the promise of urban science aaas annual meeting chicago, 02/15/14 steven e. koonin, phd director
TRANSCRIPT
The Promise of Urban ScienceAAAS Annual Meeting
Chicago, 02/15/14
Steven E. Koonin, PhDDirector
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Cities are (and will be) important
• Currently about 80% of the US and about 50% of the world population reside in urban areas, growing at over one million people per week.
• A city is a complex system of systems that must provide safety, health, housing, mobility, water, food, energy, interactions, connectivity
• New cities must be built wisely and existing cities must be refurbished, if not improved in dimensions such as efficiency, quality of life, and resilience.
When you can measure what you are speaking about, and express it in numbers, you know something about it; when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind. – Lord Kelvin, 1883
Urban Data• Urban data have been collected for millennia
sta·tis·tics (st-tstks) n. 1. The mathematics of the collection, organization, and interpretation of numerical data, especially the analysis of population characteristics by inference from sampling
From German Statistik, political science, from New Latin statisticus, of state affairs, from Italian statista, person skilled in statecraft, from stato, state, from Old Italian, from Latin status, position, form of government.
• Sparseness and quality have limited urban science – difficult to usefully measure the urban system, test hypotheses
• But new data technologies completely recast the study of cities– digital records, sensors, computing power, analytical techniques – unprecedented granularity, variety, coverage, and timeliness
Properly acquired, integrated, and analyzed, data can • Take government beyond imperfect understanding
– Better (and more efficient) operations, better planning, better policy
• Improve governance and citizen engagement• Enable the private sector to develop new services for citizens,
governments, firms• Enable a revolution in the social sciences
Environment
Meteorology, pollution, noise, flora, fauna
People
Relationships, location, economic /communications activities, health, nutrition, opinions, …
Infrastructure
Condition, operations
What does it mean to instrument a city?
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
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The CUSP PartnershipNational Laboratories• Brookhaven• Lawrence Livermore• Los Alamos• Sandia
Industrial Partners• IBM• Microsoft• Xerox• Cisco, Con Edison, Lutron,
National Grid, Siemens• AECOM, Arup, IDEO
University Partners• NYU/ NYU-Poly• The City University of New York• Carnegie Mellon University• University of Toronto• University of Warwick• IIT-Bombay
City & State Agency Partners• The City of New York
• Metropolitan Transportation Authority• Port Authority of NY & NJ
Buildings City Planning Citywide Administrative
Services Design and Construction Economic Development Environmental Protection Finance
Fire Department Health and Mental Hygiene Information Technology
and Telecommunications Parks and Recreation Police Department Sanitation Transportation
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
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Science “Users” Citizen Science, Quantified Community, Innovation District
Proj
ect 1
Proj
ect 2
Proj
ect 3
Proj
ect 4 …
Transit Utilities Health …
Domains (tbd)
Data Management, Data Curation, Data Analytics, Visualization, Geographic Information Systems, Machine Learning, Data Mining,
Modeling and Simulation, Sensing, …
Acquisition Integration Analysis
Dis
cipl
ines
(tbd
)CUSP Research Program Structure
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
Data Warehouse Facility
Overview• Omnivorous ingestion to a repository for NYC-related data
Objective and Goals • Make data interoperable, with proper multi-layered access protocols
Data • Data from City agencies on operations, schedules, maps, etc.• Will start with the open datasets• Will include proprietary data, social media data, CUSP-generated data• Working with the Mayor’s Office of Analytics • CUSP Chief Data Officer will oversee ethical, legal, and social issues
N = 1,150
Mean = 219.5
s.d. = 101.7
020
4060
80Fr
eque
ncy
0 200 400 600 800Weather Normalized Source EUI (kBtu/sq.ft./yr.)
Source: Local Law 84 Disclosure Data, Kontokosta 2013
Source Energy Use Intensity, Office Buildings, New York City
N = 7,505Mean = 137.9
s.d. = 46.8
020
040
060
080
0Fr
eque
ncy
0 100 200 300 400Weather Normalized Source EUI (kBtu/sq.ft./yr.)
Source: Local Law 84 Energy Disclosure Data, Kontokosta 2013
Source Energy Use Intensity, Multi-Family Buildings, New York City
Building Energy Efficiency
Kontokosta 2013
Local Law 84 Benchmarking Data
Kontokosta, 2013
Taxis as Sensors for NYCTaxis are sensors that can provide unprecedented insight into city life: economic activity, human behavior, mobility patterns, …
“What is the average trip time from Midtown to the airports during weekdays?'’ “How the taxi fleet activity varies during weekdays?’’“How was the taxi activity in Midtown affected during a presidential visit?'’“How did the movement patterns change during Sandy?”“Where are the popular night spots?”
Drop-off
Pick-up
Most drop-off’s occurred on avenues, most pick-up’s on streets
Lauro Lins, Fernando Chirigati, Nivan Ferreira, Claudio Silva, and Juliana Freire, NYU-Poly(Data obtained from TLC on June 6, 2012)
Visualization of TLC GPS Data (2011)
USDOT Off-Hour Deliveries Project: Taxi GPS Data
• GPS Tracking data from delivery trucks is limited for a network-wide analysis.
