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DOI: 10.4230/LIPIcs.GISCIENCE.2018.61

Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach (Short Paper)

Authors: Quy Thy Truong, Guillaume Touya, and Cyril de Runz

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract

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.

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Quy Thy Truong, Guillaume Touya, and Cyril de Runz. Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 61:1-61:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{truong_et_al:LIPIcs.GISCIENCE.2018.61,
  author =	{Truong, Quy Thy and Touya, Guillaume and de Runz, Cyril},
  title =	{{Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{61:1--61:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.61},
  URN =		{urn:nbn:de:0030-drops-93897},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.61},
  annote =	{Keywords: Vandalism, Volunteered Geographic Information, Outlier detection}
}

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Towards Vandalism Detection in OpenStreetMap Through a Data Driven Approach (Short Paper)

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