Driving can be dangerous. But perhaps most so in the developing world. The Pulitzer Center created this interactive map to allow users to explore just how dangerous driving can be.
A look at road deaths in Kenya
Little windows provide details on countries the user rolls over. This data looks at deaths per 100,000 people, killer/victims, and lastly a rating of law enforcement across several different issues. The map also includes links to stories on the website as well as an information panel that related small bits of information about selected countries.
Credit for the piece goes to Tom Hundley and Dan McCarey.
Earlier this summer I looked at a graphic by Thomson Reuters that compared life expectancy changes across the world from 1990 to 2011. Last month, the Washington Post published an interactive graphic that explores life expectancy (along with obesity and physical activity) across the United States from 1985 to 2010.
Changes in female life expectancy
What I really enjoy about the piece is that each toggle for the health condition, i.e. life expectancy, obesity, physical activity, the text beneath swaps out to explain what the story is. Context is key. But then the ability to flip between the actuals and the growth for both men and women allows the user to really explore the data. And to see that growth or lack thereof is not even across the sexes.
From the design side, a minor point worth noting is the use of different colour palettes based on the mapped metric. The actual values (with the greater range) use a darker green-blue and tint that down whereas the growth values (all of three conditions) are in a different palette. Here it works, though I am more accustomed in similar pieces to seeing the swapping of palettes for changes in the mapped metric.
Beneath the big map, however, are two components also well worth the user’s attention. Perhaps deceptively simple, two sets of line charts, they add (again) context to the data. For example, while it is great to see life expectancy in the United States improving, when you compare that to the rest of the developed world, we are falling behind.
Overall a solid piece.
Credit for the piece goes to Patterson Clark, Kennedy Elliott, and Katie Park.
Sometimes maps just do not carry the visual weight of the potential impact of climate change, specifically rising tides. Swathes of blue over city maps from high altitude are intellectual exercises. Who works where? Where do I live? But when you can begin to see familiar buildings and sites swallowed up by a modest rise in the sea level, the hope is that people feel the impact.
A flooded Boston
My guess is that was the intention of the Boston Globe in this piece, which lets you explore a bit of an underwater Boston waterfront.
Happy Friday, everyone. Today’s post comes via colleagues of mine in London, who shared with me the Guardian’s selection of 16 useless infographics. They are shit infographics. Well, at least one is. Check them out and you’ll understand.
Using maps to explain maps…
Credit for the selection goes to Mona Chalabi. Credit for each infographic belongs to the infographic’s respective designer.
Today’s piece is a map from the Economist. It looks at the state of nuclear energy across the world. Slovakia caught my eye because when I recently traveled across that country I glimpsed from my train the massive complex near (I think) Trnava. Apparently those are also some of the youngest reactors out there.
A map? Again? I know. But trust me, this one is interesting. For those of you who do not know, Boston’s Thomas Menino is not running for reelection this year. By the time he leaves office, he will have been the mayor of Boston for over twenty years and so this year is the first open election in a long, long time.
So what’s better than graphics for election-related data? Graphics with a medieval/Renaissance/fiefdom aesthetic, that’s what. With a little bit of fun, the Boston Globe mapped out the local areas of strength for the 12 candidates for mayor. The residence of each is denoted by a castle keep while areas of strength, location of donors, and key voting areas are signified in different colours. And the map’s background? Well, you can see for yourself.
Boston mayoral candidate map
Credit for the piece goes to Alvin Chang, Andrew Ryan, Javier Zarracina, and Matt Carroll.
I don’t often write about maps, especially of the choropleth kind. In many cases I choose not to because so many of the maps are one-dimensional: how fast is x growing across the world; which is predominant across the world, y or z? So I was pleasantly surprised by the Economist yesterday when they published this interactive map on the scourges of hepatitis and HIV.
Hepatitis vs HIV
Quickly put, the map is a success. It shows a clear geographic pattern; the developed/Western world along with the Middle East and Asia have a larger problem in hepatitis than HIV whereas Africa and Latin America are dealing moreso with HIV. (Admittedly, the fact that 117 out of 187 countries are dealing more with hepatitis is lost because so many of the countries are small in area.) But, the really nice bit about the map is not just the colour by virus, but the tint by comparative ratio. The darker the colour, the stronger the one virus over the other.
Lastly, from a data perspective, I just wonder if the ratios could not be adjusted for population, or deaths as a percentage of the national population? I would be curious to see if that would yield interesting results.
Credit for the piece goes to C.H., R.L.W., J.S., and D.H.
For those of you who did not know, the country of Mali held elections yesterday and results should be forthcoming. Those of you who regularly read or semi-frequently check my blog, you are likely familiar with the work I did covering the French-led intervention in Mali. I am a bit busy working on some other projects, so I did not have the time to prepare a graphic for the election as I had hoped. Nor did many others. Alas, the only graphic I have come upon is from Al Jazeera. And it is a mess.
Mali's election
That map only shows the provinces; the colours signify nothing. Nor is there any context for the factettes on the side. And while perhaps the intention was to show Mali in a snapshot, I think a piece about the challenges facing Mali could delve a bit into forecasted statistics. I credit the team behind the project with attempting to cover the story, but aside from biographies on the four leading candidates and overviews of the main militant groups, the piece lacks depth and substance.
Ultimately, after looking at the work, I am left wanting more. A lot more.
Credit for the piece goes to Alia Chughtai and Jacob Powell.
After two weeks out of the country, I come back and find early this morning (thanks, jet lag) an interactive article published by the New York Times on income mobility. What does that mean? From a medium side, a long narrative interspersed with charts and graphics with which the user can interact to uncover specific data about specific elements in the dataset. From a content side, income mobility means the movement of an individual from one group of money earned to another, e.g. a poor person becoming a millionaire. The piece is fantastic and you should take the time to go read and interact with it.
A map shows the broad context of the data to be looked at in the story
For some time now I have harped on about the need to annotate and contextualise datasets. Too often, large datasets paralyse people; their eyes glaze over and they simply gaze at a graphic without seeing the data, the story, the information. Little notes and blurbs of text can help people synthesise what they see with what they read with what they know to gain better understanding. But in this piece, by combining a lengthy article—very well written although that is not the focus of this post—with powerful interactive maps and graphics, the New York Times has created a powerful piece that states and then proves the point of the article. And while doing all of that, by making the datasets explorable, the Times also allows you to find your own stories.
A story-like piece lets you choose an area and an income to see how the article's topic plays out
Lastly, in the credits section at the end you will see this piece required the input of eight individuals (though I know not in what particular capacities). Clearly, for the Times this is not about to become a regular type of infographic/datavis/journalism piece. But when will skill sets be democratised or dispersed enough that smaller teams can create similar scale projects? That will be interesting to see. However, the Times certainly leads the States if not the world in some of the best information design pieces and undoubtedly this will push other publishers of similar content in this direction.
Ultimately people want to know who's best and who's worse and where they fall and this chart does that at the end of the piece
Credit for the piece goes to Mike Bostock, Shan Carter, Amanda Cox, Matthew Ericson, Josh Keller, Alicia Parlapiano, Kevin Quealy, and Josh Williams.
