Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns. Issue 7 (3rd July 2019)
- Record Type:
- Journal Article
- Title:
- Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns. Issue 7 (3rd July 2019)
- Main Title:
- Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns
- Authors:
- Kashian, Alireza
Rajabifard, Abbas
Richter, Kai-Florian
Chen, Yiqun - Abstract:
- ABSTRACT: In the past decade, Volunteered Geographic Information (VGI) has emerged as a new source of geographic information, making it a cheap and universal competitor to existing authoritative data sources. The growing popularity of VGI platforms, such as OpenStreetMap (OSM), would trigger malicious activities such as vandalism or spam. Similarly, wrong entries by unexperienced contributors adds to the complexities and directly impact the reliability of such databases. While there are some existing methods and tools for monitoring OSM data quality, there is still a lack of advanced mechanisms for automatic validation. This paper presents a new recommender tool which evaluates the positional plausibility of incoming POI registrations in OSM by generating near real-time validation scores. Similar to machine learning techniques, the tool discovers, stores and reapplies binary distance-based coexistence patterns between one specific POI and its surrounding objects. To clarify the idea, basic concepts about analysing coexistence patterns including design methodology and algorithms are covered in this context. Furthermore, the results of two case studies are presented to demonstrate the analytical power and reliability of the proposed technique. The encouraging results of this new recommendation tool elevates the need for developing reliable quality assurance systems in OSM and other VGI projects.
- Is Part Of:
- International journal of geographical information science. Volume 33:Issue 7(2019)
- Journal:
- International journal of geographical information science
- Issue:
- Volume 33:Issue 7(2019)
- Issue Display:
- Volume 33, Issue 7 (2019)
- Year:
- 2019
- Volume:
- 33
- Issue:
- 7
- Issue Sort Value:
- 2019-0033-0007-0000
- Page Start:
- 1420
- Page End:
- 1443
- Publication Date:
- 2019-07-03
- Subjects:
- OSM -- coexistence patterns -- spatial data quality -- spatial association rules -- spatial data mining -- points of interest
Geography -- Data processing -- Periodicals
Information storage and retrieval systems -- Periodicals
Géomatique -- Périodiques
Systèmes d'information -- Périodiques
910.285 - Journal URLs:
- http://www.tandfonline.com/loi/tgis20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/13658816.2019.1584803 ↗
- Languages:
- English
- ISSNs:
- 1365-8816
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.266150
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23815.xml