Oil, sweet oil. How we depend upon you for modern civilisation. BP published a report on world energy that Craig Bloodworth visualised using Tableau.
The piece has three tabs; one is for production, another consumption, and a third for reserves. (The screenshot above is for production.) But when I look at each view I wonder whether all the data views are truly necessary?
In production for example, is a map of a few countries truly informative? The usual problem of Russia, Canada, the US, and China dominating the map simply because they are geographically large countries reappears. Furthermore the map projection does not particularly help the issue because it expands the area of Siberia and the Canadian arctic at the expense of regions near the Equator, i.e. the Middle East. That strikes me as counter-intuitive since some of the largest oil producers are actually located within the Middle East.
A map could very well be useful if it showed more precisely where oil is produced. Where in the vastness of Russia is oil being sucked out of the ground? Where in Saudia Arabia? In the US? Leave the numbers to the charts. They are far more useful in comparing those countries like Kuwait that are major producers but tiny geographies.
Lastly about the maps (and the charts), the colour is a bit confusing because nowhere that I have found in my quick exploration of the application does the piece specify what the colours mean. That would be quite useful.
Finally, about the data, the total amount of oil produced, but more importantly consumed, is useful and valuable data. But seeing that China is the second largest consumer after the US is a bit misleading. Per capita consumption would add nuance to the consumption view, because China is over three-times as large as the US in population. Consequently, the average Chinese is not a major consumer. The problem is more that there are so many more Chinese consumers than consumers in any other nation—except India.
A bit of a hit and miss piece. I think the organisation and the idea is there: compare and contrast producers and consumers of oil (and consumers of other energy forms). Alas the execution does not quite match the idea.
Credit for the piece goes to Craig Bloodworth, via the Guardian.
And not in the polite Galactica way, but more in the let’s drill you, rocks, and split you open. I could go in further detail about the injection of fracking fluids, but let’s leave the double entendre alone and talk about Marcellus Shale. It’s a layer of rocks in the dirt that contain natural gas. It’s a pain in the gas production industry (sorry) and thus is only economically viable when fuel prices are high.
So in the 21st century with high fuel prices, energy companies are hydraulically fracturing (fracking) the rock to suck out all the natural gas. But this might be (probably is) causing environmental problems and thus human health problems. Ergo the controversy. This has now reached New York and so the New York Times created a simple map with some key layers of information to explain the controversy there.
Note the useful layers of depth of the shale and where those intersect (or do not) with areas that have banned or endorsed fracking.
Western Pennsylvania has had similar problems, and the Philadelphia Inquirer has had an interactive special on their website up for a little while now. And by interactive infographic I mean largely just a play-through of static images. Unfortunately, the online content is not of the best resolution and leaves much to be desired. Fortunately the graphics would appear to be quite informative especially as part of a series. A pity they are not entirely legible.
Credit for the Inquirer piece goes to John Tierno.
Infographics and interactive pieces need not always be about data. Sometimes they can help you find things far more practical than levels of Canadian defence spending or changing demographics. Sometimes they can help you find new summer cocktail recipes. Like this piece from the New York Times.
I don’t know about you, but I’ve got goals in life. Namely to retire. So thankfully the Economist put together this infographic on retirement age across the OECD (a cool club of rich countries), specifically to look at how retirement ages have changed between 1970 and 2010 alongside life expectancy.
The Secret Service screwed up not so long ago with the whole hookers in Colombia scandal. (Proof that it pays to pay.) This infographic was passed along to me by my colleague Eileen and it investigates the results of congressional hearings into the Secret Service.
This piece is doing some interesting things within the framework of the donut chart I generally dislike. We do get to see the levels of detail for different departments or areas of spending. For example, one can see that costs for building Australia’s new destroyers and how that fits into the whole budget. Or, by clicking on a slice of the donut, one can zoom in to see how pieces fit at the selected level.
But the overall visual comparison of pieces and then identifying them through colour is less than ideal.
Found via the Guardian’s datablog, credit for the piece goes to Prosple and OzDocsOnline.
For the Queen’s Jubilee I had been looking for a good infographic or two about how the United Kingdom had changed over the length of her reign, at least thus far. Alas, I found not a great deal of substantial work. This is an infographic from the Guardian that looks at quite a few single figures.
But it also has a map looking at the decline/unravelling of the British Empire.
It’s like a log cabin. But taller. A lot taller. The New York Times reports with an infographic on a nine-story block of flats (apartment building for us Americans) in London called the Graphite Apartments that was built almost entirely of timber.
Last week, the New York Times looked at the growing education gap amongst this country’s largest metropolitan areas. The infographic, click the image below to go to the full version, is perhaps a bit more layered, nuanced, and complex than it looks at first. In about forty years, the number of adults with college degrees has doubled, good, but so too has the spread of those numbers across the set of cities, bad. And then to look at any geographic spread, the two datasets are mapped geospatially. By my eye, the Northeast and Pacific Northwest seem to be doing fairly well. Not so much around the rest of the country.