Below the Tip of the Urban Data Iceberg

Posted: April 8th, 2009 | No Comments »

Data mining artist Andrea Vaccari gave a thorough interview to ZDNet on his current investigation at MIT SENSEable City Lab also providing context of the lab’s current endeavors. He starts of by argumenting on the necessity to produce quality visualizations responding to the skeptics that call it “info-porn“. I found myself defending the necessity of the urban demos produced at SENSEable to attract attention, stimulate the dialogue and stretch the imagination. Yet, this is only the tip of the iceberg of the work produced in Cambridge that strongly relies on the experience and data generated during the demos to produce scientific content. The opacity of the research review process and publication venues, does not often allow to get a glimpse of the research outcomes. So Andrea goes at it and gets specific on the type of contributions we can expect form the analysis of city-scale data. He takes example of the project in the context of the New York City Waterfalls we collaborated on to describe how the analysis of urban dynamics can become evidences of the evolution of the attractiveness of the most popular areas of a city. Other of his works aim at identifying unexpected events and assist public authorities and first responders.

Andrea recently presented the lab’s work at Etech (slides) where is seems that the buzz was on the fusion of sensor data with social data traffic that “to improve life“. Beside this honorable goal, I am dubious that this is purely reachable with data mining, machine learning to networks analysis and statistics. But maybe the current conclusion of my dissertation plays a bad influence on me.

Relation to my thesis: Andrea describes very well the lab its approach and projects I had the chance to share back in my SENSEable days. The open question that he leaves at the end of his interview are up my alley. Currently writing the conclusion of my dissertation, I take advantage to draw the implications of my work and discuss “human side of urban data” and what it means in context of urbanism; discarding a pure data-driven urbanism and sketching something I would call human-based urbanism, an approach mixing quantitative and qualitative data analysis.