Esquire invited a handful of map-makers to represent the United States outside its borders.

Red state, blue state, big state, small state, north and south and east and west: How we define our similarities and differences with each other often comes down to where we see ourselves on the map of America. But what if we threw out the standard-issue version and started over with something new?

Esquire's online format doesn't do the maps justice though. A lot of the images are too small to see the details. In particular, don't miss Eric Fischer's high-resolution cartogram and Stamen's interactive on where the money went. Fischer's map shows density of geotags, but zoom in, and you can see major cities in detail. Stamen's map uses IRS data in a twist to the migration map, showing county-level monetary gains and losses.

[Esquire]

Nate Silver looks at past players who have scored 20 or more points, had 6 or more assists, and shot better than 50 percent in four or more games in a row. It's an illustrious list of all-stars, including Jordan, Bird, and Magic, with only a handful who were just so-so.

Like everyone else, I was skeptical. I saw him play with the Warriors, and it was never that impressive. However, watching last night's game against the Lakers it was hard not to buy in to Linsanity. We'll see if he can extend the streak tonight against Minnesota, but even if the Knicks do win, should we read that much into it? Remember, there aren't that many other scoring options on the Knicks right now, two of the past four wins were against horrible teams (New Jersey and Washington) and the other two, the Lakers and the Jazz, were teams just slightly above .500.

[Nate Silver]

In a tongue-in-cheek tribute to the Dancing Plague of 1518, Niege Borges illustrates dances from a number of shows and movies in his project of the same name. All of them available in print, including the Elaine dance from Seinfeld, Little Miss Sunshine, and Singin' in the Rain. [Niege Borges]

While we're on the topic of things moving on a map of changing camera angles, class project Taxi, by Tom McKeogh, Eliza Montgomery and Juan Saldarriaga, shows the movements of said vehicles in Manhattan, over 24 hours.

Geographic location data for the origin and destination of each ride is combined with waypoint data collected from the Google Maps API in order to generate a geographically accurate representation of the trip. We used data from taxi rides originating or ending in the neighborhoods of Lincoln center or Bryant Park. The visualization recreates a 'breathing' map of Manhattan based on the migration of vehicles across the city over a period of 24 hours, displaying periods of intensity, density and decreased activity.

I hope they do another iteration of this project. I bet they could do a lot more on the temporal side of things.

[Digital Urban via @kennethfield]

Even Westvang uses tax return data to visualize migration patterns of 300,000 Norwegians.

When running at full speed the visualization is clearly lacking in terms of salient features, yet I find it interesting. Then again, I like looking at Pachinko machines and waterfalls — processes comfortably stuck between the random and the ordered. When slowing the animation down and filtering for certain demographies it becomes more useful. At its best laymen, like myself, can visually perceive facets of the natioal Norwegian migratory process that before were only available through the statistical calculations of researchers in demography.

As you might expect, each particle represents a person moving from one ZIP code to another. The more people moving from point A to point B, the faster the particles move.

The most interesting bit, that I wish Westvan did more of, is closer to the end, when he shows a couple of demographic breakdowns. The older demographic tends to move shorter distances, and those with higher salaries shoot out from bigger cities. Hey Jon Bruner, something to keep in mind for your next iteration. Although I'm pretty sure the US doesn't make income data for every citizen publicly available like Norway does. What's that about?

[Even Westvan via @mariuswatz]

Web-based Analysis and Visualization Environment, or Weave for short, is open source software intended for flexible visualization.

Weave (BETA 1.0) is a new web-based visualization platform designed to enable visualization of any available data by anyone for any purpose. Weave is an application development platform supporting multiple levels of user proficiency — novice to advanced — as well as the ability to integrate, disseminate and visualize data at "nested" levels of geography.

It looks like everything is done through a click interface, and you can piece together modules and link them, etc. There is some setup involved, but there are a number of video tutorials and documents to get everything installed.

Source code also available on GitHub.

[Weave]

In a blend of data and storytelling, Jeremy Mendes and Leanne Allison dig into surveillance logs generated by a monitored grizzly bear between 2001 and 2009. The final work is a moving interactive documentary, Bear 71.

