Stephen Walter’s The Island looks like an ordinary map of London from afar. Just a bunch of scribbles, actually. But zoom in and you get something more.

The Island satirises the London-centric view of the English capital and its commuter towns as independent from the rest of the country. The artist, a Londoner with a love of his native city, offers up a huge range of local and personal information in words and symbols. Walter speaks in the dialect of today, focusing on what he deems interesting or mundane.

Zoom in once. Outlines and locations appear.
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Maybe there’s something to this whole data science thing after all. Mike Loukides describes data science and where it’s headed on O’Reilly Radar. It’s a good read, but statisticians get clumped into suits crunching numbers like actuarial drones:

Using data effectively requires something different from traditional statistics, where actuaries in business suits perform arcane but fairly well-defined kinds of analysis. What differentiates data science from statistics is that data science is a holistic approach. We’re increasingly finding data in the wild, and data scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.

What is data science? It’s what well-rounded statisticians do.

Health and Human Services (HHS) is about to announce the launch of their Community Health Data Initiative over in DC right now. The point is to make health data more usable for consumers and communities.

Today groups will be presenting how they’ve made use of the data in the past few weeks from about 9:30 to 10:30 – as in right now. I’ve embedded the live webcast below.

They’re just going through the formalities of thank yous and intros right now, but the good stuff should start soon.
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BBC Radio 1 takes a shot at displaying the top 40 chart visually in The Love 40. It’s actually a lot better than I thought it was going to be.

A grid view of bubbles arranges singles (or albums) such that you have each column as a day, and each row as a rank. So for example, the top right bubble, is the most recent number one single, which at the time of writing this, is Nothin’ on You by B.o.B, featuring Bruno Mars. Roll over any song (i.e. bubble) and a connecting path shows how the song has risen or fallen in the past few weeks.
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It takes a lot of work for a bill to become a law. It’s a complex process that most of us know nothing about, other than the tidbits that linger in our memory from high school government class. Mike Wirth clarifies the process in his gameboard-like submission to Sunlight Labs’ competition, Design for America. Mike’s entry won top honors in the “How A Bill Becomes a Law” category.

Another great month of FlowingData. Thanks, everyone for the retweets, likes, stumbles, etc. Every share helps FD reach a wider audience, so I really appreciate it. For the new readers, or in case you missed them, here are the top posts of May, based on a combination of views, comments, and links:

1. What America spends on food and drink
2. Dreaming in numbers
3. The Boom of Big Infographics
4. Data Underload #21: Exit Strategy
5. Facebook privacy options untangled
6. Most influential people on Twitter – Cosmic 140
7. BP tries to mislead you with graphs
8. Field guide to fanboys
9. Evolution of Facebook privacy policies
10. Marge Simpson is Europe in disguise

From the Forums

Got a visualization question or something to share? Post it in the forums. Make sure you register first though.

• Org Chart Alternatives – We didn’t come up with any. Got any in mind?
• Graphic on Fight Against Breast Cancer – “Wow, so much wrong just to make it look like a boob. :\” — krees
• Large pile of ranking data for programming languages. – Anyone want to do something fun with it?
• Nokia: Looking for a data visualization specialist – Looking for a BI-related job in New York?

In case you were confused by the Pulp Fiction storyline, dehahs has plotted it out for you. Inspired by Randall Munroe’s character timeline, each line represents a character and intersections show interactions. The story board rests in the background. Like any good Quentin Tarantino flick, everyone dies more or less. Bang, bang. Boom, boom.

[via]

The ever-popular New York subway map is getting some work done, and will reveal itself with its first major redesign in over a decade:

The new subway map makes Manhattan even bigger, reduces Staten Island and continues to buck the trend of the angular maps once used here and still preferred in many other major cities. Detailed information on bus connections that was added in 1998 has been considerably shortened.

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Men’s Health takes a look at America’s most sugary drinks and their junk food equivalents. A Peppermint White Chocolate Mocha with whipped cream (venti size) from Starbucks has the same amount of sugar as 8½ scoops of Edy’s Slow Churned Rich and Creamy Coffee Ice Cream. Calorie-wise, the picture might look a little different. Still though, that’s a lot of sugar.

Be careful what you drink, boys and girls.

[via Boing Boing]

In a collaboration between CNN and Stamen Design, Home and Away offers a sobering view into casualties in Iraq and Afghanistan, since 2001.

On the left is a map that shows hometown locations, and on the right is a map of casualty locations. The two maps are linked such that you see where people are from and where they served. Linked filters on the bottom show distributions of age, location, and date. Select or search for an individual to see further details. Friends and family are also able to submit fond memories of fallen loved ones.

Altogether, the interactive provides a connection between the data and the people behind it. See the full piece on CNN.

It’s not easy keeping up with what’s going on around the Web. Trending topic here. Another topic there. Zoe Fraade-Blanar, a graduate student at NYU ITP, hopes to lessen the pain with Current: A News Project.

Through a combination of data from Google Hot Trends and cross-references via Google News, the last 24 hours of memes are charted over time. The focus is on providing a tool that allows journalists to report news that matters, without sacrificing the reader traffic that comes in for videos of cute puppy dogs.

News relies on soft stories like horoscopes, celebrity gossip and restaurant reviews to subsidize the important but less sensational stories that keep democracy running. At base, any solution to News’ present problems must address the balance between the hard news we need and the soft news that drives advertising dollars. By visually anthropomorphizing the capricious nature of public attention Current can spotlight these missed opportunities in news coverage.

