Call for Papers
The abstract submission site is now closed. Please see the Home tab for registration information.
WORKSHOP ON BIG DATA AND URBAN INFORMATICS WITH SUPPORT FROM NATIONAL SCIENCE FOUNDATION
11-12 AUGUST 2014, CHICAGO, ILLINOIS, USA
CALL FOR PAPERS (Click here to download in PDF format)
Big Data has opened up several opportunities to obtain new insights on cities. We invite papers at the intersection of the urban social sciences and the data sciences to be presented in an NSF-sponsored workshop to be held on Aug 11-12, 2014, in the University of Illinois at Chicago, Chicago, Illinois. We hope that the workshop will generate discussions in this emerging area of research, with the goal of long-term community-building on the topic. Travel funds will be available for presenters. Workshop papers will be published in an online workshop proceeding. Selected papers will be published, after additional peer-review, in an edited book titled Seeing Cities Through Big Data – Research, Methods and Applications in Urban Informatics to be published with Springer. We welcome papers that discuss research results as well as idea pieces of work in progress which highlight research needs and data limitations.
|Thakuriah, Piyushimita (Vonu), Workshop Chair, Department of Urban Studies and School of Engineering, University of Glasgow, UK|
|Tilahun, Nebiyou, Co-Chair, Department of Urban Planning and Policy, University of Illinois at Chicago|
|Zellner, Moira, Co-Chair, Department of Urban Planning and Policy, University of Illinois at Chicago|
|Albrecht, Jochen, Hunter College||Levinson, David, University of Minnesota|
|Bhaduri, Budhudendra, Oak Ridge National Laboratory||Lin, Jane, University of Illinois at Chicago|
|Dieber, Max, University of Illinois at Chicago||Meen, Geoff, University of Reading, UK|
|Dirks, Lise, University of Illinois at Chicago||Miller, Harvey, Ohio State University|
|Fan, Yingling, University of Minnesota||Page, Scott, University of Michigan|
|Ferriera, Joseph, MIT||Poplin, Alenka, HefenCity Universitat Hamburg, Germany|
|Fingleton, Bernard, University of Cambridge, UK||Pryce, Gwilym, University of Glasgow, UK|
|French, Steven, Georgia Tech||Ramasubramanium, Laxmi, Hunter College, New York|
|Geers, Glenn, NICTA, Australia||Shekhar, Shashi, University of Minnesota|
|Grengs, Joe, University of Michigan||Waddell, Paul, University of California, Berkeley|
|Harris, Richard, University of Bristol, UK||Wang, Shaowen, University of Illinois Urbana-Champaign|
|Hudson-Smith, Andy, University College London||Wolfson, Ouri, University of Illinois at Chicago|
|Jiang, Bin, University of Gavle, Sweden||Wu, Jeremy, George Washington University|
|Johnson, Timothy, University of Illinois at Chicago||Zielinski, Sue, University of Michigan|
OBJECTIVE OF THE WORKSHOP
The objective of the workshop is to bring together researchers with an interest in the use of Big Data for urban analysis. The focus will be on understanding of urban systems, and related examples of urban applications, methods and tools. We are seeking papers that clearly create or use such novel sources of information for urban and regional analysis. Urban and regional analysis spans a broad range of areas. A far from complete list of areas include transportation, environment, public health, land-use, housing, economic development, labor markets, criminal justice, population demographics, urban ecology, energy, community development and public participation.
We invite original research papers including position papers on theoretical developments and applications demonstrating the use of urban Big Data, and the next-generation of Big Data services, tools and technologies for urban informatics. We are interested in papers that use Big Data in one or more of the following five themes:
1) Theoretical developments and knowledge discovery in urban systems;
2) Planning and operational uses of urban Big Data;
3) Urban Big Data measurement, analysis and methodological questions;
4) Information management for urban informatics;
5) Institutional issues, organizations, networks and infomediaries in urban Big Data.
Examples of specific topics of interest within these broad themes are:
Theoretical developments and knowledge discovery in urban systems: Results derived using Big Data on new insights, hypotheses and understanding of urban systems and their social, behavioral, political, mobility and economic aspects including models of transactions, incentives, collaboration, and cooperation and behavior or organizational change.
Planning and operational uses of urban Big Data: use of Big Data for improved planning, management and governance in the urban sectors (e.g., transportation, energy, smart cities, crime, housing, urban and regional economies, public health, public engagement, urban governance and political systems) including uses for decision-making, and development of indicators to monitor economic and social activity, and for urban sustainability, transparency, livability, social inclusion, place-making, accessibility and resilience.
Urban Big Data measurement, analysis and methodological questions: research relating to urban Big Data information extraction and analytics; statistical inference, data quality and related issues such as missing data, endogeniety and selection biases; assessment of the extent to which urban Big Data may be able to add to traditional survey-based urban social science research, as well as examples of Big Data linkage with census, survey and administrative data; evolving goodness of fit metrics for models and data, exploratory versus predictive analytics and visualization; methods to handle verification and validation, sensitivity analysis, and experimental design.
Information management for urban informatics: advancements in tool development for analytics, data mining, visualization, sensor fusion, information retrieval, and information extraction; links between urban Big Data, complex systems and agent-based models; urban sensing and computational approaches relating to information gathering, management and distribution of urban Big Data for knowledge discovery of cities.
Institutional issues, organizations, networks and infomediaries in urban Big Data: studies of locational privacy, trust management and information security relating to urban Big Data; analysis of social networks and sensing systems involved in urban data; studies of civic hacking networks and organizational assessments of open data portals and city dashboards.
