The Analysis of Big Data on Cites and Regions - Some Computational and Statistical Challenges

Schintler, Laurie A. and Fischer, Manfred M. ORCID: (2018) The Analysis of Big Data on Cites and Regions - Some Computational and Statistical Challenges. Working Papers in Regional Science, 2018/08. WU Vienna University of Economics and Business, Vienna.


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Big Data on cities and regions bring new opportunities and challenges to data analysts and city planners. On the one side, they hold great promise to combine increasingly detailed data for each citizen with critical infrastructures to plan, govern and manage cities and regions, improve their sustainability, optimize processes and maximize the provision of public and private services. On the other side, the massive sample size and high-dimensionality of Big Data and their geo-temporal character introduce unique computational and statistical challenges. This chapter provides overviews on the salient characteristics of Big Data and how these features impact on paradigm change of data management and analysis, and also on the computing environment.

Item Type: Paper
Keywords: massive sample size, high-dimensional data, heterogeneity and incompleteness, data storage, scalability, parallel data processing, visualization, statistical methods
Classification Codes: JEL C10, C55, C80
Divisions: Departments > Sozioökonomie
Depositing User: Gertraud Novotny
Date Deposited: 12 Nov 2018 10:52
Last Modified: 29 Aug 2020 06:53


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