• Correlation between taxi travel times and truck travel times is statistically shown.
• Taxi-GPS data is used to supplement the truck-GPS data.
• Travel time savings are evaluated using taxi-GPS data.
USDOT Off-Hour Deliveries Project: Taxi GPS Data
Taxi GPS Data vs. Truck GPS Data
-Mean truck travel times fall into 90th -50th percentile of taxi travel time distribution.
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Privacy & Confidentiality BookConfidentiality and Data Access in the Use of Big Data:
Theory and Practical ApproachesThe book will identify ways in which vast new sets of data on human beings can be collected, integrated, and analyzed to improve urban systems and quality of life while protecting confidentiality. It will provide theoretical and practical foundations cities across the world can draw from to establish data access rules and data security procedures. Sponsored by CUSP, the American Statistical Association, its Privacy and Confidentiality subcommittee, and the Research Data Centre of the German Federal Employment Agency.
Lead EditorJulia Lane, American Institutes for Research
EditorsStefan Bender, Institute for Employment Research, The German Federal Employment Agency; Helen Nissenbaum, NYU; Victoria Stodden, Columbia University
Chapter AuthorsSteve Koonin, CUSP; Andrew Gelman, Columbia and Mark Hansen, UCLA; Alessandro Acquisti, Carnegie Mellon University; Theresa Pardo, SUNY Albany; Helen Nissenbaum, NYU; Kathy Strandberg, NYU; Paul Ohm, Colorado; Victoria Stodden, Columbia; Alan Karr, National Institute of Statistical Sciences and Jerry Reiter, Duke University; John Wilbanks, Sage Bionetworks/Kauffman Foundation; Cynthia Dwork, Microsoft; Alexander Pentland, MIT; Carl Landwehr, George Washington University; Peter Elias, University of Warwick
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
Create New Data Streams:Urban observatory
http://danielbachhuber.com/2010/11/19/empire-state-building-view-to-south-and-north/
Photo by Tyrone Turner/National Geographic
Other synoptic modalities: Hyperspectral, RADAR, LIDAR, …
Manhattan in the Thermal IR
199 Water StreetBuilt 1993 :: 998,000 sq ft
electricity, natural gas, steamLEED Certified
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
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Quantified Community (QC) FacilityOverview
• Fully instrument a defined district in NYC• Unique opportunity to partner with major new site in Manhattan• Deploy sensor network to monitor, measure, and analyze
‒ Physical infrastructure‒ Behavior and mobility‒ Environment and sustainability indicators
Objective and Goals • Long-term study of key performance indicators (KPI) and longitudinal study of
resident/worker outcomes• Test interventions/hypotheses
‒ Real-time monitoring and feedback evaluation; broadly application to NYC• Living lab for tech innovations
‒ Evaluate performance of new technologies in real-world context• Quality of life improvements through sense-model-intervene paradigm• Risk mitigation through dynamic monitoring of infrastructure, environment
‒ Enhanced opportunities for emergency response and resilience
What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
Students: Admissions Summary, MS Applied Urban ScienceCycle Dates: December 18, 2012 through June 30, 2013 (~6months)25 21% 27 36% 3.5
Inaugural Class Selectivity YearsAverage Age
Female Average Undergraduate GPA
20 48% 9 4 28%Undergraduate
DisciplinesInternational Countries
RepresentedYears Average
Work ExperienceWith Graduate
Degree
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What it takes to “do” urban science
• Multisector collaboration • Multidisciplinary collaboration
– “sensors to sociologists”• Acquire, integrate, exploit large diverse datasets while
respecting privacy• Ability to create new data streams• Deep studies of “millicities”• Students who will create the new discipline• A willingness to get one’s hands dirty with applications
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Among the Projects We’re Working On
• Multi-data correlations to improve city resource allocation
• Sound / Temperature / Pollution• Mobility• Novel sensing of public health• Building efficiency• Decision science
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Entrepreneurship & CommercializationCUSP’s commitment to fostering and promoting entrepreneurship reflects a
University-wide programmatic commitment to entrepreneurship.
Embedded in Learning: Entrepreneurship and Innovation• CUSP students study either change leadership/organizational behavior
or entrepreneurship and new venture creation
Embedded in Operations: Executives in Residence• Irving Wladawsky-Berger, Chairman Emeritus, IBM Academy of
Technology; entrepreneurship and science advisor, board member• Shelley A. Harrison, Senior Advisor & Head of Corporate Portfolio
Ventures at Coller Capital; entrepreneur, advisor
Embedded at CUSP: • 370 Jay Street includes 40,000 square feet dedicated to incubation and
related activities• Student, faculty, and alumni projects may apply to NYC Seed, NYU
Innovation Venture Fund, and other seed programs
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What’s success after 5 years?• Define and elaborate “Urban Science”• A vibrant world-class center pursuing such
– Nucleate an NYU/NYU-Poly community– Implement CUSP facilities
• Projects that impact the City and its Citizens– CUSP established as a trusted partner to NYC– Support public understanding and engagement
• Train several hundred people in this new field• Commercialization of CUSP technologies• Bring new tools to the social sciences• Begin to franchise the brand globally