The New York Times does it again with this succinct look at tech IPOs. It begins with looking at everything through the lens of when Google’s IPO in 2004, which, at the time, was considered huge. The next screen adds Facebook to the mix which dwarfs everything prior. It continues on to show the first day of trading pop and where things landed long term (3 years post-IPO).

It’s a very interesting view of IPOs and could actually be a good financial analysis tool with a few more features.

Help is a drug company that offers you less. Less active ingredients, less waste, less confusion, less greed. Its tongue-in-cheek website has a map of its latest sales data called “What’s wrong U.S.?” A bar chart for each state shows how many people are buying products for particular maladies.

So why are the inner northwest states having problems sleeping? My guess they’re up late worrying about gay marriage.

Garbage in, garbage out the old adage goes. Nigel Hawkes, Director of Straight Statistics, describes a sort of statistical whistleblowing letter to the British Medical Journal.

A team from Imperial College found that in 2009-10, nearly 20,000 adults were coded as having attended paediatric outpatient services, and 3,000 patients under 19 were apparently treated in geriatric clinics. Even more striking, between 15,000 and 20,000 men have been admitted to obstetric wards each year since 2003, and almost 10,000 to gynaecology wards.

It’s hard to put your faith in analysis, visualization, policy, and anything else that comes out of data with reports like these. With human error being a known issue, we have to find better ways of inputting and double-checking data. Unfortunate mistakes at the outset only lead to bigger problems down the line.

The unassuming little Descriptive Camera made me rethink data. This project by Matt Richardson was on display at the ITP Spring Show. The basic premise is that you take a photo and the camera spits out a textual description of what it sees. The results are remarkably accurate, detailed, and humorous.
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What is Missing? by Maya Lin seeks to raise awareness about the mass extinction of species. It has a beautiful interface. The world map is black on a sea of black. Your mouse acts as a sort of flashlight layered between land and water, showing you glimpses of familiar coastlines and allowing you to select dots that tell the stories of extinction.
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Yesterday I visited the ever popular NYU ITP bi-annual show which is a showcase of the students’ experimental and ingenious interactive work.

I stopped to talk to data visualization student and self-tracker, Doug Kanter, about his work. His first and smaller piece was about the war in Iraq. The image above depicts the number of wounded US soldiers by state (and territory) using the red stripes. The stars show the number of soldiers killed. I’m sure we could quibble about labels and where the bar chart starts, but to me, the tattered appearance of the flag created by data about war is very arresting.
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I’m going to be away for a couple of weeks, with little to no Internet access most of the time, so I’ve asked Kim Rees to step in while I’m gone. She’s the co-founder of Periscopic, one of my favorite information visualization firms, and she was the technical editor for Visualize This. You’re in good hands.

You can follow her at @krees.

Be good, and see you all when I get back.

She’s all yours, Kim.

Nicolas Rapp dives into the patterns and growth of worldwide shipping in a six-page spread for Fortune Magazine.

Nearly 90% of all goods traded across borders travel, in part, by sea. Typically a ship will undertake six voyages a year. The fastest-growing routes are between ports in Asia, while goods moving out of that continent account for 43% of all maritime trade, according to IHS Global, an economic forecasting firm. Today the most heavily trafficked sea route is between China and the West Coast of the U.S. The total value of goods that travel from China to the U.S. is four times that of those on the return trip—a clear symbol of America’s trade deficit.

Despite a gap of a few centuries, the routes today still look a lot like the ones from the 18th century.

I’m pretty sure I’m not in their target audience, but my main takeaway from this video is that now, with easel.ly, you don’t need time, money, or skill to make quality infographics. And the prezi-like video seems fitting.

Maybe I’m just stuck in my ways, but I’m having trouble getting on board with these tools. Easel.ly, for example, provides themes, such as the one on the right. There’s a guy in the middle with graphs around him and pointers coming out of his body. You get to edit however you want.

So in this case, you start with a complete visual and then work your way backwards to the data, which I’m not sure how you can edit other than manually changing the size of the graphs. (Working with the interface takes some patience at this stage in the application’s life.) It’s rare that good graphics are produced when you go this direction.

Instead, start with the data (or information) first and then build around that — don’t try to fit the data (or information) into a space it wasn’t meant for.

Or maybe there’s a lot more in store that we can’t see yet. Either way, right now, the application is rough at best.

Robert Groves, director of the U.S. Census Bureau, on the Appropriations Bill:

The Appropriations Bill eliminates the Economic Census, which measures the health of our economy. It terminates the American Community Survey, which produces the social and demographic information that monitors the impact of economic trends on communities throughout the country. It halts crucial development of ways to save money on the next decennial census. In the last three years the Census Bureau has reacted to budget and technological challenges by mounting aggressive operational efficiency programs to make these key statistical cornerstones of the country more cost efficient. Eliminating them halts all the progress to build 21st century statistical tools through those innovations. This bill thus devastates the nation’s statistical information about the status of the economy and the larger society.

A lot of the negative comments following the post are from people who have never used Census data, or any substantial amount of data for that matter, and have no clue how a dataset can feed into a model to make other estimates. Then there’s the people who don’t want to answer questions about their toilets. I wonder what their Facebook profiles look like.