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Hans Rosling Joy of Stats Addendum: Making Data Dance

January 21, 2011 By brenda michelson

In December, I posted Hans Rosling’s Joy of Stats video in which Rosling “tells the story of the world in 200 countries over 200 years using 120,000 numbers – in just four minutes.”

The video is a terrific example of combining statistics, data visualization and story telling to simplify the delivery, and therefore absorption, of an important, data rich message.

This afternoon, as I was flipping through the latest Economist Technology Quarterly, I ran across the perfect addendum to the Joy of Stats video.  An article on Rosling’s work entitled Making Data Dance. 

The piece starts by describing Rosling’s primary work:

“The realities that Dr Rosling is trying to highlight have been gleaned from decades of studying statistics. They sound simple enough: that it no longer makes sense to consider the world as divided between developing and industrialised countries; and that people everywhere respond similarly to increasing levels of wealth and health, with higher material aspirations and smaller families. “There is no such thing as a ‘we’ and a ‘they’, with a gap in between,” Dr Rosling says. “The majority of people are living in the middle—although the distance from the very poorest to very richest is wider than ever.” The best measure of political stability of a country, he believes, is whether fertility rates are falling, because that indicates that women are being educated and basic health services are being provided. “The only way to reach sustainable population levels is to improve public health,” he says. “Child survival is the new green.””

Then moves to his embrace of infographics:

“Communicating these realities to students in his international-development classes at Uppsala University proved problematic, however. “I used to make huge photocopied sheets of Unicef statistics for the students on income, life expectancy and fertility rates around the planet. But it didn’t change their world view, it didn’t create another mindset. They still insisted that we were different, that all the Chinese cannot all have a car,” says Dr Rosling. He needed a new way to present his conclusions—a way to turn dusty figures into convincing illustrations.

Innovation in infographics has always been driven by the need to explain difficult things, Dr Rosling points out. “Florence Nightingale is known as a nurse, but she also made a new kind of pie chart showing how many soldiers in the Crimean war died from military action and how many from disease.” Nightingale’s famous “coxcomb” chart from 1858 demonstrated that improving hygiene in British military hospitals slashed mortality rates. She said its design was intended “to affect thro’ the eyes what we fail to convey to the public through their word-proof ears.””

Next, the article uncovers a bit of the how:

“With the help of his son and daughter-in-law, Dr Rosling then developed Trendalyzer software (now called Gapminder) to animate the bubbles.

“It was a conscious intent to make the data look alive,” he explains. “My son invented the trails, like patterns in the snow, so you can see how countries have changed. And we could overlay countries historically so that it’s clear that, for example, China today is like Sweden in 1948 and people in Vietnam now have the same life expectancy as Americans did in 1985. Every country has a graphical path that describes its development.””

And (news to me), Gapminder software is available via Google, as Google Motion Chart:

“The software was a hit, first with his classes in Sweden, then worldwide after a video of his 2006 TED lecture was posted online. Dr Rosling was soon helping Al Gore polish up his climate-change presentations and talking about Gapminder with the founders of Google, Larry Page and Sergey Brin. “I could see in their eyes how excited they were, how my software fitted with their ideas about making organised information generally available,” he recalls. “We started collaborating and quickly reached the conclusion that it was more rational that Google acquire our technology and the team behind it.” Within a year Google had bought Gapminder, and a version of the bubble-graph software is now available free online under the name Google Motion Chart.”

Lastly, the article describes the very real problem of making data public, and Rosling’s work to “become the Robin Hood for free data”.

Check out the full article.

If you create any interesting visualizations with Google Motion Chart, please do share.

Filed Under: active information, data science, data visualization Tagged With: economist, Hans Rosling, infographics

The Beauty of Data: Hans Rosling’s The Joy of Stats

December 1, 2010 By brenda michelson

Floating on twitter today is this tremendous clip of Hans Rosling using an unique data visualization technique to tell a story.  The clip is an excerpt from an upcoming BBC special, The Joy of Stats.

“Hans Rosling’s famous lectures combine enormous quantities of public data with a sport’s commentator’s style to reveal the story of the world’s past, present and future development. Now he explores stats in a way he has never done before – using augmented reality animation.

In this spectacular section of ‘The Joy of Stats’ he tells the story of the world in 200 countries over 200 years using 120,000 numbers – in just four minutes.

Plotting life expectancy against income for every country since 1810, Hans shows how the world we live in is radically different from the world most of us imagine.”

Check it out. It’s amazing.

Filed Under: active information, data science, data visualization Tagged With: BBC, Hans Rosling

O’Reilly Radar: What is Data Science?

June 3, 2010 By brenda michelson

Mike Loukides has an excellent piece on O’Reilly Radar entitled “What is data science?”  In the article, Loukides covers making data products, the data lifecyle, working with data at scale (Big Data), story telling and data scientists.

Throughout the article, Loukides introduces the reader to many data science concepts, tools, experts and skills.

Calling out several items, I love the “data exhaust” term:

“These recommendations are “data products” that help to drive Amazon’s more traditional retail business. They come about because Amazon understands that a book isn’t just a book, a camera isn’t just a camera, and a customer isn’t just a customer; customers generate a trail of “data exhaust” that can be mined and put to use, and a camera is a cloud of data that can be correlated with the customers’ behavior, the data they leave every time they visit the site.”

I think this “make lemonade” sentiment on data quality is crucial:

“Once you’ve parsed the data, you can start thinking about the quality of your data. Data is frequently missing or incongruous. If data is missing, do you simply ignore the missing points? That isn’t always possible. If data is incongruous, do you decide that something is wrong with badly behaved data (after all, equipment fails), or that the incongruous data is telling its own story, which may be more interesting? It’s reported that the discovery of global warming was delayed because automated data collection tools discarded readings that were too low 1. In data science, what you have is frequently all you’re going to get. It’s usually impossible to get “better” data, and you have no alternative but to work with the data at hand.”

The big data definition is excellent.  It’s about the problem, not the (product) solutions:

“The most meaningful definition I’ve heard: “big data” is when the size of the data itself becomes part of the problem. We’re discussing data problems ranging from gigabytes to petabytes of data. At some point, traditional techniques for working with data run out of steam.”

And the information platforms / dataspaces concept ties to my active information tier:

“What are we trying to do with data that’s different? According to Jeff Hammerbacher 2 (@hackingdata), we’re trying to build information platforms or dataspaces. Information platforms are similar to traditional data warehouses, but different. They expose rich APIs, and are designed for exploring and understanding the data rather than for traditional analysis and reporting. They accept all data formats, including the most messy, and their schemas evolve as the understanding of the data changes.”

If you want to learn something today, read the article. Then bookmark it for future reference.

Filed Under: active information, data science, trends

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Brenda M. Michelson

Brenda Michelson

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