I bet you didn’t know this. Marge Simpson was actually modeled after the coastlines of Europe. True story. [via Strange Maps]

How much more (or less) money do you spend on groceries than you do on dining out? How does it compare to how others spend? Bundle, a new online destination that aims to describe how we spend money, takes a look at the grocery-dining out breakdown in major cities. The average household in Austin spends the most money on food per year, period. Atlanta has the highest skew towards spending on dining out at 57%. The US average is 37%.
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Andrew interviews Fernanda and Martin about their new venture Flowing Media, visualization, and their amazing taste in adjectives. On the divide between art and science as it pertains to visualization:

The only divide that matters is between good work and bad. Contextualized questions like, “Does technique X help biologists investigate gene regulation?” or “Would installation Y be an inspirational addition to our museum exhibit on generative art?” are necessary and useful. More general debates about the role of art versus science are fun, but can also be distracting and block the flow of ideas.

In any case, arguing about labels isn’t effective because language has a life of its own. For instance, “social network” once meant a specific sociological model, but for most people today it means Facebook or MySpace. It may annoy sociologists, but that’s just how the language evolved. Now the word “visualization” is starting to become part of the popular lexicon. Who can say what it will mean in ten years?

That sounds about right. Read the full interview on infosthetics.

PCWorld provides a handy field guide to help you spot fanboys in the wild. Come in contact with someone who is strangely turned on by brushed metal, goes rampant on the mention of AT&T, calls everything magical, fears beach volleyballs, and has Coldplay on constant repeat? You’ve got an Apple fanboy on your hands. You’ve been warned.

[via Cool Infographics]

Sebastian Wernicke, an engagement manager at Oliver Wyman and former bioinformatics researcher, explains the results from his pseudo-analysis of TED talks. The result: a guide on how to give the ultimate TED talk. Go as long as you can, grow your hair out and wear glasses, and cover happy ideas that are easy to relate to. Or better yet, use Wernicke’s tedPAD to formulaically write your own talk to drive the audience wild – or boo at you emphatically.
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This is a story of fake charities and tax shelters. In an analysis of data from the Canada Revenue Agency (CRA), it was found that billions of dollars in donations were collected by fraudulent organizations, with only a tiny portion going to the actual causes. In one case, only $1 out of every $100 went to helping the homeless. The rest of the money went to a tax shelter. Shameful.

All told, my colleague estimated that these illegally operating charities alone sheltered roughly half a billion dollars in 2005. Indeed, newspapers later confirmed that in 2007, fraudulent donations were closer to a billion dollars a year, with some 3.2 billion dollars illegally sheltered, a sum that accounts for 12% of all charitable giving in Canada.

Not only did this lead to the exposure of fraud, but also negligence on the part of the CRA charity division (now under new leadership). How did this go on for so long? A simple sort on the data would have raised questions immediately. Instead, it took a freelance consultant, poking around out of curiosity, and journalists, who were aware of fishy behavior, to move things along.

[via @datamarket]

Hannah Fairfield of the New York Times looks at driving habits and gas prices over the past six decades. Miles driven per capita is on the horizontal, and the adjusted price of gasoline is on the vertical. The drawn path indicates order in time.

Americans have driven more miles every year than the year before, almost every year, but there’s been a swing as of late. High unemployment has meant less people driving to work, and less consumer spending means less freight moving across the country. As a result, the path appears to swing in the opposite direction.

[Thanks, Craig]

Most people don’t know what actually goes into a good infographic. There’s a lot more to it than just the design. There’s research, analysis, and fact-checking that you have to do long before you open Illustrator. Sarah Slobin, from the Wall Street Journal, explains how to create successful infographics. Have an idea, get the data, choose your tools, edit wisely, and above all else, pay close attention to detail.

I don’t dream in numbers, but if I did, I’m pretty sure it’d look a lot like this. In Nature by Numbers, a short movie by Cristobal Vila, inspired by, well, numbers and nature, Vila animates the natural existence of Fibonacci sequences, the golden ratio, and Delaunay triangulation. Watch it. Even if you don’t know what those three things are, the video will rock your socks off.
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Nutrition facts labels are uniform across products, but let’s imagine for a second that you could do whatever you want, just as long they showed certain bits of information. FFunction takes a stab at redesigning the standard milk carton under this premise. No cows, no fields of green, and no dairies. Just nutritional facts and full transparency on what’s going into your body.

This wouldn’t work with a mass market, but hey, they’ve got my purchase. After all, data does a body good.

[Thanks, Audree]

There’s been a lot of hullabaloo about Facebook’s newly installed privacy policies. It started out very closed, to just university students, and has expanded its reach, especially over the past year, to the more public Web. Matt McKeon, of the Visual Communication Lab, explores Facebook’s privacy policies, from 2005 to present.

Rings represent the audience, starting with you in the middle all the way out to the entire Internet. Slices represent bits and interactions you have on Facebook. Click on the image to see how the policies changed over the years for each bit.

