TY - JOUR
T1 - Urban Informatics in the Science and Practice of Planning
AU - Kontokosta, Constantine E.
N1 - Funding Information:
This work represents lessons learned as the inaugural Deputy Director of the NYU Center for Urban Science and Progress (CUSP), during which time I led the design, implementation, and oversight of one of the first graduate programs in Urban Informatics. I would like to thank the faculty and staff that helped launch and manage the graduate programs at CUSP, particularly the insight and expertise of Steven Koonin, Michael Holland, Claudio Silva, Ingrid Gould Ellen, Kaan Ozbay, Gregory Dobler, Michael Flowers, Geoffrey West, Michael Batty, Luis Bettencourt, Logan Werschky, and Neil Klieman, among many others. I would also like to thank all of the CUSP Master of Science in Applied Urban Science and Informatics graduates, who are now using the skills described here to help makes cities better places to live. A preliminary version of this paper was presented at the SCOPE 2017 International Workshop. The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been funded, in part, by a grant by the MacArthur Foundation. This material is based on work supported, in part, by the National Science Foundation under Grant No. 1653772.
Publisher Copyright:
© The Author(s) 2018.
PY - 2021/12
Y1 - 2021/12
N2 - The vast amount of data being generated in and about cities creates both an opportunity and a dilemma for urban policymakers and planners. This paper articulates the theoretical, practical, and pedagogical foundations for the fields of urban informatics and civic analytics and outlines the challenges to effectively applying big data and computational methods to urban management, policy, and planning. It describes the state of the field, defines the range of applications in the urban context, and presents key considerations in training scientists that both acknowledge and capitalize on shifting modes of learning, working, and decision making. Situated within the ethical and moral landscape of data analytics, it articulates the knowledge and skills needed by future urban science practitioners and concludes with a discussion of data-driven problem solving in the urban context.
AB - The vast amount of data being generated in and about cities creates both an opportunity and a dilemma for urban policymakers and planners. This paper articulates the theoretical, practical, and pedagogical foundations for the fields of urban informatics and civic analytics and outlines the challenges to effectively applying big data and computational methods to urban management, policy, and planning. It describes the state of the field, defines the range of applications in the urban context, and presents key considerations in training scientists that both acknowledge and capitalize on shifting modes of learning, working, and decision making. Situated within the ethical and moral landscape of data analytics, it articulates the knowledge and skills needed by future urban science practitioners and concludes with a discussion of data-driven problem solving in the urban context.
KW - big data
KW - civic analytics
KW - urban data science
KW - urban informatics
KW - urban science
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U2 - 10.1177/0739456X18793716
DO - 10.1177/0739456X18793716
M3 - Article
AN - SCOPUS:85053319779
SN - 0739-456X
VL - 41
SP - 382
EP - 395
JO - Journal of Planning Education and Research
JF - Journal of Planning Education and Research
IS - 4
ER -