Publication | Open Access
The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011
391
Citations
23
References
2011
Year
Germany 2007–2011EngineeringUrban InformaticsGeovisualizationProprietary DatasetOsm DatasetSocial SciencesGeographic Information SystemsCrowdsourced MapsData ScienceData ManagementStatisticsTransportation SystemsMobility DataCartographyStreet Network EvolutionTransportation GeographyCrowdsourcingUrban GeographyVolunteered Geographic InformationDigital GeographyCommercial DatasetLocation InformationBig Data
OpenStreetMap is a leading example of Volunteered Geographic Information, with hundreds of thousands of contributors worldwide, yet data contributions vary geographically; Germany is among the most active countries, leading to extensive development of its street network. The study investigates how the German OSM street network compares to a commercial dataset. The authors analyze the scale of topological errors, completeness of turn restrictions, and street name information in the OSM network. In June 2011 the OSM street network differed by only 9 % from the commercial dataset for car navigation, yet overall it surpassed the proprietary data by 27 %, and projections suggest when OSM will be considered complete relative to commercial sources.
The OpenStreetMap (OSM) project is a prime example in the field of Volunteered Geographic Information (VGI). Worldwide, several hundred thousand people are currently contributing information to the “free” geodatabase. However, the data contributions show a geographically heterogeneous pattern around the globe. Germany counts as one of the most active countries in OSM; thus, the German street network has undergone an extensive development in recent years. The question that remains is this: How does the street network perform in a relative comparison with a commercial dataset? By means of a variety of studies, we show that the difference between the OSM street network for car navigation in Germany and a comparable proprietary dataset was only 9% in June 2011. The results of our analysis regarding the entire street network showed that OSM even exceeds the information provided by the proprietary dataset by 27%. Further analyses show on what scale errors can be reckoned with in the topology of the street network, and the completeness of turn restrictions and street name information. In addition to the analyses conducted over the past few years, projections have additionally been made about the point in time by which the OSM dataset for Germany can be considered “complete” in relative comparison to a commercial dataset.
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