Urban Data Science
Title
Urban Data Science
Author
Law, Tina
Legewie, Joscha
Research Area
Social Processes
Topic
Urbanization
Abstract
Data on urban life are more accessible today than ever before. New sources of “big data” such as 311 requests, recorded police activity, digitized student records, and social media capture urban life on an unprecedented temporal and geographical scale. Combined with new and improved computational social science methods for harnessing data, they promise to change urban research in important ways. In this essay, we outline urban data science—an emerging, interdisciplinary approach to studying urban life using big data and computational social science methods. We discuss three key innovations that this approach offers for urban research: (i) a broader and more multifaceted definition of neighborhood activity, (ii) greater knowledge on the role of socio‐spatial interdependencies in urban life, and (iii) more dynamic understandings of urban issues and policies. We conclude by highlighting some challenges that urban scholars must collaboratively address as they engage in this new urban data science.