She lived her life under near-constant surveillance and was continually stressed by interactions with the human world. She was tracked and logged as data, reflecting the way we have come to see the world around us through Tron and Matrix-like filters, qualifying and quantifying everything, rather than experiencing and interacting.

Leanne Allison sifted through thousands of photos from motion-triggered trail cameras for this project. The grainy images gathered over the past 10 years by various scientists reveal the hidden life of the forest, played out by the animals and humans — including Bear 71 — captured covertly on film.

It begins with the capture of a grizzly, its tagging, and then release, as a first-person narrative tells a story through the eyes of the bear. You, the observer, are allowed to follow the bear and explore its environment on an abstract map, and somewhere along the way digital and the physical world melt together.

[Bear 71 via @wiederkehr]

Like something from of a video game, this graphic from The New York Times shows the most mentioned NFL players and coaches this season. Players are scaled approximately by the number of mentions between August 1, 2011 to February 1, 2012 on ESPN's SportCenter and Sunday NFL Countdown. The giant on the left is Tim Tebow, with 1,450 mentions. Bar graphs on the bottom highlight mentions over time for players of interest.

[New York Times]

Data science has been covered at length during the past couple of years, and we tend to think of it as a field of study just a couple of years older than that. Jeff Hammerbacher and DJ Patil have played roles in further propagating the term as an actual profession in roughly the same timespan. So I was surprised to come across this rarely-cited 2001 paper by statistician William Cleveland, Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics [pdf].

This document describes a plan to enlarge the major areas of technical work of the field of statistics. Because the plan is ambitious and implies substantial change, the altered field will be called "data science."

For those unfamiliar, Cleveland's work on graphical perception might ring a bell.
Continue Reading

Presidential candidates have raised $186 million up to now, according to the Federal Election Commission. The New York Times lets you compare the amounts raised by each candidate, over time and space. Simply select a candidate on the left, and another on the right to see how they match up. Fundraising by candidates from previous elections, at the same time of year, are also included for context.

While not the focus of the interactive, the distributions for donation size at the bottom seem to be especially telling.

[New York Times via infosthetics]

Birds move. eBird shows us how.

Understanding patterns of bird occurrence at continental scales has long been one of eBird's fundamental challenges. Only now, with 42 million records and ever more thorough coverage nationwide, is this becoming possible. Ongoing research at the Cornell Lab is currently producing cutting-edge graphics that we are pleased to share here. Day-by-day predictions of species occurrence allows these models to shine a spotlight on the most awe-inspiring of natural spectacles: the ebb and flow of bird migration.

Cutting edge? No. They are thorough though, with maps (in the form of animated gifs) for a large number of species.

[eBird | Thanks, Ed]

Diego Valle-Jones maps homicides and trafficking routes in Mexico.

To unclutter the map and following the lead of the paper Trafficking Networks and the Mexican Drug War by Melissa Dell, I decided to only show the optimal highways (according to my own data and Google Directions) to reach the US border ports from the municipalities with the highest drug plant eradication between 1994 and 2003 and the highest 2d density estimate of drug labs based on newspaper reports of seizures. The map is a work in progress and is still missing the cocaine routes, but hopefully I'll be able to add them shortly.

There's lots to look at and interact with here. To start, there are bubbles that cluster homicides by region and major highway routes in black.

Click on any bubble and you get a time series for the corresponding area, going back to 2004. Or if you like, draw your own polygon to see the time series for specific regions. Pointers on the time series highlight significant events. There's also a slider that lets you see numbers on the map for different years. A layer underneath the bubbles lets you see high density areas for marijuana, opium, and drug labs.

Take a look at the full map for yourself. This is nice work by Valle-Jones.

[Diego Valle-Jones | Thanks, Diego]

You would think that something so concrete, carefully recorded by authorities, wouldn't be too tough to tabulate, even if at a large scale. Not so.

Homicide is a "serious crime that many people are concerned with, it is well-measured, and it is to a large degree well-reported and -recorded," says Alfred Blumstein, a criminologist at Carnegie Mellon University. "That is not to say that there aren't a variety of ways for fudging the measurement."

Among the factors that cloud homicide numbers: gaps between police-reported numbers and counts by public-health organizations. The discrepancy is wide in many African countries and some Caribbean ones. The United Nations attributes the disparity to several factors, including definitional differences—whether honor killings should count—a lack of public-health infrastructure in some countries, and undercounting—possibly deliberate—by police.

