The BRICs are ten years old. Well, not really. But the concept of Brazil, Russia, India, and China becoming some of the world’s largest economies is. Well, not even that necessarily. But the coining of the term BRIC is a decade old. So the BBC has a small interactive piece showing why the BRICs matter.
BRIC GDP Growth compared to that of the US
They do some interesting things with the use of hues and tints to group lines in the line charts and provide consistent groupings throughout the piece. And they have photos of leaders. Just in case you do not know what the finance minister of Italy looked like back in 2001…just do not ask me to remember his name.
Something I’ve been meaning to put up for a little while, the New York Times’ coverage of that city’s marathon and changes in the socioeconomic composition of the neighbourhoods through which the course winds.
The piece includes a narrated motion graphic explaining the changes along a map of the course, while a series of charts look at those factors from a static perspective. The horizontal axis being the route of the course.
Brooklyn segment of the NYC Marathon
Credit for the piece goes to Graham Roberts, Alan McLean, Archie Tse, Lisa Waananen, Timothy Wallace, Xaquin G.V., Joe Burgess, and Joe Ward.
Nearly a month ago, the New York Times released an interactive piece along with a printed infographic about the European debt crisis in an attempt to explain just what is going on; I wrote about it here.
Now, the BBC has an interactive graphic showing how different countries relate to each other. The width of the lines relates to the amount of debt and the colours fall into three groups: red for high risk, yellow for medium risk, and grey for low risk. These are all fairly sensible and are echoed in the New York Times piece.
The BBC's explanation of the European debt crisis
However, one advantage of the diagram used by the BBC is that the arrows emerge from an arc and show the total amount of debt going to the selected European (and US) economies. At least, I hope they do. That is how I read it, but it is not explicitly stated. I hope that I am correct. If so, this is better than the Times version which simply has a proportionally wide line starting from a circle. But without other lines, one cannot see the useful supplemental information about how much total trade the country has.
One element that sticks out is the selected state of the diagram. This uses a blue line that is rather crudely drawn atop the arc. Distractingly so. The colour choice works as blue contrasts with the reds, yellows, and greys, but the execution of the line drawing is simply poor.
Overall, the data is interesting, and if my assumption is correct, and presents a more meaningful picture of trade relations between the chosen countries. However, the execution of the piece’s design does leave me wanting more. And that, given the need to tell this story both completely and correctly, is unfortunate.
Forbes released Jon Bruner’s latest map of migration in the United States. It uses IRS figures to show inbound and outbound movement from counties across the United States. The work itself is an improvement from his map from last year, which was a bit more difficult to read. Beneath is the new version, and at the end, for comparison, the old.
This year's migration map
Firstly, the colour palette is far more sophisticated. Secondly, and most crucially, the user can hide the lines on the map, which obscures a key part of the story of migration in urban areas—higher income people moving out of the city and into the suburbs. Thirdly, the map data now includes additional years, which are available by clicking the small chart in the upper right—a welcome addition that allows the data from last year’s map to become accessible this year. Fourthly, and to be fair this may have existed previously but not that I can recall, the new map is accompanied by essays.
These essays use the map and its data to tell stories and explain what one sees going on with the data. It is (relatively) easy for one to put together a piece of data visualisation from a data set. But, without knowing where to look, users may not actually find anything valuable in the visualisation. By pointing to these essays, the map—already much improved from a design perspective—takes on a much more rounded and mature character and becomes more about generating information and knowledge than simply figures and statistics.
In an area very close to me…quite literally…the New York Times published an article about increasing segregation between the rich and the poor via the areas where they live. The study by Stanford University found that the Philadelphia metropolitan area saw the “sharpest rise” in segregation since the 1970s—the study used census data available through 2007. The accompanying graphic highlights the growth of the segregation from 1970, using small multiples of choropleths to compare 1970 to 1990 to 2007.
In 1970, much of the metro area was middle-income neighbourhoods. Certainly, the central core of Philadelphia was depressed. So too was Chester and rural southwestern Chester County. The upper-income neighbourhoods were in the close suburbs, note the townships stretching due west of the city and you see the Main Line, one of the most affluent areas of the United States, while other veins of wealth extend along other old rail lines leaving the city.
Neighbourhoods by Income in 1970
Those such as myself who are familiar with both the area and recent history should note that places like Coatesville and Downingtown are shown as middle-income. In the 1970s, areas like this and in similar places like Falls Township in Bucks County had robust steel and manufacturing sectors that employed a substantial portion of the local population.
But, compare this to 2007 and you will begin to see how many old factory towns of middle-income areas became dense pockets of depression while the city of Philadelphia itself saw a flight of wealth to the rest of the suburbs. The rural parts of Chester, Montgomery, and Bucks have seen high growth by means of new developments of upper-middle- and upper-income homes.
We are now just under 365 days away from Election Day 2012. Without a doubt, I shall have many politically-themed graphics coming. People just have to start making them. But for now, the Economist kicked it off Monday—when it was 365 days—with a motion graphic piece that outlines some of the polling numbers and challenges to the Republicans vying for power and President Obama determined to keep it.
365 days until Election Day 2012
Certain types of the chart are very much not helpful in determining the actual numerical comparisons. But, with the voiceover keeping our attention and explaining what is going on with the charts, it is as always interesting to experience a story told in charts and graphs for nearly three minutes. And about a story with real significance.
If you live in a big city, you’ve probably been running late, missed the bus or the train, needed to get home safely at least once. So you’ve probably taken a cab.
This interactive graphic from the Washington Post compares cab fares across a number of major cities in the United States. The cheapest cab rides are to be found in Washington D.C. The priciest are in Honolulu.
Comparison of Cab Fares Across Major US Cities
Credit for the piece goes to Todd Lindeman and Sisi Wei.
Humanity is amazing. We have great emotional power for love, sympathy, compassion, &c. We have great intellectual power; we have/are mastering mathematics and science to explore the depths of this ocean and the surfaces of planets not our own.
Yet with these great powers comes a great responsibility. And as we continue to reflect upon the milestone of reaching a population of 7 billion men and women, Bill Marsh at the New York Times, along with Micah Cohen, Matthew Ericson, and Kevin Quealy, reflected Sunday on humanity’s ability to let this responsibility slip from time to time and how at those times the human population of Earth fell.
Timeline of Humanity's Atrocities
The data comes from a book by Matthew White called “The Great Big Book of Horrible Things” that details the worst 100 cases of man killing fellow man. (Although, according to Marsh the account is humourous, though I have never read it.) At the top are no particular surprises: World War II, World War I, and Genghis Khan. The reigns of Chairman Mao, Stalin, and the Kims of North Korea. But a look further down the list, further down the timeline reveals in all its tarnished glory the history of humanity when we not quite so amazing.
It’s Election Day. Well, not really. But, Nate Silver and the New York Times have come together to release an election simulator, if you will, focused on the chances that a Republican will win the White House.
Chances of Republican Candidates Winning the Election
You play with a few different variables to control the outcome: GDP growth and President Obama’s approval rating. These then are computed along with a few other things (I assume) and, like magic, you get to see your Republican pick’s changes of winning the election.
Keep in mind that these are just possible candidates, not necessarily likely candidates. John Huntsman, after all, is polling in the single digits in some of the early primary states. So while the moderate, centre-right, former ambassador to China, ex-governor of Utah looks almost unbeatable in several scenarios, I think most would agree that the Republican base will not vote for him.
But it is scenarios like that of Huntsman that are worth reminding us that perhaps the current party political system we have in the United States does not yield the best candidates for public office, nor the most broadly electable.
