Do you live in a horribly violent and crime-afflicted state? Do you want to know? Well there’s a map for that.
From the Guardian, here we have a familiar choropleth that colours each state based on where it falls into the range from most peaceful, Maine and Vermont, to the the most violent, Louisiana and Tennessee. The map was developed using a site called chartsbin from data provided by the Global Peace Initiative.
In short, nothing fancy, but an interesting topic to visualise after the earlier world rankings. Truth be told, I think the added data in the rollover state for the US states is more meaningful than the big rank number and flag that appears in the global version.
Le Monde is a French-language publication and so I never really bother with it, despite favourable reviews. However, they do have a small site with some content in the English language that I check from time to time. Frequently they have maps or other graphics of some interest, and this time upon visiting—done to see if they have anything on Libya given the lead taken by France and the UK—they had a few maps of the situation in North Africa.
By and large, nothing radical or ground-breaking in the maps. But, the designer, Philippe Rekacewicz, used a different cartographic perspective than I am at least accustomed to seeing for infographics. And then the aesthetic of the map is interesting, and quite different than what one typically sees. In a refreshingly interesting way. Now, whether he used a texture or filter in Photoshop to create the background map or whether he physically drew the map (and then overlaid the informational elements digitally), it matters little as the style works. I enjoy the idea of mixing the hand-made and data visualisation—though it needs to be well-executed.
He created a few sets of maps; each makes use of a slightly different palette. These certainly help create the visual distinction necessary between data sets. The pie charts are not particularly helpful, but they at least are kept simple: looking at only two parts of the whole. The comparison within each nation by bar charts of internet connectivity and higher-education learning works. It begins to work not so well as one tries to compare country to country. Though, the separation of the bars into ten-percentage point sub-bars begins to alleviate that issue. The main map, that highlights the political situation does a nice job of putting these countries into broader context. That is, who has oil and who has control over the key waterways in the region.
All in all, a refreshing set of maps that illustrate the fluid situation in North Africa and the Middle East.
While not new news, if you have not heard, Canada’s minority government fell and Canada is having an election. And, as we all know, elections mean infographic insanity. Map mania. Graphs galore. You get my drift.
The Globe and Mail, a Toronto-based newspaper, printed an infographic about the 50 ridings to watch. (A riding is, for my mostly US-based readers, similar to a congressional district.) They complemented this with an online, interactive piece. They did all of this a few days ago.
I have been meaning to write about this for a few days, but am only now sitting down to write it up and an interesting thing has happened. Whereas before, I was able to click the Globe and Mail’s link to their print graphic, now I get directed to their Google map pushpin overlay. Bye-bye, print graphic.
And that is a shame, because, the print graphic is far better than the interactive. Yes, the pushpin can be clicked to read a small snippet of summary about the riding, however, at the same scale of print graphic, good luck finding all the pushpins. And while one can certainly zoom-in to find all the urban ridings, one loses seeing the whole and that riding’s relationship to the rest of Canada. Compare that to the print graphic where equally-sized boxes represent the ridings, and the boxes are spread out across a map of Canada in the background, showing the total apportionment of ridings to the provinces and territories. Whereas the pushpins do not. The arrangement of the boxes also has urban ridings grouped together and delineated from more rural ridings. Whereas the pushpins do not. And the boxes are not tied specifically to a point. Whereas the pushpins are. And that is most helpful, because one can only assume that the Western Arctic riding is located inside Yellowknife’s city hall. Right?
Pushpins are great for locating a specific point. Note the point of the pin. The boxes are great for eliminating the distorting effects of electoral districts in rural vs. urban settings. For comparison, look at the congressional districts in and around cities like New York and compare them to those in places like Montana.
I think the print graphic is better also because it included three charts that summarised and provided context of the 50-key ridings in the context of the whole general election across Canada. Google’s pushpin map overlay thing…does not.
Is the print graphic perfect, no. As I noted above, it does not specifically name the 50, as one can discover by clicking on the pushpins. Nor does it provide the name of the candidates or a very brief summary of the situation, as one can discover by clicking on the pushpins. But I have a better grasp of how the little piece fits into the whole from the print graphic.
Perhaps the best solution would have been to create a unique interactive piece that married the best of both designs. Scrap the Google maps bit and create a set of interactive boxes that mirror the print graphic, and so by clicking on the boxes one can access the same information in the pushpin. And then one would also have a reason to write something in the print article about checking the website for the online version that has even more information. But that is surely crazy talk.