WORKSHOP PROCEEDINGS AND BOOK
Interested authors should submit an extended abstract of 750-1000 words for review by April 1, 2014 for presentation in the workshop. Full workshop papers of selected abstracts will be due by July 15, 2014. All papers accepted for presentation in the workshop will be published in an online proceedings. In addition, select workshop presenters will be invited to submit a revised version of the conference paper for inclusion in an edited book titled Seeing Cities Through Big Data – Research, Methods and Applications in Urban Informatics to be published with Springer. Papers selected for inclusion in the book will undergo a second peer-review.
Because the use of Big Data for urban analysis is fairly recent, we also welcome “idea” or “work in progress” pieces that do not as yet have definite results. We will devote a working session for discussion on how such ideas may evolve and the research needs and data limitations experienced by the researchers. A special section of the online conference proceedings will be devoted to such papers.
While there are many definitions of “Big Data”, it is the term being applied to very large volumes of data which are difficult to handle using traditional data management and analysis methods, and which can be differentiated from other data in terms of “volume, velocity and variety”, and in some cases, its real-time nature. Examples of Big Data include highly unstructured text, video, still pictures or web-based data, in addition to very large structured datasets which can help discern urban patterns, dynamics and growth, primarily arising from business transactions (for example, real estate transactions data, data on household energy consumption and expenditures), urban management and monitoring processes in a wide variety of urban sectors, government administrative sources, longitudinal outputs from regional planning models, or longitudinal and linked social science surveys.
Big Data for quantitative urban social science research may be generated from several sources. One source is infrastructure-based sensors used for operations and management in urban sectors such as transportation, energy, water, environmental, crime and homeland security management, weather and other sectors. Static and mobile sensors have led to significant advances in urban Big Data and while infrastructure-based sensors have been around in several sectors for decades (for example, Intelligent Transportation Systems; smart water, energy and utility management; smart city and future city demonstrator projects; and other urban technology projects), recent developments in Machine-to-Machine communications and the Internet of Things have led to increasing connectivity amongst such data streams and to their availability for end use by urban social science researchers.
Another source is User-Generated Content arising from social media, web submissions, and volunteered geographic information. Citizen science projects, and participatory or opportunistic sensing systems are making such data available for urban informatics. While analytics of such data may provide interesting insights into urban dynamics, the power of such data for urban social science research may be further increased if linked to other data sources, for example, administrative or transactions data. For example, analytics of location-based social networks or language detection of geo-tagged tweets may allow early insights into changes in neighborhood demographics or economic composition, but when linked with transport, economic or housing data, may be able to pinpoint time-varying demand for urban spaces and the need for new public models of dynamic resource management.
A third source of urban Big Data is Open Government initiatives which are leading to large and longitudinal or repeated cross-sections of open data on crime, transport, property values, educational performance, public engagement processes, and many other factors that explain urban behaviors and dynamics. These data sources may be linked together, and with census or survey data, to create rich and contextualized urban Big Data.
Urban Big Data has the potential to stimulate new insights and perspectives by means of data-intensive research on urban dynamics, human behavior, resource use, and spatial disparities. New perspectives on urban analysis are being stimulated by: (A) techno-managerial considerations (eg, more effective management and planning in urban areas through Big Data generated by intersectoral connectivity and dynamic resource management); (B) scientific considerations and quantified urbanism (eg, deeper, more fine-grained understanding and knowledge discovery of urban processes and dynamics, with the goal of developing theories or hypothesis to stimulate future empirical research); (C) urban engagement (eg, collaborative strategies for increased engagement and exploration of communities, and civic participation and citizen involvement); (D) methods development (eg, novel new ways of data-driven modeling, complex systems analysis of urban processes and urban computation); and (E) Big Data quality considerations (eg, research into major data quality issues, frameworks, metrics and methods to be used for data quality assessment, extent to which emerging urban Big Data can augment knowledge gleaned from survey research and fundamental limitations in Big Data-based urban social science research)
The objective of the workshop is to bring together researchers with an interest in the use of Big Data for urban analysis. The focus will be on understanding of urban systems, and related examples of urban applications, methods and tools. We are seeking papers that clearly create or use such novel sources of information for urban and regional analysis. Urban and regional analysis spans a broad range of areas. A far from complete list of areas include transportation, environment, public health, land-use, housing, economy, labor markets, criminal justice, population demographics, urban ecology, energy, community development and public participation. Many specialized modeling and simulation approaches have been developed in the urban sector for the discovery of behavioral, social and economic dynamics, and for the identification of novel patterns for improved planning, operations and management, and policy evaluation. We welcome papers that add to this existing body of knowledge and which clearly create or use such emerging data sources in any of the aforementioned urban sectors.
The abstract submission page is now closed.
April 1, 2014: Extended Abstract (750-1000 words) submission to conference website.
May 1, 2014: Communication of workshop presentation decision to authors.
July 15, 2014: Full papers due for inclusion in online conference proceedings.
Aug 11 and 12, 2014: Workshop in Chicago.
September 1, 2014: Selected conference papers invited for submission for review for publication in edited volume.
December 15, 2014: Submission of selected conference papers for review for publication in edited volume.
Travel funds up to $700 will be available for a single presenter per paper, on a reimbursement basis. Student presenters will be able to compete for an additional limited pool of funds, for upto an additional $250 per student presenter. At least one author per paper must commit to attending and presenting in the workshop, before final selection of the paper. All travel arrangements, including visa and other requirements, will be the responsibility of the presenter. We will have further information at the appropriate time regarding hotel and other local information.