Anahid Basiri
Quality assessment of OpenStreetMap data using trajectory mining
Basiri, Anahid; Jackson, Mike; Amirian, Pouria; Pourabdollah, Amir; Sester, Monika; Winstanley, Adam; Moore, Terry; Zhang, Lijuan
Authors
Mike Jackson
Pouria Amirian
Amir Pourabdollah
Monika Sester
Adam Winstanley
Terry Moore
Lijuan Zhang
Abstract
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
Citation
Basiri, A., Jackson, M., Amirian, P., Pourabdollah, A., Sester, M., Winstanley, A., Moore, T., & Zhang, L. (2016). Quality assessment of OpenStreetMap data using trajectory mining. Geo-Spatial Information Science, 19(1), https://doi.org/10.1080/10095020.2016.1151213
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 19, 2015 |
Online Publication Date | Mar 25, 2016 |
Publication Date | Jan 1, 2016 |
Deposit Date | May 5, 2016 |
Publicly Available Date | May 5, 2016 |
Journal | Geo-spatial Information Science |
Electronic ISSN | 1009-5020 |
Publisher | Taylor and Francis |
Peer Reviewed | Peer Reviewed |
Volume | 19 |
Issue | 1 |
DOI | https://doi.org/10.1080/10095020.2016.1151213 |
Keywords | Spatial data quality; OpenStreetMap (OSM); trajectory data mining |
Public URL | https://nottingham-repository.worktribe.com/output/979742 |
Publisher URL | http://dx.doi.org/10.1080/10095020.2016.1151213 |
Files
Quality assessment of OpenStreetMap data using trajectory mining.pdf
(1.7 Mb)
PDF
Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search