As an additional point of comparison, the two screenshots are both roughly the same size in width—the main concern in showing all of Canada—and just note the amount of data presented in both versions.
A more interesting question, though, is why was the print graphic was removed from the site? (Or at least made so difficult to find that I could not find it.)
Credit for the print graphic image I have is to the Map Room, which is from where I first learned of the map to begin with.
This post comes to us from eBay via cnet. Ebay does a wonderful thing, it fills in the gaps in the marketplace. If you live in, say, the Netherlands, and want something that is available only in the United States, chances are you might find somebody willing to sell it to you from the US.
Among those things that people want are iPad 2s. So here eBay has put together an infographic about their sales of iPad 2s from US sellers to foreign buyers.
I must admit to being a bit underwhelmed here. Maps are great and all, but here this map adds nothing to the story except that I can now identify where Poland is. It’s an island country north of Belgium. Or is that France? Wait, what is this lonely sticker-tag for the United Kingdom out in the Atlantic? The data encoded in the map is already present in the datagraphic, if you look to the bar chart of iPad shapes in the lower left quadrant.
But the bar charts do confuse me, I very rarely like using symbols of things for measuring precise numbers of things when those symbols of things represent a number of things more than just one thing. (And that is about as confused as I feel.) And then on another level, I have to strain for a moment to figure out what these three-letter identifiers are. As it just so happens, there is a standardised set of country abbreviations in both two and three letters. When I see UNK, I immediately think Unknown. And RSS makes me think of RSS feeds. Neither connects me to the United Kingdom or Russia.
In the bottom right is the breakdown of sales by model type. Here, where the treatment is simpler we see more success at clearly communicating the information. Could it be more succinct and a touch better organised, yes. But, in all, this is clear and effective. Ergo, it works.
Interestingly, cnet also posted the previous year’s infographic by eBay for sales of the first iPad.
Very loosely (and quickly), I think it is more successful and tells more data. The data on the map, like this year’s, need not be communicated by a map, that much is true—why are the countries two shades of blue, I have no idea if that encodes data. However, the same data is also duplicated in the chart in the lower left quadrant, but here far more succinctly and far more accurately than by weird symbols of the iPad. Last year’s infographic is missing the breakdown by model type, however, instead of those six datapoints, here we have a timeline of iPad sales that, it is safe to say, references more than six datapoints.
In a sense, eBay took a step backwards in their infographics. A pity, because one imagines that if they have the sales data for time periods, they probably have other sets of data that would make for an interesting and richer piece.
Credit to the designers at eBay and cnet for posting the article.
The Census Bureau has been releasing state population figures over the past several weeks and one means of accessing those figures is through a small, interactive map feature. Clicking through makes for some interesting observations—although not all states are currently available. In this screenshot, one can see an interesting story. Western Pennsylvania is shrinking whereas eastern Pennsylvania is growing. And, perhaps importantly, Philadelphia has perhaps reversed its long-term trend of population decline and saw a 0-5% increase in population while its further suburbs have seen increases in the 5–25% range.
If one is not viewing the piece in fullscreen mode, the navigation can be a bit small, especially for small counties. And the counties over which one rolls with the mouse cannot be selected, they are purely rollover functions that display census data from 1960 and the total population as of 2010. I would have liked the ability to select a particular county and then compare it to others by rolling over neighbouring counties. The colour choice, blues and a light, brownish-beige work rather well within the overall blue motif of the site. And by restricting the palette there, one gains the ability to use an altogether different colour, here green, to indicate which counties are rolled over along with differentiating the rollover box from the remainder of the map piece.
I wonder if more could not have done with the ethnic breakdowns on the right. Certainly the overall breakdown is effective, but it appears to lack a summary of sorts. What was the overall change for the state? And on a minor note, the person symbol is downright distracting.
To get to the first state, one clicks on said state from an overall map of the United States. States are blue if they have had their data released, grey otherwise. However, once looking at a state, there is no way back to the overall map as states are chosen from a small button in the upper-right. This works just fine, we are here to look at state data, not for a geography lesson. However, that they use the map at the beginning seems incongruent with the remainder of the experience. I wonder if they could not remove the map at the start, or keep the map but make it more useful. After all, it would be interesting to see the percentage change in the states displayed—the unpublished states could remain grey.
Further below the first map is a second map.
