows where the imprisoned population calls home (2003 data). It’s an image with vivid hot spots amidst a sea that’s mostly dark. In thirty seconds or less, viewers can see that while crimes are committed all over Brooklyn, the population in prison tends to come from a handful of very localized neighborhoods. It would have been easy, and easy on the eyes, to use two different colors for the different maps, but because this idea works as a comparison, it’s important to keep the color scale the same across both images.

These maps are used as tools of analysis and pattern recognition, helping to make data legible both for the public and for the researchers who use these tools not only as tools for publication but also as tools of analysis. They go further, augmenting these maps with finer grained maps as you’ll see if you keep reading.

What Needs Work

A stronger outline of Manhattan would help non-New Yorkers recognize the location immediately.

More Than Critique

This post reminds us that there are many victims of crime. The authors’/graphic designers write, “If crime maps succeeded dramatically in mobilizing public opinion, redefining the city as a mosaic of safe and unsafe spaces, and forcing the reallocation and targeting of police resources on specific neighborhoods, the gains were short-lived. The resulting crime prevention techniques, and the community-policing movement in general, soon reached the inevitable limits of any purely tactical approach. The city spaces that were targeted came safer, but too often crime incidents were simply displaced to other locations.”

Nobody is denying that being mugged or raped or murdered is fun for the person who was mugged or raped or robbed or murdered. But the report by the Spatial Design Lab at Columbia University sponsored by The Architectural League that uses maps as a tool of analysis and discovery to suggest that because perpetrators live in areas with lots of other perpetrators, those entire communities are also the victims, not of the crimes per se, but of the impact of high concentrations of recurrent incarceration. Convicted people go away to prison leaving these neighborhoods with a gender imbalance (only 12% of the prison population is female). The money spent to imprison this largely male population is not being invested in developing these communities. This study finds a block where $4.4m has been spent to imprison its one-time residents. One block, $4.4m.

The authors pose the question their maps have helped make obvious: “What if we sought to undo this shift, to refocus public spending on community infrastructures that are the real foundation of everyday safety, rather than criminal justice institutes of prison migration?”

Relevant Resources

Spatial Information Design Lab at Columbia University (2006) Architecture and Justice sponsored by The Architectural League.

Spatial Information Design Lab Main Page

The Architectural League

What Works

The first map was produced by the USDAs Economic Research Service in 2004 to show the change in milk production by US region from 1980 – 2003. The accompanying text is surprisingly brief, “Since 1980, milk production in the U.S. has increased almost 33 percent. Regional production growth has been most pronounced in the Pacific and Mountain regions, the result of development of low-cost systems of milk production in the Pacific region and some Mountain States. Growth has been much slower in the Northeast and Southern Plains, and the other six regions have seen essentially flat or declining production.”

The graphic is a fairly straightforward way to combine a map with a bar graph. I like it better than if it were just a bar graph with regional labels, but I would like it even more if it were better integrated so that the data from the graphs were embedded in the map, maybe by showing the change in production by color or by applying concavity/convexity to the map.

What Needs Work

There is a serious drawback to the map + graph combination. One of the problem with images is that they tend to appear as sealed, complete narratives that are telling the whole story. It’s hard to interrogate an image, harder than interrogating a text. We’re taught not to believe everything we read, but those strategies don’t translate directly into the world of images. The important missing information here is that the population in the US is shifting to the south and west out of the north east. The image doesn’t suggest causal links; but the text does. However, it leaves out the no-brainer that since milk is a localized commodity, population growth is generally going to result in increased milk production in that area.

Bonus Image

I found this image depicting population density and population change in the US. Cool colors indicate a loss of population; warm ones suggest growth. The z-axis represents human volume. A solid graphic. I have looked and looked and been unable to find the original source which just goes to show that once information hits the digital domain it really does have a life of its own. Hackers were right about that, information wants to be free.

Relevant Resources

Blayney, Donald. (2004) Milk production shifts West USDA Economic Research Center.

Dupuis, E. Melanie. (2002) Nature’s Perfect Food: How Milk Became America’s Drink. New York: NYU Press.