It’s still rough around the edges, and I’m not really digging the whole amoeba aesthetic, but I could see how this might be useful. Next steps: provide a way to focus on specific topics, incorporate Twitter trends, and smooth out the interaction.

Try it out for yourself (available for Mac and PC), and toss your thoughts in the comments below.

[via ReadWriteWeb]

I’m having more fun putting random stuff into graphs than I care to admit, but it’s my prerogative, and I can do what I want, so ha. In something of a Data Underload, special edition, I played with famous science fiction quotes for Sci Fi Wire. My favorite is obviously from Back to the Future, the greatest movie of all time. Check out the rest at Sci Fi.

Moritz Stefaner, whose work we’ve seen a few times here on FD, just released his code for Elastic Lists (in Actionscript).

For those unfamiliar, Elastic Lists builds on the idea of faceted browsing, which lets you sift through data with multiple filters. Think of when you search for an item on Amazon. In the initial results, filters for price, brand, and category rest in the sidebar. Similarly, Elastic Lists lets you browse data on multiple categories, but with more visual cues and animated transitions.
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When you ride your bicycle around, I bet you always wish for two things. First: “I wish this was electric so that I didn’t have to pedal so much.” Second: “I wish I could use my bicycle as a data collection device.” Well guess what. Your dreams have come true. The Copenhagen Wheel, conceived by the MIT SENSEable City Lab, will do just that. With everything rolled up into one hub, a quick and simple installation turns your plain old bicycle into an electric data collection device.
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In a different look to the let’s-map-geotagged-photos idea, photographer Eric Fischer maps picture locations of major cities in the world.

The maps are ordered by the number of pictures taken in the central cluster of each one. This is a little unfair to aggressively polycentric cities like Tokyo and Los Angeles, which probably get lower placement than they really deserve because there are gaps where no one took any pictures. The central cluster of each map is not necessarily in the center of each image, because the image bounds are chosen to include as many geotagged locations as possible near the central cluster. All the maps are to the same scale, chosen to be just large enough for the central New York cluster to fit.

Additionally, trace color indicates mode of transportation. Black is walking, red is bicycling, and blue is moving by motor vehicle. From what I gather, photos either come straight from Flickr or a teamed group of people. Unfortunately, that’s all I can find though. Some more explanation would probably make these a lot more enjoyable. Nevertheless, they’re nice to look at.
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Bluemoon Interactive, a small codeshop, maps touristiness, based on uploads to Panoramio, a site where people share photos of their favorite places. Yellow indicates high touristiness, red is medium touristiness, and blue is low touristiness.

Europe is much brighter than the rest of the world. The coasts of the US has got some brightness, along with Japan and some of the coasts of South America.

The question is are we really seeing levels of tourism, or are we looking at who uses Panoramio? I’m inclined to say the latter, simply because all of Europe is so crazy bright.

[via Information is Beautiful]

Information Architects just released their annual Web Trends Map, but it’s not about the subway and URLs this time around. Instead, it focuses on the 140 most influential Twitter users – the Cosmic 140 – based on list volume. Here are your top five:

1. Barack Obama (@BarackObama)
2. Lady Gaga (@ladygaga)
3. CNN Breaking News (@cnnbrk)
4. Taylor Swift (@taylorswift13)
5. Pete Cashmore (@mashable)

How about those American values?

As you can guess from the name, the layout and design revolve around a solar system metaphor. Founders rest in the middle, influential tweeters rest on the outer orbits, and followers are shown with surrounding edges. The longer a person has been a Twitter user, the closer to the middle he, she, or the company appears. The more a person is listed, the larger the white circle, and the more followers, the larger the surrounding transparent circle. Finally, people are placed on the 360° by category (e.g. entertainment or politics).
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John Allen Paulos, a math professor at Temple University, explains, in the New York Times, the importance of the before and after of when you get that data blobby thing in your hands.

The problem isn’t with statistical tests themselves but with what we do before and after we run them. First, we count if we can, but counting depends a great deal on previous assumptions about categorization. Consider, for example, the number of homeless people in Philadelphia, or the number of battered women in Atlanta, or the number of suicides in Denver. Is someone homeless if he’s unemployed and living with his brother’s family temporarily? Do we require that a women self-identify as battered to count her as such? If a person starts drinking day in and day out after a cancer diagnosis and dies from acute cirrhosis, did he kill himself?

In a nutshell, statistics is a game of estimation. More often than not, the numbers in front of you aren’t an exact count. They could easily change if you shift the criteria of what was counted. As a result, there’s always some amount of uncertainty attached to your data, and it’s the statistician, analyst, and data scientist’s job to minimize that uncertainty.

So the next time you see a list of rankings like “fattest city” or “dumbest town,” don’t take it for absolute truth. Instead, think of it as an educated guess. Similarly, when you analyze and visualize, remember the context of your data.

Catch Paulos’ full article here.

This might shock you, but many movies are not filmed on location. Yeah. Sometimes they’re filmed in completely different countries. Sorry, but it’s time you knew. This map from Paramount Studios, produced in 1927, showed investors where movies could shoot, instead of going to the actual places. Does your movie take place in Venice, Italy? No problem, head down to southern California. How about the Mississippi River? Check out the Sacramento River.

[via A Whole Lotta Nothing]