Here, one does have access to the state population change figures. Much of the critique above remains salient here, except the light brown for population loss in the first map is here replaced by a garish and obnoxious orange. An interesting addition is the range of historical data, from the 1910 census through the 2010 census and to see how those population changes affected the apportionment of seats in Congress. Another interesting story that one can glimpse is the ‘filling-in’ of the North American continent. Population density in 1910 was high only in the Northeast, but ever since, the people have spread, concentrating along the coasts and then moving inwards towards the vast centre of the continent.
It is a mad, mad world out there these days and I suppose this is the point at which we all begin to run around shouting that the sky is falling. Despite all the madness in Libya, the constitutional referendum in Egypt, the protests in Syria, the election in Haiti, and the president’s overseas trip to Brazil we still have the aftermath of the Sendai earthquake and the subsequent Pacific tsunami. The latter being particularly important because of the damage to the now infamous Fukushima Daiichi nuclear generating station in northeastern Japan.
Fukushima will likely be up there with the three other major nuclear disasters of a power station variety: the Windscale Fire in Cumbria, England; Three Mile Island outside Harrisburg, Pennsylvania; and of course, Chernobyl in the Ukraine (then the Soviet Union). We sometimes have heard the media compare Fukushima as the next great nuclear disaster, but how bad has it really been?
This graphic by XKCD comes to me via my coworker, Brian Morgan, and it breaks down our average exposure to ionising radiation—the bad stuff—from nuclear accidents from Chernobyl to Fukushima to x-ray machines to the natural radioactivity in the soil. Yes, you are likely being irradiated as you read this post.
Radiation is bad. But we will all find better solutions to problems if we keep our fears both in proportion and in check. Fukushima is not good. But it is far, far from the end of the world.
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.
The BBC has an article about the massiveness of Facebook—at least in the United States. They have taken the data and spent time to do a little bit of visualisation. It is worth a look; the design is not perfect but acceptable in a broad sense.
The Washington Post has released an in-depth article, or series of articles, about the intelligence community of the United States and its growth since 11 September 2001. There are several visualisations of data and relationships between government agencies and companies along with a video introduction and, well, a traditional written article or two.
Overall, the piece is quite interesting to look through—although I have not yet had the time to do just that. Some of the visualisations appear a bit thin. But, that may be just because I have not yet had time to play with them enough to draw out any particular insights.
What is nice, however, is again having visualisations supporting editorial content in such a fashion.
The election has come and gone yet very little is resolved; the UK now has a hung parliament. Labour, the Tories, and the Lib Dems are now left to negotiate on the details of forming a coalition government, wherein two parties formally agree to cooperate in governing the country, or a minority government, wherein the Tories try to govern with the most seats but less than a majority. Or does Labour try to work with the Lib Dems and achieve something of a minority coalition government. The one certain thing about the election is that we now have loads of electoral data that wants to be visualised.
A few things at the top, as an American, despite my following of British politics, I am, well, an American. I am more familiar with the American system and so some of what may follow may be inaccurate. If at all, please do speak up. I should very much like to understand an electoral system that may now change entirely.
I wanted to point out a couple of sites real quick and some advantages and disadvantages thereof. Most of these were likely around before the election, however, I have been a tad busy with work and some other things to provide any commentary until now.
Auntie. The Beeb. The BBC. They have done a pretty good job at playing with four variables and the results. Are pie charts great? No. Not at all. However, they naturally limit us to 100% whereas bar charts displaying share are not necessarily as limiting—understanding that, yes, such things can be coded into the system.
Another interesting thing about the BBC’s electoral map is their cartographic decision to represent each constituency as a hexagon instead of overlaying the constituencies over a political map. This actually makes quite a lot of sense, however, if one considers that British constituencies are supposed to be rather equal in terms of population—not geographic area. And so while a traditional map will portray vast swathes of Tory blue and Lib Deb yellow, Labour counters in holding numerous visually insignificant constituencies in the inner cities of the UK.
Does the BBC need to represent each Commons seat as a square and arrange them to cross the majority line? Most likely not. However, it does keep with the idea of displaying each constituency as the boxes are placed next to the hexagons.
All in all, I think the BBC’s piece is quite effective. I do miss seeing the actual geography of the UK. But I understand how it is less useful in displaying the outcome of one’s playing with the electoral swing. Useful, but not necessarily needed, is the provision of several historical elections as comparisons to one’s playing.
The Guardian is next, in no particular order. Their swingometer is a bit less interesting than that of the BBC’s. Certainly in some senses it makes more sense, any bi-directional swing, while easier to grasp, ignore the complexities in having the Liberal Democrats as a viable third party and thus third axis. The circular swingometer attempts to rectify that. However, what the BBC does with their pie chart version is delve into the politics of the regional and fourth party candidates. For example, the Greens won a single constituency in southern England. In a hung parliament a single vote may be the difference between passing and defeating a bill. The BBC accounts for this while the Guardian does not.
