Imagining The Data-Driven City

Yesterday I was talking with Edd Dumbill, who runs the O’Reilly Strata conference, about big data. Edd said, “I think we’re moving out of the phase of data as pretty pictures and into a phase of data as something actionable…. We (at Strata) want to enable companies to become data-driven companies.”

That was an interesting observation – it’s the shift from data-as-pretty-picture to data-as-actionable-stuff that enables a company to become data-driven.

And of course that notion applies not just to corporations but to cities as well, right? Cities can become data-driven cities by turning all of the data they churn out daily into something actionable.

This is beginning to happen bit by bit, right before our eyes. And it’s exciting to watch. But it can and will go much farther.

Right now we’re starting to get actionable realtime data in the form of things like Google Traffic, that shows us on a map which roads around us to avoid. That is cool – the kind of thing we dreamt of having a few years ago.

We also have apps like Where Are The Geeks? that shows a real-time map of Foursquare checkins in Paris. If you’re a geek in Paris you can look at that and decide where you want (or where you don’t want) to go hang out with other 4sq users. Imagine that for any demographic – being able to see exactly where your own tribe is right now.

And two years ago at DIYcity we created an open-source web app called SickCity, that monitored localized conversation on Twitter for sickness keywords like fever and chills in order to detect spikes in conversation about flu. The idea was that sudden spikes in conversation about flu symptoms might indicate spikes in actual flu locally, and act as an early warning system for communities. A real-time disease detection system for your own city or neighborhood.

These are three pretty basic examples of actionable data being put to use at the city level. Very early-stage stuff.

Imagine how much farther you could take this. Imagine a fully data-driven city, a city that can reflect on all of its own information output, in realtime, and alter its own behaviors based on the insights it gleans from that.

This could happen at the macro level, with city governments and offices acting on all sorts of realitime data, as well as at the micro level, with individuals acting on data immediately around them. And the macro could inform the micro, and vice-versa.

What would this look like? How could it make cities work better at the macro level? How could it make people’s day better at the micro level? How could it make cities and communities more sustainable, more efficient, more able to adapt to sudden challenges?

These are questions that we’re about to see more and more answers to. Because increasingly we’ve got the data in place to get started – the government data, the personal data, the geolocated data, the data from various instruments and readers – and increasingly that data is being normalized and structured for easy use. The next step, as Edd says, is to make all of that data actionable. Once that begins to happen, we’re on our way to the data-driven city.

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