Finally, you can also download the code (in the implementation section), which was written in Processing.js. I think I’m noticing a trend. Check it out here.

[via Ben Fry]

Lee Byron open-sourced his streamgraph code in Processing about a month ago. Jason Sundram has taken that and ported it to JavaScript, using Processing.js.

The algorithms are the same as that in the original, but of course the natural benefit is that people don’t need Java to run it their browsers. Jason has also added a few features including dynamic sizing, more straightforward settings, and some interaction with zoom and hover control. Really nice work.

Grab the code, plus examples on GitHub.

[Thanks, Jason]

Yeah, it’s Friday. [Married to the Sea | via @levib]

For those following the status of the oil spill, the New York Times provides a map tracking the spread. Press play to get the day-by-day. The oil is currently spreading to the west of the Mississippi delta, getting dangerously close to the oyster beds (in red).
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As always, it was an interesting month for FlowingData. Thanks again, everyone for showing your support through retweets, likes, and stumbles.

In case you missed them or are new to FD, here are the top posts from the last month, based on a combination of views and comments. The Walmart map came back to life recently with new data and a feature on CNNMoney.

1. Watching the growth of Walmart – now with 100% more Sam’s Club
2. Data Underload #18 – Sleep Schedule
3. Explorations of real-world traffic
4. Air traffic rebooted in northern Europe
5. Trustworthiness of beards
6. Data Underload #17: Famous Movie Quotes, p. 2
7. A flowchart to decide what typeface to use
8. 100 Pixar characters drawn to scale
9. Data Underload #19: First Date vs. Reality TV First Date
10. Streamgraph code is available and open source

From the Forums

There’s some good stuff in the forums too.

• Example of bad Illustrations – Sometimes graphics make things more confusing.
• Multi-series scatter plots – Looking for a way to make these.
• Creating visualizations – What tools should you use?
• Data Scientists and Engineers for Online Game Data Startup – Looking for a job?

Have a question or something cool to share? Post it in the forums.

There are a lot of job opportunities out there for visualization people. This is one of the more awesome ones:

We are looking for a PhD-level researcher who is excited by data, visualization, and communication. A job candidate should have a history of designing and building innovative visualizations. An emphasis on large-scale user participation (e.g. collaboration, crowdsourcing, social communication) and on evaluation of hypotheses about user behavior is a plus. A successful candidate will have published in one or more areas of information visualization, computer-supported cooperative work, and human-computer interaction.

No more Martin and Fernanda, but still good I am sure.

[via @infosthetics]

Along the same lines of Dolores Labs’ color experiment, Randall Munroe of xkcd reveals the results of his color survey. He took a slightly different approach though. Here are some of the basic findings:

If you ask people to name colors long enough, they go totally crazy.

“Puke” and “vomit” are totally real colors.

Colorblind people are more likely than non-colorblind people to type “fuck this” (or some variant) and quit in frustration.

Indigo was totally just added to the rainbow so it would have 7 colors and make that “ROY G. BIV” acronym work, just like you always suspected. It should really be ROY GBP, with maybe a C or T thrown in there between G and B depending on how the spectrum was converted to RGB.

A couple dozen people embedded SQL ‘drop table’ statements in the color names. Nice try, kids.

Nobody can spell “fuchsia”.

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SolarBeat is an audiolization by Whitevinyl that makes music with the planets. Each planet is assigned a note. As the planets orbit, a note is played each time a year passes on that planet. Result: the planets make sweet, sweet music together.

[via Information is Beautiful | Thanks, John]

Gary Wolf, of Wired and The Quantified Self, describes personal data collection and analysis in NYT magazine. Collect data about yourself, and you just might learn something.

Humans make errors. We make errors of fact and errors of judgment. We have blind spots in our field of vision and gaps in our stream of attention. Sometimes we can’t even answer the simplest questions. Where was I last week at this time? How long have I had this pain in my knee? How much money do I typically spend in a day? These weaknesses put us at a disadvantage. We make decisions with partial information. We are forced to steer by guesswork. We go with our gut.

That is, some of us do. Others use data.

It all sounds great at first. But the story ends, as these types of stories almost always do, with a guy in a Google shirt walking around with one too many gadgets:

Bo Adler, a young computer scientist at Fujitsu Laboratories of America, is one of the most committed self-trackers I’ve ever met: during his most active phase he wore a blood-pressure cuff, pulse oximeter and accelerometer all day long, along with a computer on a harness to collect the data. Adler has sleep apnea, and he is trying to figure it out. When he became too self-conscious going to the gym in his gear, he wore a Google T-shirt to throw people off. Maybe he was a freak, but at least people could mistake him for a millionaire freak.

We data folk stick to our guns though:

“My girlfriend thinks I’m the weird person when I wear all these devices,” Bo Adler says. “She sees me as an oddity, but I say no, soon everybody is going to be doing this, and you won’t even notice.”

So proud. You tell ’em, Bo Adler. You tell ’em.