Big Data Archives - NYU Center for Urban Science and Progress
Julia Lane joins NYU as Full-time Faculty Member
In May 2015, Julia Lane joined NYU as a Professor at CUSP. She also serves as a Professor of Public Service at NYU’s Wagner Graduate School of Public Service and Provostial Fellow for Innovation Analytics.
Dr. Lane has had leadership roles in a number of policy and data science initiatives at her previous appointments, which include Senior Managing Economist at the American Institutes for Research; Program Director of the Science of Science & Innovation Policy program at the National Science Foundation; Senior Vice President and Director, Economics Department at NORC (National Opinion Research Center) at the University of Chicago; Director of the Employment Dynamics Program at the Urban Institute; Senior Research Fellow at the U.S. Census Bureau; and Assistant, Associate and Full Professor at American University. Please click here for additional information on her professional achievements.
As part of the CUSP team, Dr. Lane will bring significant experience and expertise in building the CUSP Data User Facility, and in cultivating the social science community to strengthen our engagement with new researchers. Dr. Lane is stepping down from her role on CUSP’s External Advisory Board (EAB) where she provided valuable insight and expertise.
Privacy, Big Data, and the Public Good reviewed in Science
Earlier this year, CUSP, along with the American Statistical Association and its Privacy and Confidentiality subcommittee and the Research Data Centre of the German Federal Employment Agency, sponsored a book about the rise of big data and the privacy issues that brings up. The book, Privacy, Big Data, and the Public Good: Frameworks for Engagement, published by Cambridge University Press and launched on July 16 at the New York Academy of Sciences, is an accessible summary of the important legal, economic, and statistical thinking that frames the many privacy issues associated with the use of big data – along with practical suggestions for protecting privacy and confidentiality that can help to guide practitioners.
On November 25, Privacy, Big Data, and the Public Good: Frameworks for Engagement was reviewed by Science Magazine, which said the book “presents a collection of essays from a variety of perspectives, in chapters by some of the heavy hitters in the privacy debate, who make a convincing case that the current framework for dealing with consumer privacy does not adequately address issues posed by big data.”
The full review is available on Science Magazine’s website.
2014 AT&T Transit Tech Developer Day at CUSP
November 22, 2014 – November 22, 2014
2 MetroTech Center
The 2014 AT&T Transit Tech Developer Day App is an opportunity to launch the development of your 2014 MTA App Quest entry. This day will allow you to:
- Hear from MTA experts about this year’s App Quest and the new datasets and API released for 2014.
- Work on the early stage of your concept with access to industry and data experts.
- Sign up for in-person or virtual mentoring sessions with experts from the MTA and its partners, including AT&T and New York University’s Center for Urban Science and Progress (CUSP).
- Build your team or join a team through a Teammate Match session.
|8:30 AM||Doors Open for Check-In/Registration|
|9:00 AM||Announcements||Lecture Hall|
|9:05 AM||Event Kickoff and Welcome||Lecture Hall|
|9:12 AM||About 2014 MTA AT&T App Quest||Lecture Hall|
|9:30 AM||Highlight: New Datasets and GTFS||Lecture Hall|
|9:50 AM||Highlight: Accessibility Track||Lecture Hall|
|10:10 AM||Highlight: Beacon Q&A||Lecture Hall|
|10:20 AM||Overview: Prizes||Lecture Hall|
|10:25 AM||Teammate Match (note: teams may also start work)||Lecture Hall|
|11:00 AM||All teams at work||Town Hall East
|12:00 PM||LUNCH & Presentation Schedule Signups||Pantry|
|1:00 PM||Office Hours Open
||Rooms 810, 818, 820, 827|
|TBA||CONCEPT PITCHES||Lecture Hall|
|5:15 PM||Winners Announced||Lecture Hall|
NYU CUSP Unveils First-of-its-Kind ‘Urban Observatory’ in Downtown Brooklyn
New York University’s Center for Urban Science & Progress (CUSP) today unveiled its Urban Observatory, a project that will persistently observe and analyze New York City in an effort to better understand the “pulse of the city” in various states, such as mobility, energy use, communications and economics. The data gathered from the Urban Observatory will ultimately be used to improve various aspects of urban life, including energy efficiency, detecting releases of hazardous material, tracking pollution plumes, aiding in post-blackout restoration of electrical power, and more.
“This technology comes at an opportune time when about 80% of the U.S. population and 50% of the global population live in cities, said Dr. Steven Koonin, NYU CUSP’s founding director. “We’ll take these large data sets and turn them into solutions for city-wide problems, helping us to better understand our urban environment and improve the quality of life for citizens around the world.”
