What Big Data Means For Big Cities : 13.7: Cosmos And Culture Big Data promises a future where our Big Cities become more flexible and responsive to human needs, argues commentator Adam Frank. While danger may lurk in the data sets, the fact is that we may need to mine Big Data for solutions to our everyday problems.
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What Big Data Means For Big Cities

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What Big Data Means For Big Cities

What Big Data Means For Big Cities

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The Operations Center in Rio speaks to one promise of the smart city: command and control. But smarter cities are also about using data to help make a city more efficient. These days, there's more data than ever just waiting for us to analyze it: Big Data. NPR blogger and University of Rochester astrophysicist Adam Frank joins us now for a scientist's view of how a city might benefit. Hey, Adam.


BLOCK: And, Adam, I gather you're in a spot where you can easily illustrate some of what we're talking about. You're on the street in Rochester, New York. And explain this buzzword that we're hearing, Big Data, and why you're so interested in it.

FRANK: Well, to understand all the excitement about Big Data, you need to keep just one idea in mind, and that's digital breadcrumbs.

BLOCK: Digital breadcrumbs. What's a digital breadcrumb?

FRANK: Well, they're basically the electronic traces in ones and zeroes that we've all been leaving, you know, from cellphone location records to grocery store shopping choices, even to Facebook posts. Last year, we all generated so much data that it would take about 60 billion iPhones to hold it all. That's a lot of information, and it's all out there, getting stored and being processed somewhere by super fast computers.

Now, I've been using supercomputers my whole life, but what's new about Big Data is that rather than using equations to generate wads of information, with Big Data, all that information is actually coming from the world itself. It's the real world, and that opens up really profound new possibilities.

And to see what I'm talking about, you could go to Google Maps right now and look up Highland Hospital in Rochester because that's where I'm standing in front of.

BLOCK: OK. Highland Hospital, bordered by South Avenue.

FRANK: So now turn on that traffic feature that's up on the upper right.

BLOCK: OK. And now I'm looking at South Avenue, and it shows me yellow lines on South Avenue, indicating what, slightly stalled traffic?

FRANK: Yeah. They tell - it's telling you basically traffic is not completely flowing freely. And the interesting thing about that is I can see it right here in front of me, but you, who are hundreds of miles away, can also see it. And that's because of Big Data.

BLOCK: And how is that data turning into this traffic map that I'm seeing? How are they getting this picture?

FRANK: Right. That's the amazing thing, really. So what's happening is that Google is getting the traffic information basically from cellphones. It's tracking how the mobile phones are moving. And it's a case where the data is simply available on - and it's the digital breadcrumbs that we're all leaving.

So a city - or Google in this case - could actually, you know, buy up that data and use it to monitor traffic. But you can do even more than that. And this is really the amazing thing about Big Data, is that you can take that traffic data and use it to find patterns and draw conclusions about how things work when you combine it with other kinds of Big Data.

For example, you could look at those traffic patterns and see if there's any correlation, say, with the electricity use of the people in this neighborhood or the shopping patterns of the 18 to 28-years-olds in this neighborhood.

All that data is out there, and it's all ready to be mined to be able to tell us how the world works. And then, of course, there's that other big elephant in the room of Big Data: social media.

BLOCK: And how would that work out? And how would a city benefit, say, from data gathered through social media?

FRANK: All right. Well, I think a great example of this would be health. So right now, I'm here by Highland Hospital. And to make this point, I'm going to walk into the emergency center right here.


FRANK: OK. Well, one of the reasons I'm in the Highland Hospital right now is that, you know, I'm looking at people basically talking to their doctors. And those doctors are collecting information about who's sick and how.

And the old way of doing things is you'd take all that information, put it together, and then you'd know how many people had the flu last week or last month.

But with Twitter, you can actually look at tweets and see who is reporting that they're being sick right now. So a colleague of mine at the University of Rochester, Henry Kautz, is mining Twitter data to find out who's typing in I feel sick. And using that data, they can actually watch the spread of the flu from one neighborhood to the other.

So they use these digital social networks to map out real networks of human contact and its contagious consequences. So think how powerful that could be. Maybe in the future, you're going to get a tweet at some point telling you that you were in a room yesterday with someone who had the flu, so you should drink lots of fluids and get more sleep.

BLOCK: You know, it seems like there would be lots of pitfalls there, right? So, I mean, you're not going by an official medical diagnosis at that point. You're going by somebody saying, hey, I think I have the flu, on Twitter.

FRANK: Well, you know, that's the thing. These kinds of Big Data uses of social media are just beginning, and there's going to be a lot of mistakes. But they hold enormous promise that perhaps we can design our cities to be more responsive to human behavior as its occurring.

BLOCK: What do you think the big takeaway is here, Adam?

FRANK: Well, there's enormous promise and enormous perils, really, that's going on. But I think the important thing to understand is that, you know, urban centers have always been engines of information, and hidden in all that real-world data are patterns in the way human beings go about their urban business.

So the hope is that we'll be able to use Big Data to draw new correlations that will help city officials, you know, make more effective cities, and ultimately make them more sustainable. And, of course, since 85 percent of all people are going to be living in cities by 2050, building smarter, more efficient cities has got to be the part of the solution to the problem. You know, the unintended consequences are also going to be out there, and that's the other part of what we're going to have to deal with.

BLOCK: Right. Because with Big Data, of course, come really big concerns about privacy.

FRANK: Exactly. All those digital breadcrumbs we're leaving allow people to find us and see what we're doing.

BLOCK: That's NPR blogger and astrophysicist Adam Frank talking with us from Rochester, New York. Adam, thanks so much.

FRANK: Oh, thank you.


Next Tuesday on MORNING EDITION, the city's project goes to a Spanish city on the cutting edge of urban innovation. You can find all the stories at our website, npr.org/nprcities, and you can follow the project on Twitter, @nprcities.

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