I am a graphic designer who focuses on information design. My day job? I am the data visualisation manager for the Federal Reserve Bank of Philadelphia. (This blog is my something I do on my own time and does not represent the views of the Fed, blah blah blah legal stuff.) And with my main interest in information design—be it in the shape of clear charts, maps, diagrams, or wayfinding systems—I am fortunate that my day job focuses on data visualisation. Outside of work, I try to stay busy with personal design work. Away from the world of design, I enjoy cooking and reading and am interested in various subjects from history and geography to politics to science to the arts. And I allow all of them to influence my work.
Yesterday, the New York Times released this interactive piece to look at the popularity of particular candidates in that seemingly ubiquitous world of Twitter. Perhaps it was inevitable that the Times or somebody else would create something like this. Regardless, it is out there and I have to say, I am left confused.
No, not by the how it works. I understand that more activity makes for larger bubbles. (Although at this point I shall refrain from my usual diatribe on bubbles.) And if you click on a particular bubble/candidate, the vector and colour of the little bubbles describes the type of activity. Understand? Check.
But why are the bubbles placed where they are on the screen?
Perhaps the rationale is explained somewhere…but I have yet to find it. And after sitting down with a colleague yesterday, the two of us could not quite figure it out. Vaguely one gets the impression of representing actual geography—except for things like Delaware being in the bottom corner. Perhaps the bubbles’ centre points are randomly generated? They do not appear to be on separate loads of the Flash piece.
And so I am left with the thought that the bubbles are a needless distraction and, in fact, lead to greater confusion. What if, for example, the candidates were not bubbles but bars? The bars would create a visual rhythm as they grow and shrink and each could be clickable. One could sort the bars by some sort of a hierarchy: alphabetic, geographic, political, &c. You could even still click on a bar for more detailed views and perhaps do some other neat things.
This is another comparison of high-speed lines and how woefully inadequate American infrastructure is in this particular department. The graphic comes via the Chicago Tribune in support of this article, wherein the outgoing mayor states the need for a high-speed line to link downtown Chicago to O’Hare International Airport. Apparently his desire for such speedy transit was inspired by his trip to Shanghai, where the Chinese have had a magnetically-levitated (maglev) train connecting the airport to the city for a few years. It’s fast. (Though as the article makes a point to call out, the Shanghai train does not stop in downtown Shanghai, but rather the city’s edges where travelers then link up with a more conventional train to reach downtown.)
The chart is nice because it breaks down the types of trains into categories based upon speed, and in the area of interest, namely high-speed, the express section is broken out in detail with the several main types of high-speed trains described. Of course these are all maximum speeds and I would be curious to see a comparison of average operating speeds. For example, while Acela is billed as fast, it frequently operates well below maximum speeds because of its route—the Northeast Corridor was not designed for trains running at such high speeds all those years ago.
At the bottom is a comparison of the overall length of the Blue Line, the Chicago route that connects the Loop (downtown) to O’Hare, to the distance needed to accelerate and decelerate a high-speed train to its maximum speed. Overall, I think the plan sounds like a glossing over of other deficiencies in the Chicago mass transit network for the sake of shiny new toys for (outgoing) mayoral boys.
The United States was founded on the East Coast as English (and the odd Scottish) colonies with the old cities of Philadelphia, Boston, and New York. These first colonies became the original 13 states. Ever since the 18th century, we have expanded westward into the Ohio Territory, the Northwest Territory, French colonies, Spanish colonies turned Mexico, and then again the British in the Pacific Northwest. (Overly simplified history of the United States’ growth, but it shall do.)
Every ten years, the United States is constitutionally obligated to hold a census. You cannot elect representatives to make political decisions for you if you do not know how many of you there are and where you live. But what these decennial censuses show are how the demographics of the United States have changed, with the population shifting from the East Coast, once almost 100% of the population, to the lands south and west. It’s only natural when you consider how unpopulated that part of the continent is.
But, because we rely on these censuses to redraw political districts and boundaries, every ten years politicians make much ado about…well, something. This article by the New York Times looks at how these changes are set to affect the Midwest in particular and this graphic, while simple, charts the congressional power of the Midwest through the total number of seats held in Congress over the years.
This piece comes from my coworker, Ben, who found the graphic in Scientific American. Broadly speaking the piece is looking at the obese and the overweight in the United States, comparing the numbers of both children and adults in 1980 to 2008. These numbers are supplemented by the risk of death posed to both men and women from a few different causes. (I know at least diabetes is linked to weight, but as to whether the others are linked I am unaware.)
