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Integrating Urban Data Science into Economic Development Research and Curriculum

Bibliographic Data

ID12078166
AuthorsLi Fang (0000-0003-1462-6357, Florida State University, Tallahassee, FL, USA, corresponding author), Jamaal Green (0000-0002-8322-8654, University of Pennsylvania, Philadelphia, PA, USA), Xinyue Ye (0000-0001-8838-9476, Texas A&M University, College Station, TX, USA), Wei Shi (0000-0002-3031-732X, Hartford Financial Services (United States))
Year2022
Volume44
Issue3
Pages1001-1009
Publication date2022-10-27
Open AccessYes
TypeARTICLE
VenueJournal of Planning Education and Research (JOURNAL)
Journal identifiersISSN: 0739-456X • E-ISSN: 1552-6577
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/0739456x221128501
OpenAlexW4307711735
LanguageEN
References cited26

Urban data science (UDS) is developing rapidly and starting to be widely adopted in urban planning research and curricula. However, economic development planners have been relatively slow in introducing UDS into their toolkits. This reality is a disservice to the subfield and students. This article discusses the motivation and current practices of UDS in economic development, identifies successes and challenges, and suggests actions moving forward. Professional training, curriculum innovation, and support from departments, institutions, and the broader academic and professional communities are called for

Curriculum · Curriculum development · Engineering ethics · Pedagogy · Political science · Professional development · Public relations · Sociology · Upgrade · Urban planning · Computer Science · Engineering · Housing Market and Economics · Human Mobility and Location-Based Analysis · Spatial and Panel Data Analysis

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