Mendelson, Anne. (2008) Milk: The Surprising Story of Milk Through the Ages. Knopf.

USA Today Flash Animated Graphic accompanying the headline “Deaths Down on America’s Roads”

What Works

Nothing is working here and I’m not just saying that because it’s flash and I can’t repost it. Please link through for a hot minute and look at it anyways.

What Needs Work

My problem with this graphic is that it is ONLY a map of the US, except for the few seconds when you roll your mouse over it. Even then, you don’t end up seeing a pattern, you just see little pop up windows with some numbers in them. Information graphics need to artfully, intelligently, dare I say cleverly weave the information into the graphic so that the two become greater than the sum of their parts. None of that happens here.

The map of the US is still just a map of the US. No shading, no numbers, no way to tell that we’re talking about traffic deaths. Even just mapping out the interstate highway system would have given a hint of a visual clue to tell us what we’re talking about. In the previous post, Snow stacked bars to indicate dead bodies. Maybe it’s a little over the top, but if we are addressing the notion of a change in body count, I would like to see some visual representation either of bodies or of change (change is more abstract and probably more appropriate for USA Today than a visual representation of a body count). Furthermore, I want to know if there really is a relationship between gas prices and body counts which *could* be explored looking across states. States tax gas at different rates resulting in variations from one state to the next. Sensitively factor in income and unemployment and we might be able to get a sense of how much gas prices impact mortality on the roads. Even more interesting would be whether it’s the fact that people aren’t on the road at all that prevents them from dying out there (no gas = no go) or if it is somewhat more subtle – perhaps people drive slower to be more fuel efficient rather than staying home and it is the slow down, not the no-go that keeps people alive. The more likely scenario would also point out that cars continue to get safer and that seatbelt laws work. If we could look at the data over time, we’d have a better idea how more quickly traffic fatalities dropped in 2008 than in other recent years, which would help factor in the cars-are-safer-now + more-states-have-seatbelt-laws effects.

This graphic falls woefully short of even hinting at any of these questions. I wish they had left it out altogether, forcing everyone to read the article in full.

What Works

This is a combination of a map and a chart whose creation helped epidemiologists understand that cholera was not caused by a ‘miasma’ carried by the fog from the river, but rather was a germ carried in the water. It’s one of my personal favorite early examples of information graphics as a tool not of publication, but of analysis and discovery. Snow mapped the area around the Broad Street pump and then represented deaths with bars (not dots as some later cartographers have done when re-presenting Snow’s maps). The bars end up looking like stacked bodies, reinserting the gravity of the situation into the fairly sterile context of the map as info graphic.

The pattern is imperfect, but clear. Proximity to this well is directly proportional to mortality risk. The point of this entry it to encourage the use of information graphics not only in the publication stage of the research process, but also in the analysis stage. Granted, epidemiology isn’t a social science, but this is a classic example that sets the scene for contemporary examples of graphics as tools of analysis.

What Needs Work

There are other more comprehensive maps of the whole neighborhood that show the patterns even more clearly. What I have here is just a close up, probably a mistake on my part. The full version is here as a pdf. The romantic in me wanted to restrict this post to the original grainy, scanned map* drawn by Snow himself.

The realist in me notes that even though I believe the creation of information graphics can be used as analytic tools, the story in the John Snow case isn’t a perfect fit. An article by Brody et al in The Lancet points out that, “Snow developed and tested his hypothesis will before he drew his map. The map did not give rise to the insight, but rather it tended to confirm theories already held by the various investigators.” So Snow didn’t get his brilliant insight just by examining the map but he did use the map as an analytical tool later in the process to help confirm his hypothetical hunches. It wasn’t like he just threw the map/chart together to present at a conference or while he was writing up an article which is how I feel many social scientists end up using info graphics.

*This version is actually the second version though it’s main difference from the very first map is that the pump has moved just slightly off from the exact corner of Broad Street closer to the house of 18 deaths.

Relevant Resources

John Snow website at UCLA School of Public Health where I found many maps.

Brody, H., M. R. Pip, et al. <2000) “Map-making and myth-making in Broad street: The London Cholera epidemic, 1854.” The Lancet 356, (9223): p64-68.