Quality Assessment of the French OpenStreetMap Dataset

Abstract

The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user-generated content.

Social Moderation and Dynamic Elements in Crowdsourced Geospatial Data: A Report on Quality Assessment, Dynamic Extensions and Mobile Device Engagement in the George Mason University Geocrowdsourcing Testbed

“…adequacy on consistency with previous findings in other geocrowdsourced data quality studies, such as Haklay (2010) 66 , Girres and Touya (2010) 67 , and Ramm et al (2011) 68 , who find that positional error is typically within 5-6 meters in OSM studies (as summarized in Table 6). We also use Camponovo and Freundschuh's (2014) 69 research on prior knowledge of categorical accuracy of geocrowdsourced data.…”

“…Notable publications from this era include Veregin and Hunter (1998) 112 , Goodchild and Gopal (1989) 113 , and Guptill and Morrison (1995) 114 . Many of the recent research papers in quality assessment for geocrowdsourced data (i.e., Haklay 2010, Girres andTouya 2010) refer back to these earlier traditional GIS-based quality assessment works. 115,116 We wonder how far the traditional approaches for quality assessment can be stretched to fit what is emerging in geocrowdsourcing and geosocial media.…”

“…While it is easy to see the influences and sensibility of NMAS, NSSDA, and GIS quality assessment approaches in Girres and Touya (2010) 117 , these approaches begin to crumble when faced with unstructured geosocial media and aggregations of geocrowdsourced and linked data. Measurements related to horizontal positional accuracy begin to lose meaning when dealing with disparate collections of semi-structured geocrowdsourced data and unstructured geosocial media.…”

Using OSM for LBS – An Analysis of Changes to Attributes of Spatial Objects

“…This work also highlighted problems with the quality of the shape representation of polygon features representing natural features in OSM when compared with NMA data for the same features. However other studies such as Over et al (2010), Haklay (2010), Girres and Touya (2010) compares OSM very favourably, in terms of geometric accuracy, against road and street network databases from National Mapping Agencies and commercial sources. Fritz et al (2009) even suggest at using OSM and other crowd-sourced VGI as an alternative approach for "validating and calibrating global land cover".…”

Dynamically Integrating OSM Data into a Borderland Database

“…Zielstra and Zipf [4] analyzed the completeness of OSM data relative to the navigation data of the TeleAtlas MultiNet datasets in Germany. Girres and Touya [5] completed a quality assessment of France OSM spatial data using the Large-Scale Reference database (RGE) for reference data and a sampling method using the assessment components, i.e., geometric accuracy, attribute accuracy, completeness, logical consistency, semantic accuracy, temporal accuracy, lineage, and usage. Cipeluch et al compared the accuracy of Ireland OSM data with Google Maps and Bing Maps [6].…”