Are Crowdsourced Datasets Suitable for Specialized Routing Services? Case Study of OpenStreetMap for Routing of People with Limited Mobility

Abstract

Nowadays, Volunteered Geographic Information (VGI) has increasingly gained attractiveness to both amateur users and professionals. Using data generated from the crowd has become a hot topic for several application domains including transportation. However, there are concerns regarding the quality of such datasets. As one of the most famous crowdsourced mapping platforms, we analyze the fitness for use of OpenStreetMap (OSM) database for routing and navigation of people with limited mobility. We assess the completeness of OSM data regarding sidewalk information. Relevant attributes for sidewalk information such as sidewalk width, incline, surface texture, etc. are considered, and through both extrinsic and intrinsic quality analysis methods, we present the results of fitness for use of OSM data for routing services of disabled persons. Based on empirical results, it is concluded that OSM data of relatively large spatial extents inside all studied cities could be an acceptable region of interest to test and evaluate wheelchair routing and navigation services, as long as other data quality parameters such as positional accuracy and logical consistency are checked and proved to be acceptable. We present an extended version of OSMatrix web service and explore how it is employed to perform spatial and temporal analysis of sidewalk data completeness in OSM. The tool is beneficial for piloting activities, whereas the pilot site planners can query OpenStreetMap and visualize the degree of sidewalk data availability in a certain region of interest. This would allow identifying the areas that data are mostly missing and plan for data collection events. Furthermore, empirical results of data completeness for several OSM data indicators and their potential relation to sidewalk data completeness are presented and discussed. Finally, the article ends with an outlook for future research study in this area.

The use of geometric indicators to estimate the quantitative completeness of street blocks in OpenStreetMap

“…The application of demographic and socioeconomic indicators has also revealed that OSM data completeness is affected by both population density (Zielstra & Zipf, ) and the income levels of contributors (Neis, Zielstra, & Zipf, ), while Camboim et al () have also shown that road completeness in urban areas is moderately well correlated with population density. The application of contributor indicators also led Mobasheri, Sun, Loos, and Ali () to the conclusion that the total number of OSM users has a direct impact on sidewalk information volume in these products. Most previous assessments have, however, been based on conceptual descriptions or qualitative analyses; for example, Camboim et al () demonstrated the presence of a correlation between road completeness and population density, but did not investigate how the latter could be utilized to quantitatively estimate the former, while Gröchenig, Brunauer, and Rehrl () qualitatively classified the completeness of OSM datasets into three phases encompassing “start,” “growth,” and “saturation” based on an analysis of dataset historical activity but did not quantify the completeness (e.g., between 60 and 80%) of each phase.…”

An Analysis of the Evolution, Completeness and Spatial Patterns of OpenStreetMap Building Data in China

“…Fan [35] used "development of building count over time" which was also based on analyzing the historical data in OSM. Mobasheri et al [36] analyzed the OSM sidewalk data by counting the number of road segments with/without a tag. Recently, Zhou [37] proposed using OSM building density as a proxy indicator to quantitatively estimate OSM building completeness.…”

Circuity Characteristics of Urban Travel Based on GPS Data: A Case Study of Guangzhou

“…For example, Hendawi point out the proliferation of volunteered geographic information (VGI) such as GPS tracks donated by individuals via forums such as OpenStreetMap has created an opportunity for providing next generation routing services [22]. Mobasheri proved crowdsourced datasets are suitable for specialized routing services [23]. Graser pointed out that the quality of these data sources and OpenStreetMap, in particular, is sufficient for answering questions about the heterogeneous nature of VGI in general [24].…”