The CUSP Urban Observatory, which is still in its demonstration phase, uses an 8 megapixel camera situated atop a building in Downtown Brooklyn to quantify the dynamics of New York City by capturing one panoramic, long-distance image of Lower and Midtown Manhattan every 10 seconds. These observations differ from those of a satellite due to the fixed urban vantage point, which offer an unchanging perspective, with easy and low cost operations. Techniques adapted from astronomy are used to analyze the images.
Strict protocols have been observed to protect the privacy of those individuals in the field of view – no more than a few pixels cover the closest sources in the scene and images are significantly blurred to ensure that no personal detail is ever captured. Additionally, all analyses have been performed at the aggregate level and any human inspection has been done without the knowledge of the precise location of the source.
CUSP’s Urban Observatory seeks high impact science and applications to enhance public well-being, city operations, and future urban design and combines correlative data including administrative records, original measurements, and current topography. Although the technology is currently being used to solely observe New York City, CUSP hopes to share this with other major cities, such as London, Chicago, and Hong Kong, for similar use and application.
A team of CUSP scientists have been working on this technology for almost two years. Data will be made available for analysis by CUSP personnel and others by proposal.
About New York University’s Center for Urban Science & Progress
CUSP is an applied science research institute created by New York University with a consortium of world-class universities and the foremost international technology companies to address the needs of cities. At the heart of its academic program, CUSP will investigate and develop solutions to the challenges that face cities around the world. This research will make CUSP the world’s leading authority in the emerging field of “urban informatics”. For more news and information on CUSP, please visit http://cusp.nyu.edu/.
Kim Alfred, CUSP
Megan Romano, The Marino Organization
CUSP Research Seminar Series: Dr. Aaditya Rangan
October 29, 2014 – October 29, 2014
1 MetroTech Center
A common problem in data analysis – including machine learning and genomics – is to detect, within a large array, small submatrices which are ‘structured’ in some way.Such submatrices, called ‘biclusters’ can represent a subset of features shared across a subset of images, or a subsets of genes that are coexpressed across a subset of the patient population. In this talk I will discuss some of the challenges associated with biclustering, and provide an algorithm that overcomes most of these challenges.
Dr. Aaditya V Rangan is an Assistant Professor at the Courant Institute of Mathematical Sciences, NYU. He received his PhD in Mathematics from the University of California, Berkeley. His research interests lie in large – scale scientific modeling of physical, biological and neurobiological phenomena and the development of efficient numerical methods and related analysis.
AAAI 2015 Workshop on AI for Cities
Almost half of humanity today lives in urban environments and that number will grow to 80% or more by the middle of this century in different parts of the world. Cities are thus the loci of resource consumption, economic activity, social interactions, and education and innovation; they are the cause of our looming sustainability problems but also where those problems must be solved. Cities are also an enormous forum for policy making, as well as an apparently unbounded source of digital data of a wide nature. Artificial Intelligence has the potential to play a central role in tackling the underlying hard computational, decision making, and statistical problems of cities.
With this in mind, CUSP has proposed a worskshop to bring together AI researchers who work on urban informatics and domain experts from city agencies in order to: i) identify and characterize the prototypical AI problems that cities face, ii) discuss data access, open platforms, and dissemination of information, iii) present recent research in this nascent subfield, and iv) strengthen the path from research to decision and policy making. The workshop will be held on January 25-26, 2015, in Austin, Texas.
