Quality assessment of OpenStreetMap data using trajectory mining

Basiri, Anahid, Jackson, Mike, Amirian, Pouria, Pourabdollah, Amir, Sester, Monika, Winstanley, Adam, Moore, Terry and Zhang, Lijuan (2016) Quality assessment of OpenStreetMap data using trajectory mining. Geo-spatial Information Science, 19 (1). pp. 56-68. ISSN 1009-5020

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OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions, and updates, can be inaccurate, incomplete, inconsistent, or vague. There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data. Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs. This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users. The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature. Using such rules, some sets of potential bugs and errors can be identified and stored for further investigations

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/979742
Keywords: Spatial data quality; OpenStreetMap (OSM); trajectory data mining
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1080/10095020.2016.1151213
Depositing User: Eprints, Support
Date Deposited: 05 May 2016 16:18
Last Modified: 04 May 2020 20:04
URI: https://eprints.nottingham.ac.uk/id/eprint/33132

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