What is particularly interesting about their calculator, however, is the ability to track individual seats and watch as one’s changes affect that particular constituency. As I play with the calculator, I can watch as Brighton Pavilion, where the Green party candidate won, changes from Labour to Conservative. However, nowhere in my exercises, have I managed to switch the seat to a fourth party candidate. The BBC solves this by not allowing one to select particular constituencies; one can only guess which seats they are looking at.
Also interesting about the Guardian’s version is their provision of different data displays. The default is a proportional representation, with each seat equating to a single square. However, they also allow one to view the results on a natural geographic level and strictly in terms of number of results and how close said results are to the magic number of 326. Additionally, the map allows you to filter for only that region of particular interest to you. If I only wish to look at, for example, the West Midlands, I can look at just the West Midlands without being distracted by additional regions. (The West Midlands provides another interesting example of being unable to factor in the role of fourth party players as Wyre Forest switched to the Conservatives, a result I cannot here duplicate.)
Overall, I really like how the Guardian provides different ways of viewing the data and the ability to track those changes to a particular constituency—even across the changes in data views. However, the Guardian is lacking at least in the ability to address the role of independents and regional parties. Perhaps this is do to a level of difficulty in predicting results at that level of granularity; something that is wholly understandable. However, that the BBC does just that is unfortunate for the rest of the Guardian’s piece because the rest of it is so nice. Even aesthetically, I find the Guardian’s to be appealing.
Next is the Sun. This, admittedly, is not so much a calculator but more a results map. And as such, it is effective in its simplicity. There is no messing about with swing or such—again probably because it is simply filling in constituencies by result. However, where the Sun’s piece fails is that to see any result, one needs to click a specific region. When selecting the UK, one can only see the outlines of the various regions of the UK. There appears to be no way of seeing UK-wide results.
Additionally, the data is presented strictly on a natural geography. This has the deficits as outlined above. And while the Guardian does present the results in such a fashion, it is not the only fashion in which data can be presented. Further, to see any results for a particular constituency, one must click all the way through the map before seeing data. None of this helps one access the actual data. And while one could say that the results are less important than showing the victor, one still needs to click into a specific region to see a victor thereby requiring a click whereas the other pieces provide results at an instant view.
Aesthetically, while both the BBC and Guardian favour a lighter, more open space the Sun’s piece feels trapped in a claustrophobic space surrounded by dark advertisements and flush against menus and heavy-handed navigation. All in all, I must confess that the Sun’s piece strikes me as an underwhelming piece that is less than wholly successful. It could have been made at least wholly successful if I needed not navigate into a particular region to mouseover a constituency.
The last piece I am going to look at is that from the Times. While there appears to be no way of playing with possible outcomes, the Times provides interesting ways of slicing the data in a more narrative structure. In terms of the map, the display suffers from being viewable only as the natural geography of the United Kingdom without being able to even toggle to a proportional view.
The additional data is displayed nicely in a side panel. I have to say that from an aesthetic standpoint, the Times’ mini site for the election results is my favourite. The black banner and main navigation sits well against the light colours used for the remainder of the piece. The serifed typeface for the numbers fits well with the newspaper feel and the black and serif combined works well to recall No. 10, Downing Street. A very nice touch and design decision.
As noted, the display fails in that only shows the data in a natural geographic sense. Now, the site overall provides links to news coverage of the event; these are accessible through a dropdown menu in the black banner. But, when clicked, these stories alter the map and highlight the particular constituencies in question. This approach provides a nice touch on straight data visualisation in linking the data to the editorial content of the newspaper. Which seats were taken or lost by independents? On a broad and filled-in map of the United Kingdom, I may not be able to know. But by clicking on that story, the map filters appropriately and I can click each constituency and get the story.
And so while the data visualisation is not necessarily on par with that of the BBC and the Guardian, the tie-in with the editorial emphasis—in my mind—makes up for the lack of detail in data visualisation. Data is wonderful, however, the narrative is what helps us make sense of what is otherwise just numbers and figures.
That editorial link and the subtle design decision to link the minisite to the sort of 10 Downing Street aesthetic makes the Times version my favourite and the best designed experience. Besides the lack of detail in the data visualisation aspect, the only other drawback is perhaps the load time for each change in display.