I’ve started to think a lot about data.
I know, it’s out of character. It came from a question about assumptions: How can we measure the accuracy of what we assume to be true about the world?
We can’t. At least, that’s what I’ve decided. I’ve been wrong before. We all know that everything is relative; that assumptions are almost always wrong; that two contradictory statistics can both be accurate; that Truth is unattainable, that truths are multiple, colliding, uncharted. We know. This is why it’s impossible for journalists to be objective: we have to choose a truth. But I can’t stop thinking about it.
For my internship, I’ve been watching videos put out by TED, Technology, Entertainment, Design, that have piqued my interest. One presentation, by Hans Rosling, a Swedish public health professor, moved me. Titled Let My Dataset Change You Mindset, the piece was about the way we visually structure our worldviews. Industrialized and Developing nations sit on opposite sides of the room, one laughing at the other, or, when feeling generous, throwing a bone.
He opens the presentation by showing that, when represented by data, that assumption is based on the world in the 1950s.
Divided by family size and life expectancy, “Developing” and “Industrialized” nations no longer sit in two separate clusters in opposite corners of the graph, but as he plays the animation to advance the data over time, the bubbles all move slowly, gathering in the top left, long life, small family corner. Only a few struggling countries lag behind. This sharp division that continues to be made in our general discourse, of “Developing” and “Industrialized” nations, is false. We are all developing, and toward the same goal.
Slowly, this convergence will transform the way we think about the globalizing world. For right now, we’re thinking three generations in the past.
Skip to another graph: Life expectancy v. Income. Case studies: China and the U.S. Both live longer and make more money than they did 60 years ago, but how they got there is intriguing. The U.S. used the economy to build income, which gradually improved the overall health of citizens. China’s development went in stages, stagnant until the rise of Mao Zedong, when health improved dramatically and rapidly. Public health was thrust upon the people, providing vaccinations, treatments, prevention methods, family planning and general knowledge of how to live a healthy life. But during this time, income among the Chinese remained low and steady. It wasn’t until Mao’s death and the introduction of a quasi-capitalist economy that Chinese citizens increased personal income.
Quality of life increases rapidly in Socialist environments, where household income is not relevant to general way of life. Capitalism develops the same quality, more gradually, and less equally among its citizens. Beautiful. In the end, two world views, pitted against each other for their vast differences, are not so different. They’re both boiled down to little bubbles on a graph near the top of the life expectancy range.
Another presentation, The Beauty of Data Visualization, by David McCandless moved me as well. While the entire presentation gives us an illuminating look at the importance of visualizing data, whether to parse out the real meaning of $1 billion, or to see the most popular times of year for break-ups on Facebook, a few particular points caught my attention.
The U.S. military budget, he shows, is so massive that it can contain all the other military budgets of the world inside of it, and still have room to flex its muscles. It is more than twice the size of Africa’s total debt.
This sparks certain assumptions: military dominance; modern imperialism; the insatiable need to spread democracy; the military-industrial complex. Yet, it’s in absolute numbers, and we know all fact is relative. So, of course the U.S. has a giant military budget. It also has a giant GDP, so logically they would grow hand-in-hand. When we compare the military budgets as a proportion of GDP, Myanmar comes out on top. Myanmar. At 26 percent of its GDP.
The U.S., in comparison, budgets 4 percent of its GDP on military activities. Below Jordan, Georgia, Saudi Arabia, Kyrgyzstan, Burundi and Oman.
Yeah, I said Burundi.
It’s the intersection between understanding relative information, cross referencing absolutes with other interesting absolutes to come to a beautiful conclusion, and the power of visualization that make these presentations powerful. We see much faster than we think. I can think of so many applications this knowledge has in my industries: the creation of useful infographics in a newspaper; the consolidation of massive amounts of information into easily digestible, but comprehensive charts; the ability to show readers a state budget they can really understand.
And, most relevant to the project this blog seeks to explore, all this comes to terms with the fact that it’s all subjective, relative. Even data journalism isn’t objective. It can’t be. We’re choosing which points of information to pit against each other. We’re choosing that X is relevant to Y and not Z. But visual data gives so many more options. It allows readers to soak in much more information in much less time. They can compare more data sets to come to their own conclusions. There will always be a certain amount of editorial agenda-setting, but with visual data, the opportunities for reader engagement are endless.
McCandless was right. Data is beautiful.