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Work Always in Progress: Analysing Maintenance Practices in Spatial Crowd-sourced Datasets

Quattrone, G; Dittus, M; Capra, L; (2017) Work Always in Progress: Analysing Maintenance Practices in Spatial Crowd-sourced Datasets. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. (pp. pp. 1876-1889). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

Crowd-mapping is a form of collaborative work that empowers users to share geographic knowledge. Despite geographic information being intrinsically evolving, little research has so far gone into analysing maintenance practices in these domains. In this paper, we quantitatively capture maintenance dynamics in geographic crowd-sourced datasets, in terms of: the extent to which different maintenance actions are taking place, the type of spatial information that is being maintained, who engages in these practices and where. We apply this method to 117 countries in OpenStreetMap, one of the most successful examples of geographic crowd-sourced datasets. Furthermore, we explore what triggers maintenance, by means of an online survey to which 96 OpenStreetMap contributors took part. Our findings reveal that, although maintenance practices vary substantially from country to country in terms of how widespread they are, strong commonalities exist in terms of what metadata is being maintained, by whom, and what triggers them.

Type: Proceedings paper
Title: Work Always in Progress: Analysing Maintenance Practices in Spatial Crowd-sourced Datasets
Event: 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2017)
Location: Portland, United States
Dates: 25 February – 1 March 2017
ISBN-13: 978-1-4503-4335-0
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2998181.2998267
Publisher version: http://dx.doi.org/10.1145/2998181.2998267
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1515025
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