2026-07-27T05:06:47Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:9389 2024-03-06T10:44:12Z ddc:004 open_access

Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach (Short Paper) Truong, Quy Thy Touya, Guillaume de Runz, Cyril Vandalism Volunteered Geographic Information Outlier detection Vandalism is a phenomenon that has affected by now the digital domain, in particular in the context of Volunteered Geographic Information projects. This paper aims at proposing a methodology to detect vandalism in the OpenStreetMap project. First, an analysis of related works sheds light on the lack of consensus when it comes to defining vandalism in VGI from both conceptual and practical points of view. Second, we present experiments on the use of clustering-based outlier detection methods to identify vandalism in OSM. The outcome of this study focuses on choosing the right variables when it comes to detecting vandalism in OSM. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Quy Thy Truong and Guillaume Touya and Cyril de Runz 2018 Is Part Of LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.GISCIENCE.2018.61 urn:nbn:de:0030-drops-93897 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.61 eng https://creativecommons.org/licenses/by/3.0/legalcode