- Spatiotemporal inference of urban processes (social or natural)
- Energy consumption/disaggregation models of large urban areas
- Planning/Scheduling for city operations
- Decision making for urban science and for city policy
- AI models of transportation and utilities networks
- Resource allocation in urban systems
- Event detection of urban activity and processes
- Active learning, sampling biases and dataset shift in city data
- Multi-agent simulations of urban processes
- Visualization and city operational systems
- Cross-city comparative analysis
- Improving public health systems in cities
- Crowdsourcing for urban science and decision making
- Open data platforms and data access tools for data science
|09:00 – 09:10||-||Introduction and opening remarks|
|09:10 – 09:40||-||Invited talk – Juliana Freire, NYU Polytechnic School of Engineering|
|09:40 – 10:10||-||Invited talk – Autonomous Machines and Robots in Cities – Manuela Veloso, CMU|
|10:10 – 10:30||-||Coffee Break|
|10:30 – 11:00||-||Invited talk – Adi Botea, IBM|
|11:00 – 11:30||-||Invited talk – Craig Knoblock, USC|
|11:30 – 12:30||-||Lunch Break|
|12:30 – 01:00||-||Invited Talk – Mike Flowers, NYU CUSP|
|01:00 – 03:00||-||Paper Presentations|
|03:00 – 03:30||-||Data access – city data portals, initiatives, and restrictions|
|03:30 – 04:00||-||Coffee Break|
|04:00 – 04:30||-||Data access – city data portals, initiatives, and restrictions|
|04:30 – 05:00||-||Open discussion and concluding remarks|
|05:00 – 06:00||-||Social event|
Papers must be formatted in AAAI two-column, camera-ready style. Regular research papers (submitted and final), presenting a significant contribution, may be no longer than 7 pages, with page 7 including only references. Short papers (submitted and final), describing a position on the topic of the workshop or a demonstration/tool, may be no longer than 4 pages, including references.
CUSP is offering two awards of up to $1,000 each in travel reimbursements for students who are lead authors on papers contributed to the workshop.
Submissions are to be made online at https://easychair.org/conferences/?conf=ai4cities. We request that interested authors log in and submit abstracts as an expression of interest before the final deadline.
|11/09/2014||-||Paper Submission deadline|
|11/14/2014||-||Notification of decisions|
Theo Damoulas - firstname.lastname@example.org
Research Assistant Professor, New York University, Center for Urban Science and Progress (CUSP)
Biplav Srivastava - email@example.com
Senior Researcher, IBM Master Inventor, IBM Research
New Delhi, India
Sheila McIraith - firstname.lastname@example.org
Professor of Computer Science, Department of Computer Science, University of Toronto
Freddy Lecue - email@example.com
Research Scientist, IBM Research, Smarter Cities Technology Center
Sarah Bird (Microsoft Research, USA)
Alex Chohlas-Wood (NYPD, USA)
Philippe Cudre-Mauroux (University of Fribourg, CH)
Mathieu d’Aquin (Open University, UK)
Bistra Dilkina (Georgia Tech, USA)
Greg Dobler (NYU CUSP, USA)
Harish Doraiswamy (NYU, USA)
Stefano Ermon (Stanford University, USA)
Maurizio Filippone (University of Glasgow, UK)
Rebecca Hutchinson (Oregon State University, USA)
Rishee Jain (Stanford, USA)
Nikos Karampatziakis (Microsoft, USA)
Liakata Maria (University of Warwick, UK)
Charlie Mydlarz (NYU CUSP, USA)
Temitope O Omitola (University of Southampton, UK)
Jeff Pan (Univ. of Aberdeen, UK)
Kostas Pelechrinis (University of Pittsburgh, USA)
Alessandro Perina (Italian Institute of Technology, ITA)
Justin Salamon (NYU CUSP, USA)
Daniel Sheldon (UMass Amherst, USA))
Vasilis Syrgkanis (Microsoft Research, USA)
Ravi Shroff (NYU CUSP, USA)
Vasileios Stathopoulos (UCL, UK)
Huy T. Vo (NYU CUSP, USA)
Yuxiang Wang (Carnegie Mellon University, USA)
Hong Yang (NYU CUSP, USA)
Arkaitz Zubiaga (University of Warwick, UK)
Workshop on Semantics for Smarter Cities
In conjunction with 13th International Semantic Web Conference (ISWC 2014)
Payam Barnaghi, Jan Holler, Biplav Srivastava, John Davies, John Breslin, and Tope Omitola
Riva del Garda, Italy – 20 October, 2014
Workshop on Semantic Cities
In conjunction with Association for the Advancement of Artificial Intelligence conference (AAAI-14)
Mark Fox, Freddy Lecue, Sheila McIlraith, Biplav Srivastava and Rosario Usceda-Sosa
Québec City, Québec, Canada – July 27-31, 2014
Workshop on Inclusive Web Programming – Programming on the Web with Open Data for Societal Applications
In conjunction with 36th International Conference on Software Engineering
Biplav Srivastava and Neeta Verma
Hyderabad, India – May 31-June 4, 2014
Workshop on Semantic Cities
In conjunction with International Joint Conference on Artificial Intelligence (IJCAI-13)
Freddy Lecue Biplav Srivastava, and Ziaqing Nie
Beijing, China – Aug 3-5, 2013
The Semantic Smart City Workshop (SemCity-13)
In conjunction with International Conference on Web Intelligence, Mining and Semantics (WIMS-13)
Tope Omitola, John Breslin, Biplav Srivastava, and John Davies
Madrid, Spain – June 12-14, 2013
Workshop on Semantic Cities
In conjunction with 26th Conference of Association for Advancement of Artificial Intelligence (AAAI-12)
Biplav Srivastava, Freddy Lecue, and Anupam Joshi
Toronto, Canada – July 22-26, 2012
AI for an Intelligent Planet
In conjunction with 22nd International Joint Conference on Artificial Intelligence (IJCAI-11)
Biplav Srivastava, Carla Gomes, and Anand Ranganathan
Barcelona, Spain – July 16-22, 2011
Privacy, Big Data, and the Public Good
Massive amounts of new data about people, their movements, and activities can now be accessed and analyzed as never before. Numerous privacy concerns have been raised by use – or misuse – of such data in commercial and national security arenas. Yet we are motivated by the potential for “big data” to be harnessed to serve the public good: scientists can use new forms of data to do research that improves people’s live; federal, state and local governments can use data to improve the delivery of services to citizens; and non-profit organizations can use the information to advance the public good.
