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  5. Urban Consumption Patterns: OpenStreetMap Quality for Social Science Research
 
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Urban Consumption Patterns: OpenStreetMap Quality for Social Science Research

Author(s)
Rabiei-Dastjerdi, Hamidreza  
McArdle, Gavin  
Ballatore, Andrea  
Uri
http://hdl.handle.net/10197/12632
Date Issued
2020-05-09
Date Available
2021-11-11T14:37:18Z
Abstract
Citizen consumption refers to the goods and services which citizens utilise. This includes time spent on leisure and cultural activities as well as the consumption of necessary and luxury goods and services. The spatial dimension of consumption inequality can show the underlying urban spatial structure and processes of a city. Usually, the main barrier to effectively measuring consumption is the availability and accessibility of spatial data. While the main body of the literature utilises official, government data, such data is not always available, up-to-date or can be costly to acquire. In this paper, we discuss the potential of Volunteered Geographic Information (VGI) as a source of spatial data for determining consumption inequality. To this end, we compared OpenStreetMap (OSM) data, that can be used as proxies for consumption inequality, with official data in the area of Greater London. The results show that OSM is currently inadequate for studying the spatial dimension of consumption. It is our view that while VGI is appropriate for tasks such as routing and navigation, it also has the potential to add value to social science studies in the future.
Sponsorship
European Commission Horizon 2020
Type of Material
Conference Publication
Publisher
SciTePress
Subjects

Consumption inequalit...

OpenStreetMap (OSM)

Data quality

London

DOI
10.5220/0009576302780285
Web versions
http://www.gistam.org/?y=2020
Language
English
Status of Item
Peer reviewed
Journal
Grueau, C., Laurini, R., and Ragia, L. (eds.). Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management
Conference Details
The 6th International Conference on Geographical Information Systems Theory, Applications and Management, Online Event, 7-9 May 2020
ISBN
9789897584251
ISSN
2184-500X
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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GISTAM_2020_62_CR.pdf

Size

1010.96 KB

Format

Adobe PDF

Checksum (MD5)

992a8a35fb6135abb6ed2c9de8ecbc1d

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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