Yule Heibel's personal annotations on this page
James Turner interviews Andrea Vaccari of MIT's SENSEable City Lab about using internet and mobile technology data (generated by citizens in their day-to-day lives) to figure out how "digital technologies are evolutionizing the way we live in cities." (Not sure about turning EVOLUTION into a verb...)
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JT: In a future world where this is more pervasive and available rather than being a one-shot, how would you see urban planners and governments using this data?
AV: Well, for the urban planners, there is a big, big revolution going on. What happens today is that policies and plans are thought by assumptions. And their effects and imports can be evaluated only after a long time that they are implemented because, again as it was seen before, gathering this information is expensive. It's costly. It's cumbersome. So it's really impossible to get this information in real-time. What is going to happen is that instead of planning the city, the urban planners would actually have to program the city, to configure [it] in real-time because information will flow in real-time. So if you change the direction of the one-way road, you will see almost immediately what the effect on traffic is. If you close an area to cars, you can see immediately what will happen into the mobility in general. And if you create public spaces in a place rather than another, you will see immediately how people will react to that.
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I recently saw some comments about our work that were asking what's the function of these visualizations. And I have to say they are very useful. And they are extremely important in two different ways. On one side, yes, they are helpful to inform the citizens to educate, in a sense, the public to understand this kind of information; to make them understand that their actions build up on an overarching dynamic system which is the city that really is built of individual choices. But these individual choices emerge as one unique entity which is the city again. So as we somehow try to explain how financial markets work by showing some graphs or charts at the end of the news on TV or on newspapers, I think that we will have to do the same to inform the public about these issues and to let them understand what it means. On the other side, these visualizations are extremely helpful and I have to say successful in helping those who are stakeholders in this revolution, as I was saying before, which includes telecomm operators or municipalities in getting interested into this analysis, in understanding the potential. And really by seeing this data visualized, the decision-maker can grasp it. And these visualizations helped us collecting some of the data that we then used for our quantitative analysis.
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Well, basically, our major datasets are on one side cell phone activity and on the other side, Flickr pictures. They are not the only ones of course. But they are the two best examples of what we call digital shadows and digital footprints. Digital shadows are all of those data that are gathered by the interaction and conscious interactions of the user with pervasive systems. Digital footprints, on the other side, are explicitly released information about the behavior of citizens in the city. Flickr pictures are publically available online.
And a good deal of those is available and geotagged. So you can download them and see where they were taken. Since you know also the user that took them and you know, for example, his or her nationality, you can really see how people flow within a specific area from the level of the nation to the level of a city, back down to the level of a specific area within the city. And you can see where most of the pictures are taken: what are the hotspots, what kind of temporal signature is in specific place so whether tourists go more in the morning or in the afternoon.
And more interestingly, you can see flows. You can see where people go to take a picture first and where they go next. And all of these places are interconnected with each other.
This link has been bookmarked by 3 people . It was first bookmarked on 17 Apr 2009, by someone privately.
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Andrea Vaccari: Sure. The SENSEable City Lab is a recent initiative; a new initiative of the Massachusetts Institute of Technology which focuses on studying how digital technologies are evolutionizing the way we live in cities. And, therefore, how we can leverage these technologies; how we can make use of it through understanding how cities are using it; how we can design better cities. And then we can create cities that are more sustainable, more livable and automatically more efficient.
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What we are trying to do is to leverage the pervasive systems that enhance our cities today. And I'm referring to telecommunication networks, wireless networks, transportation systems or any other sort of digital system that interacts on a daily basis -- on a real-time basis -- with the citizens. What happens is that with these systems, interactions between the user and the system creates logs of their activity. And these logs can be used to understand the urban dynamics, to understand how people move in living cities and how cities themselves evolve in time.
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jumi ramJames Turner interviews Andrea Vaccari of MIT's SENSEable City Lab about using internet and mobile technology data (generated by citizens in their day-to-day lives) to figure out how "digital technologies are evolutionizing the way we live in cities." (Not sure about turning EVOLUTION into a verb...)
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Yule HeibelJames Turner interviews Andrea Vaccari of MIT's SENSEable City Lab about using internet and mobile technology data (generated by citizens in their day-to-day lives) to figure out how "digital technologies are evolutionizing the way we live in cities." (Not sure about turning EVOLUTION into a verb...)
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JT: In a future world where this is more pervasive and available rather than being a one-shot, how would you see urban planners and governments using this data?
AV: Well, for the urban planners, there is a big, big revolution going on. What happens today is that policies and plans are thought by assumptions. And their effects and imports can be evaluated only after a long time that they are implemented because, again as it was seen before, gathering this information is expensive. It's costly. It's cumbersome. So it's really impossible to get this information in real-time. What is going to happen is that instead of planning the city, the urban planners would actually have to program the city, to configure [it] in real-time because information will flow in real-time. So if you change the direction of the one-way road, you will see almost immediately what the effect on traffic is. If you close an area to cars, you can see immediately what will happen into the mobility in general. And if you create public spaces in a place rather than another, you will see immediately how people will react to that.
-
I recently saw some comments about our work that were asking what's the function of these visualizations. And I have to say they are very useful. And they are extremely important in two different ways. On one side, yes, they are helpful to inform the citizens to educate, in a sense, the public to understand this kind of information; to make them understand that their actions build up on an overarching dynamic system which is the city that really is built of individual choices. But these individual choices emerge as one unique entity which is the city again. So as we somehow try to explain how financial markets work by showing some graphs or charts at the end of the news on TV or on newspapers, I think that we will have to do the same to inform the public about these issues and to let them understand what it means. On the other side, these visualizations are extremely helpful and I have to say successful in helping those who are stakeholders in this revolution, as I was saying before, which includes telecomm operators or municipalities in getting interested into this analysis, in understanding the potential. And really by seeing this data visualized, the decision-maker can grasp it. And these visualizations helped us collecting some of the data that we then used for our quantitative analysis.
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