Abstract: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. OPEN ACCESSFuture Internet 2012, 4 2

OpenStreetMap (OSM) is one of the most popular examples of a Volunteered Geographic Information (VGI) project. In the past years it has become a serious alternative source for geodata. Since the quality of OSM data can vary strongly, different aspects have been investigated in several scientific studies. In most cases the data is compared with commercial or administrative datasets which, however, are not always accessible due to the lack of availability, contradictory licensing restrictions or high procurement costs. In this investigation a framework containing more than 25 methods and indicators is presented, allowing OSM quality assessments based solely on the data's history. Without the usage of a reference data set, approximate statements on OSM data quality are possible. For this purpose existing methods are taken up, developed further, and integrated into an extensible open source framework. This enables arbitrarily repeatable intrinsic OSM quality analyses for any part of the world.

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Abstract:The OpenStreetMap (OSM) project, founded in 2004, has gathered an exceptional amount of interest in recent years and counts as one of the most impressive sources of Volunteered Geographic Information (VGI) on the Internet. In total, more than half a million members had registered for the project by the end of 2011. However, while this number of contributors seems impressive, questions remain about the individual contributions that have been made by the project members. This research article contains several studies regarding the contributions by the community of the project. The results show that only 38% (192,000) of the registered members carried out at least one edit in the OSM database and that only 5% (24,000) of all members actively contributed to the project in a more productive way. The majority of the members are located in Europe (72%) and each member has an activity area whose size may range from one soccer field up to more than 50 km 2 . In addition to several more analyses conducted for this article, predictions will be made about how this newly acquired knowledge can be used for future research.

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Volunteered Geographic Information (VGI) projects and their crowdsourced data have been the focus of a number of scientific analyses and investigations in recent years. Oftentimes the results show that the collaboratively collected geodata of one of the most popular VGI projects, OpenStreetMap (OSM), provides good coverage in urban areas when considering particular completeness factors. However, results can potentially vary significantly for different world regions. In this article, we conduct an analysis to determine similarities and differences in data contributions and community development in OSM between 12 selected urban areas of the world. Our findings showed significantly different results in data collection efforts and local OSM community sizes. European cities provide quantitatively larger amounts of geodata and number of contributors in OSM, resulting in a better representation of the real world in the dataset. Although the number of volunteers does not necessarily correlate with the general population density of the urban areas, similarities could be detected while comparing the percentage of different contributor groups and the number of changes they made to the OSM project. Further analyses show that socio-economic factors, such as income, can have an impact on the number of active contributors and the data provided in the analyzed areas. Furthermore, the results showed significant data contributions by members whose main territory of interest lies more than one thousand kilometers from the tested areas. OPEN ACCESSFuture Internet 2013, 5 283

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