Posts tagged data
In the latter half of 2011, I offered to help Nicholas Felton spec out an iOS app for collecting survey and ambient data throughout 2012 for his next iteration of his Annual Report. Halfway through our requirements discussion – about the time I realized the app a) wouldn’t be public and would be b) would be a really fun challenge with a wholly unique use case – I offered to build the app myself. I’m sure we’ll share more details later, but for now Felton’s final designs speak for themselves.
4,739 reports later, the results are stunning.
We use MapBox and the tools they create often at PlaceIQ. No one else seems to better understand the difficulty in presenting and analyzing spatial data better than MapBox.
Adding access to satellite imagery is great on its own, but the ability to customize the images themselves is almost essential. Toning down the colors and subtleties of sat images lets overlay data pop while still having the real world reference layer. Only people who’ve agonized over displaying spatial data would recognize the need for these adjustments.
The sat filter presets they launched today are great starting points. Like Instagram’s filters, they allow us to quickly tweak the imagery to help us more clearly communicate the story in the data.
Every human in the United States. All 308,450,225 of them.
Made by Brandon Martin Anderson with US Census data. Click through for a zoomable map. The details are stunning.
According to GNIP, Oreo’s Gay Pride work spurred huge interactions on Tumblr, and yet when you look at Twitter’s numbers there wasn’t a blip.
The conclusion I’d draw from this is that Twitter, at a high, numerical level, renders as a static drone. It’s so big and messaging is limited in form that spikes are limited, especially when the story is complicated or involved imagery. Has it always been this way or is this a product of its growth?
I’m not posting this chart to make a comment about the iPad’s dominance, but rather to applaud Chitika’s visualization tactic. Rather than include iPad figures as a giant bar, dwarfing all the others into a indistinguishable scale, Chitika chose to absorb the iPad’s performance into the Y axis.
I think this allows the chart to pull more weight: we can both understand how other tablets stack up against each other with some nuance and get that oh damn the iPad is dominating moment when we realize it’s factored into the scale itself. Including a dominating bar would only give you the oh damn, while omitting the bar entirely would only give you the also-ran nuance.
In summation: if you have a chart with an overwhelmingly strong signal, make the dominant datapoint the scale against which all others are measured. (Via GigaOm)