Access to big data raises many unanswered questions related to privacy and confidentiality: What are the ethical and legal requirements for scientists and government officials seeking to serve the public good without harming individual citizens? What are the rules of engagement? What are the best ways to provide access while protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss?
CUSP, along with the American Statistical Association and its Privacy and Confidentiality subcommittee and the Research Data Centre of the German Federal Employment Agency, sponsored a book on this very issue, Privacy, Big Data, and the Public Good: Frameworks for Engagement. Published by Cambridge University Press, this book is an accessible summary of the important legal, economic, and statistical thinking that frames the many privacy issues associated with the use of big data – along with practical suggestions for protecting privacy and confidentiality that can help to guide practitioners.
The book launch, held at the New York Academy of Sciences on July 16th, included talks and panels by the book’s editors and a number of the authors. You can watch these talks and panels below.
Moderator: Michael Holland
Panelists: Julia Lane, Victoria Stodden, Stefan Bender, Helen Nissenbaum
The editors discuss the motivation for the book and how it contributes to the broader conversation on privacy concerns about big data. They also briefly highlight the contribution of authors who were unable to participate in the event.
Panel 1: Law, Ethics, and Economics of Big Data
Moderator: Jake Bournazian
Panel: Helen Nissenbaum, Kathy Strandburg, Victoria Stodden
Authors discuss the fact that “big data” is more than a straightforward change in technology. It poses deep challenges to our traditions of notice and consent as tools for managing privacy. Because our new tools of data science can make it all but impossible to guarantee anonymity in the future, is it possible to truly give informed consent, when we cannot, by definition, know what the risks are from revealing personal data either for individuals or for society as a whole?
Panel 2: Practical Concerns of Working with Big Data
Moderator: Julia Lane
Panelists: Bob Goerge, Daniel “Dazza” Greenwood, Carl Landwehr
Based on their experience building large data collections, authors discuss some of the best practical ways to provide access while protecting confidentiality. What have we learned about effective engineered controls? About effective access policies? About designing data systems that reinforce – rather than counter – access policies? They also explore the business, legal, and technical standards necessary for a new deal on data.
Panel 3: Statistical Framework: Issues & Practical Responses
Moderator: Stefan Bender
Panelists: Frauke Kreuter, Jerry Reiter, Peter Elias
Since the data generating process or the data collection process is not necessarily well understood for big data streams, authors discuss what statistics can tell us about how to make greatest scientific use of this data. They also explore the shortcomings of current disclosure limitation approaches and whether we can quantify the extent of privacy loss.
Capstone Speaker: Theresa Pardo
Our capstone speaker is the Director of the Center for Technology in Government at the University at Albany, the Open NY Policy Advisor for Open.NY.Gov, and the President of the Digital Government Society. She shows us how “big data” can be harnessed to serve the public good by presenting a guide for making information in the public sector more available and more usable.
Beyond The Quantified Self: The World’s Largest Quantified Community
So-called “smart” cities and communities are sprouting around the world, from the urban laboratory that is the Spanish port city of Santander to a huge residential energy research project that has been running for years in Austin, Texas.
Now a new “quantified community” built from scratch is about to take shape, and it’s on the biggest stage yet: The Hudson Yards, the largest private real estate project ever in the United States, which is slated for construction on Manhattan’s underdeveloped West Side beginning this year.