Weaving a Patchwork Map ... in Real Time

We did something a little creative and unique at WNYC this past election night: We mapped the vote by "community type."

This revealed the diversity of the vote across New York State -- from the cities to the suburbs, boom towns and "service worker" centers -- in real time, on the air and on the WNYC home page.

And the diversity is striking. Despite Democratic wins in every statewide race, the Republicans running for state attorney general and comptroller "won" every community type outside "Industrial Metropolis" and "Campus & Careers" counties.

Patchwork Nation's Dante Chinni talked about this on air during WNYC's coverage election night, and has written more about it since.

The live map was a mashup of Patchwork Nation's unique take on the nation and the Associated Press's live vote totals. At the request of WNYC, Patchwork Nation programmers dove into the AP test results and quickly wove them into a new map based on PN's existing county maps -- customizing them for the event and adding real-time percentages by community type.

Bringing the Threads Together

In the months before the election, I had wondered how we might better understand the early returns -- those that come in typically between 9 p.m. and 10:30 p.m. -- which often don't match the final results. I wanted more clarity.

At a Hacks/Hackers Open-Source-a-Thon, I started playing with the election data with help from Al Shaw (then at TalkingPointsMemo, now at ProPublica) and Chrys Wu (of Hacks/Hackers and ONA fame).

That evolved into a little program I wrote in Sinatra that generated vote-total map at the left, shading counties darker as more of their precincts reported. It also helped me better understand how the data were structured, how to retrieve the numbers and what it might take to make a live map.

So when Chinni asked if WNYC had any county-level data sets we'd like to put through the Patchwork Nation treatment, I had the perfect candidate.

NYC Taxi Visualizations: The Pulse of the City

Fantastic presentation of GPS data from New York City Taxis in the New York Times today. So many stories embedded here, giving a wonderful sense of the city.

The ability to "play" the data is especially key. And the treatment itself hits all of my buttons. You just get it.

Beautiful.

The Secret Decoder Ring

Today our education reporter had a bunch of data from New York State she was trying to match to schools in New York City. But the school codes used by the two governments look radically different.

For example, PS 15 on the Lower East Side is known to the state as 310100010015; the city calls it 01M015.

I once made a nifty formula to make the conversion(!), but a more straightforward and official approach involves the Excel spreadsheet found here. It lists all of the city schools, along with their addresses, various codes, and more. For a data cruncher, that's a secret decoder ring.

What made me smile was that the only reason I knew this document even existed was because of a little prototype I tried during the first swine flu outbreak. That experiment wasn't robust enough to make it beyond this blog, but it taught me a lot ... including where to find this ring!

Movies & Demographics

What a great visualization of Netflix movie-rental data from the New York Times! Love how you can see how different movies play across the city.

It's even more interesting when you know something about the demographic makeup of the zip codes. Look how the Harlem River between upper Manhattan and the South Bronx is a bright dividing line for almost every movie.

How about a mashup that would reflect this info and demographic data simultaneously?


(tip via Nate Westheimer @innonate)

Super Simple Mapping Tool

Making collaborative maps is easier than ever. But maybe not quite easy enough.

One of the projects I'm working on at the moment is a super-duper-simple tool to help public radio and television stations (and pretty much anyone else) collect and map local information from their audience.

We're in the design phase right now, and we've mocked it up for feedback. The video is below.

Whaddya think? Let us know!

Paint Sticky Data (Please)

I'm into info. I want it accurate, relevant and clear.

On the radio, we try to paint clear, understandable, and journalistically-sound images of the mind -- the vivid mental pictures you see while listening to good storytelling.

Actual images can tell rich stories, too. The best photojournalism certainly does. Some pictures hit you in the chest.

But images drawn from data -- infographics, or visualizations -- rarely tell a story so well.

And they almost never hit me in the chest.

Why not? With all of the technology available, why can't we create really good visualizations that project understanding, timeliness, utility and ... dare I say ... stories?

I'm on the lookout. And I'm defining what I want to see.

For that definition, I've made a checklist based on one of my all-time favorite books, Made to Stick, by Chip Heath & Dan Heath (Random House, 2007). The initial words come from their Six Principles of Sticky Ideas; the rest is my application of their concepts.

For me, the best information images are ...

Simple: Non-geeks can absorb it within a few seconds
Unexpected: It fills a gap in our knowledge
Concrete: It takes advantage of our senses and understandings
Credible: It is journalistically sound, from a trusted source, without bias
Emotional: It hits you in the chest, you feel the data
Story: It tells one

And I'll add one more:

Relevant: It is timely, current and useful

Got examples that ring all seven bells? Maybe even four? Share them in the comments here or email me: john (at) designAgitator.com.

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The map detail above is from my favorite example at the moment, which is on Slate. Jump over there, take a look, and then run it through the checklist:

Simple? Once you know that blue is jobs gained and red is jobs lost, you're set. Just press play.
Unexpected? Seriously so. The speed of change is amazing.
Concrete? The familiar map orients me at a glance; I respond quickly to the circle sizes, colors and densities.
Credible? Bureau of Labor Statistics, Slate.
Emotional? Oh yeah. I saw someone actually shiver while watching it.
Story? Definitely.
Relevant? Yup.

Rings my bell.