I have a few quibbles with the piece; for in general I think educating the public about the health risks of obesity a worthy endeavour. From a more scientific-ish point of view, as I recall, BMI (body mass index) is not a particularly useful tool in determining obesity because it fails to differentiate people who are heavy with fat from those who are heavy with muscles. A strong and regular weight-lifter is not necessarily overweight, but simply has a lot of muscles. Does that make the weight-lifter less healthy than those with lots of body fat? Methinks not.
From the data side, I am curious to know why only the two years? It may very well be that they are the only two years for which relevant data exists. But I doubt that. 1980 compared to 2008 is interesting, but perhaps already well-known. What would perhaps be more interesting is whether over the past few years, the increasing attention paid to weight and other health issues has begun to affect the growth of the obesity problem—poor pun very much intended.
The accompanying text makes a point about the number of adult Americans being obese. Certainly the dots as a percentage of the population achieve that goal of showing percents—though I hasten to add that their arrangement around the body in the centre does very little to aid in comparing the adults of 1980 to 2000 let alone the children. And as to the children, the article points out that they are growing fastest. At this, however, I can only take the authors at their word for the graphic does nothing to visualise this statement. Perhaps they outgrew the adults—but then the adults were themselves at one point children, but that is another matter—but their growth could now be slowing as a recent turn of events. But since we only have two years, we cannot know for certain.
The risk of death by [type of death] is interesting. But running bar charts as more of a radial chart could become a bit confusing. Is there any reason the bars grow in width as they extend further out? Or was that part of an all-too-obvious play on the problem. After all, the growth in area could be significant; a simple line of constant stroke to a point along the radial distance markers would have sufficed. And then I would be particularly curious to know whether any of these types of death are related to obesity. Neither the article nor the graphic provide any clues besides whatever knowledge the viewer brings to the table. (Okay, I think I am done with the puns.) And if one happens across the article with almost no knowledge of what diseases or medical conditions are caused by obesity, how does the graphic tie into the cost of healthcare costs brought upon the country by obesity.
Overall, I think the graphic is well-intentioned. The public is becoming more accustomed to seeing data visualised. However, we need to make certain that we are communicating clearly by making datapoints easier to compare. (Looking at things across half of a circle is a bit tricky.) And then we need to make certain that the data we are visualising supports our statements. (Are children really the fastest growing? Over what span of time?) And then take the time to explain to the audience those things that may not be common knowledge. Does that mean dumb a piece down to the lowest common denominator of someone who has absolutely no knowledge? No. Design needs to elevate and educate its audience. Perhaps some of the finer details remain unexplained because of sheer complexity, but when amidst a host of details well-understood, that confounding bit may push an unsure viewer to do some additional research and educate him- or herself about the subject matter. And that, surely, is not a bad thing.
It’s Monday. The day of the week we hate the most when we realise that we really do have to wake up. Myself, I on occasion throw in some choice words as I swat my alarm clock. This graphic, from xkcd, is apropos as—well, you get the idea.
This comes via the blog The Map Room. Designer Yanko Tsvetkov created a series of maps that most wholly, completely, and accurately represent the cultures, peoples, and attitudes of various European countries towards, well, other European countries. Some of the usual suspects are in there, the Brits, the French, and the Germans. However, I find the Bulgarian perspective, my screenshot choice, of interest because one does not typically find Bulgaria in the list of usual suspects. (Though one perhaps should as it is a member of the European Union unlike the Norways, Switzerlands, and Icelands of Europe.)
Anyway, these are funny—even if one does not necessarily understand the background to the humour there are enough that even we Americans can understand.
But anyways, according to the National Bureau of Economic Research—the people who declare when recessions and such begin and end—the recession that began in December 2007 ended in June 2009. Good news of a sort. And so naturally the press covered it, including the Wall Street Journal.
They included this image:
One, the drop shadows are unnecessary and the giant diamonds hide the actual turning point. The former could be eliminated and therefore allow the line to have greater, crisper detail as the colour should be enough to differentiate the lines. The drop shadow just sort of blurs everything together. The diamond could either be smaller or simply denoted on the timeline and thus allow the entirety of the line to be shown.
What I do appreciate, however, is that the first two charts show the same timeline and therefore allow for an easy comparison of the GDP turnaround to the jobs turnaround. And as one can see, while the recession has ended, if this most recent one is to follow in the paths of its predecessors, jobs will be a long time in returning to pre-recessionary levels.