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]

Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky provide a good overview of some of the more advanced data visualization techniques in ACM Queue:

This article provides a brief tour through the “visualization zoo,” showcasing techniques for visualizing and interacting with diverse data sets. In many situations, simple data graphics will not only suffice, they may also be preferable. Here we focus on a few of the more sophisticated and unusual techniques that deal with complex data sets. After all, you don’t go to the zoo to see Chihuahuas and raccoons; you go to admire the majestic polar bear, the graceful zebra, and the terrifying Sumatran tiger.

You’ve probably seen many of the techniques they present, such as stacked graphs, small multiples, and arc diagrams, but at the very least you’ll get the names and some brief descriptions of what you’re looking at, so you don’t have to call it the circly-thing-with-curvy-lines graph again.

Plus most of the examples were made with Protovis, an open-source toolkit for visualization, and you can grab the code to help you with your own visualization project.

[Thanks, @a_lo]

I love it when data, or in this case, tweets, finds itself in physical objects. There’s no reason data needs to stay plastered on our computer screens. Embed in the physical world as much as possible, I say. Haroon Baig, a communication designer in Germany, uses a clock that he calls Twitwee to cuckoo every time a tweet comes in matching a given query.

This would get annoying really fast as it is now, but with a more refined filter or event recognition, this could actually be pretty useful.

See Twitwee in action below.
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My many thanks to the FlowingData sponsors who help keep the gears turning and let me do what I do. Check ’em out. They do data right.

Tableau Software – Combines data exploration and visual analytics in an easy-to-use data analysis tool you can quickly master. It makes data analysis easy and fun. Customers are working 5 to 20 times faster using Tableau.

InstantAtlas – Enables information analysts and researchers to create highly-interactive online reporting solutions that combine statistics and map data to improve data visualization, enhance communication, and engage people in more informed decision making.

Want to sponsor FlowingData? Email me for details.

I’m not proud of this, but I know very little about what’s going on with these 2010 midterm elections. The New York Times just put up their election maps on the race though — for governor, House and Senate seats — so at least you have a way to get informed in a hurry.
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Everyone’s been bashing Flash lately and holding HTML5 up on a pedestal. This circular graph thing, for example, shows what a combination of HTML5 and CSS3 can do and what features are available in major browsers. That’s great and all, but as you can see there are still a lot of holes.

The most glaringly obvious hole is Internet Explorer – which supports practically nothing. This is nothing new. Anyone who’s designed a site to work in all browsers knows this. But as much as you hate Internet Explorer, you’re not going to block content for some 80 percent of visitors, right?

On top of that, Flash provides richer interaction than HTML5 right now, and it’s going to be like that for a while. A lot of the work from the New York Times is in Flash. Stamen Design uses Flash. A lot of great work has come out of Flash – not just cruddy MySpace pages.

Now I’m not saying HTML5 isn’t going to be useful. It will be and is in some areas. But in terms of visualization, Flash is still better.

In 1934, American architect Frank Lloyd Wright designed Fallingwater, a house built partly over a waterfall. A couple of years ago, Smithsonian Magazine listed Fallingwater as one of the 28 places to visit before you die. Cristobal Vila, who himself has a knack for pretty things, animates the imaginary design and construction of Wright’s famous building.

Watch it unfold in the animated video below. Warning: after watching, you will have a very strong urge to visit.
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I’m pretty sure all this Facebook stuff will blow over soon enough. Most people have changed their privacy settings by now. The rest don’t really care. Some people though simply have no clue that what they’re sharing with their inner circle is out on display for anyone to see. Openbook uses the Facebook search API to show these users. Search for a term or phrase and see the status updates of public profiles.
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People are up in arms about Facebook’s new privacy policies, partly because some information was forced into public view and partly because there are so many settings that figuring out what’s public and what’s private is confusing. Guilbert Gates of the New York Times clears things up with the above graphic. To put it simply: there’s a lot of stuff.
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No clue where this is from, but something seems sort of off, no? I guess we should take the title literally. By the numbers… only.

I’m going to give the benefit of the doubt though, and assume this was just an honest mistake. Here’s my guess about what happened. A deadline was coming up quick, and a graphics editor put this together to get a feel for what the final design would look like. He then saved it as a different file, and then went to work. Except when it came time to send the file to the printers, the editor sent the wrong file. Actually, now that I think about it, I’m surprised this doesn’t happen more often.

[via @EagerEyes]

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.