I think this is something the common public often doesn't understand about data. The numbers are entered and analyzed on a computer, so it's easy to mistake data for mechanical output. It must be accurate, right? That's usually not the case though, especially when it comes to data collection outside a controlled lab setting.

The game always changes when humans are involved. Not everyone responds to surveys, definitions of events vary across organizations, estimation methods change every year, and the list goes on.

For those who do stuff with data, you have to deal with that uncertainty, and as data consumers, you have to remember that numbers don't automatically mean fact.

[Wall Street Journal]

I thought this riveting post on the New York Times Bits blog about the rise of the toilet texter deserved a graphic. Since their graphics department is no doubt busy with elections, I took the liberty. I am — the 91 percent.

I got the numbers straight from the Bits post, but you can download the full report from 11mark for all the demographics. You have to register though, and I didn't want to be the guy who creates an online account to just read a report on what people do while they make dooty. I have standards.

Yahoo is not what it used to be, but many parts of it are still alive and well. In a follow-up to their email interactive, Yahoo, along with visualization firm Periscopic, explores the popularity of articles that appear on the Yahoo homepage. It's a visualization that shows activity within the Content Optimization and Relevance Engine (C.O.R.E. for short).

The focus is on the center, which has the same layout as that of the stories on the Yahoo homepage. Story on top, and links to more stories on the bottom. Except in the interactive, you can see demographics of those who viewed the story. The slider on the bottom lets you go back up to 24 hours to see what was hot during each hour.

It gets more fun when you use the buttons on the left and right to view popular stories among age and gender cohorts and button on the right that let you see stories by categories. The rotating particles, each representing a clickable story, in the background provide a final flourish.

Oh, and extra nerd points for HTML5.

[Yahoo]

Data is hot right now, so as you would expect, more people are signing up and applying to learn about it. Quentin Hardy for The New York Times reports.

At North Carolina State, an advanced analytics program lasting 10 months has, since its founding in 2006, placed over 90 percent of its students annually. The average graduate’s starting salary for an entry-level job is $73,000. Its current class of 40 students had 185 applicants, and next year’s applications are already twice that. In 2009, Harvard awarded four undergraduate degrees in statistics. Two graduates went into finance, one to political polling and one became a substitute teacher. There were nine graduates in 2010, 13 last year. They headed into Google, biosciences and Wall Street, as well as Stanford's literature department.

And in 2011, just about everywhere.

[New York Times via @jsteeleeditor]

Priceonomics takes the association of fixie bikes to hipsters, and creates the Fixie Bike Index. After starting with New York, they branch out to national numbers.

In short, fixed gear bikes = hipsters, and New York boroughs that have more fixies per capita should have more hipsters per capita. We sampled our data to see the number of used bikes for sale per capita in each borough with the term "fixie" or "fixed gear" in the product title to create the Fixie Index.

I don't know about these numbers. I lived in Modesto for a year and don't remember people riding bikes — or hipsters, and riding your bike in Los Angeles kind of sucks.

[Priceonomics]

There are a lot of ways to collect your location, whether it's for journaling and personal reflection or for sharing with others, but it can be tricky making use of your data once it's stored behind company servers. OpenPaths lets you collect your data via iPhone or their just released Android app.

We inhabit a world where data are being collected about us on a massive scale. These data are being stored, analyzed and monetized primarily by corporations; there is limited agency for the people whom the data actually represent. We believe that people who generate data through their own day-to-day activities should have a right to keep a copy of that data. When people have access to their personal data in a useful format all kinds of new things become possible. We can become better consumers: for example, we can know whether a monthly rail pass makes sense for us, or which data-plan would be most economical for our smartphone usage. More importantly, when our personal data is readily accessible and under our control we can become active collaborators in the quest for solutions to important social problems in areas such as public health, genetics or urban planning.

You can easily view your data in the OpenPaths map interface, or download your data as CSV, JSON, or KML, and do what you want. There's also an API. Finally, if you choose to, you can contribute your data for researchers, artists, and techonlogists to create their own projects.

I just installed the mobile app. Looking forward to what happens next.

[OpenPaths]