Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery
UBDC Director, Prof Piyushimita (Vonu) Thakuriah and Co-Investigators Nebiyou Tilahun and Moira Zellner from the University of Illinois at Chicago, will soon publish conference proceedings from the NSF Workshop on Big Data and Urban Informatics. Below is an excerpt from these proceedings, specifically on "Innovations and Challenges to Urban Planning and Knowledge Discovery." The abstract and full text are available below.
Big Data is the term being used to describe a wide spectrum of observational or “naturally-occurring” data generated through transactional, operational, planning and social activities that are not specifically designed for research. Due to the structure and access conditions associated with such data, research and analysis using such data becomes significantly complicated. New sources of Big Data are rapidly emerging as a result of technological, institutional, social, and business innovations. The objective of this background paper is to describe emerging sources of Big Data, their use in urban research, and the challenges that arise with their use. To a certain extent, Big Data in the urban context has become narrowly associated with sensor (e.g., Internet of Things) or socially generated (e.g., social media or citizen science) data. However, there are many other sources of observational data that are meaningful to different groups of urban researchers and user communities. Examples include privately held transactions data, confidential administrative micro-data, data from arts and humanities collections, and hybrid data consisting of synthetic or linked data.
The emerging area of Urban Informatics focuses on the exploration and understanding of urban systems by leveraging novel sources of data. The major potential of Urban Informatics research and applications is in four areas: (1) improved strategies for dynamic urban resource management, (2) theoretical insights and knowledge discovery of urban patterns and processes, (3) strategies for urban engagement and civic participation, and (4) innovations in urban management, and planning and policy analysis. Urban Informatics utilizes urban Big Data in innovative ways by retrofitting or repurposing existing urban models and simulations that are underpinned by a wide range of theoretical traditions, as well as through data-driven modeling approaches that are largely theory agnostic, although these divergent research approaches are starting to converge in some ways. The paper surveys the kinds of urban problems being considered by going from a data-poor environment to a data-rich world and ways in which such enquiry have the potential to enhance our understanding, not only of urban systems and processes overall, but also contextual peculiarities and local experiences. The paper concludes by commenting on challenges that are likely to arise in varying degrees when using Big Data for Urban Informatics: technological, methodological, theoretical/epistemological, and the emerging political economy of Big Data.
To read the full paper, download here (PDF 519 KB).
Please cite as:
Thakuriah, P., N. Tilahun and M. Zellner (2015). Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery. In Proc. Of NSF Workshop on Big Data and Urban Informatics, pp. 4-32.
Thakuriah, P., N. Tilahun and M. Zellner (estimated Feb 2016). Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery. In Seeing Cities through Big Data: Research Methods and Applications in Urban Informatics, to be published by Springer, Consisting of papers presented in an NSF-funded Workshop on Big Data and Urban Informatics.