Analyzing OpenStreetMap Road Data and Characterizing the Behavior of Contributors in Ankara, Turkey

Abstract

The usage of OpenStreetMap (OSM), one of the resources offered by Volunteered Geographic Information (VGI), has rapidly increased since it was first established in 2004. In line with this increased usage, a number of studies have been conducted to analyze the accuracy and quality of OSM data, but many of them have constraints on evaluating the profiles of contributors. In this paper, OSM road data have been analyzed with the aim of characterizing the behavior of OSM contributors. The study area, Ankara, the capital city of Turkey, was evaluated with several network analysis methods, such as completeness, degree of centrality, betweenness, closeness, PageRank, and a proposed method measuring the activation of contributors in a bounded area from 2007–2017. An evaluation of the results was also discussed in this paper by taking into account the following indicators for each year: number of nodes, ways, contributors, mean lengths, and sinuosity values of roads. The results show that the experience levels of the contributors determine the contribution type. Essentially, more experience makes for more detailed contributions.

OpenStreetMap history for intrinsic quality assessment: Is OSM up-to-date?

“…Availability of OSM history was also exploited for the intrinsic analysis of the temporal evolution of specific OSM objects. For example, the growth of the OSM road network was analyzed for countries such as Ireland [53] and Germany [54], and cities such as Beijing [55] and Ankara [56]. Barrington-Leigh and Millard-Ball assessed the completeness of the OSM road network at the global level -finding a value of about 83% -by also studying its historical growth [17].…”

Human-Centric Data Science for Urban Studies

“…Street networks. Three issue papers used a network science approach to street network analysis [65][66][67]. Yang et al [67] analyzed changes in the spatio-temporal characteristics of the spatial-interaction networks of Beijing, finding specific changes in connections, which play a vital role in understanding urban spatial heterogeneity.…”

“…Agryzkov et al [66] proposed a new centrality measure for complex networks based on PageRank to establish a ranking of nodes considering the importance of some dataset associated to the network, evaluated on a street network. Hacar et al [65] analyzed OpenStreetMap road data to characterize the behavior of OpenStreetMap contributors, finding that more experienced contributors make for more detailed contributions.…”

A Comparative Analysis Through Time and Space of Centrality’s Role in County Centers’ Spatial Position for Several Counties in Romania

“…OpenStretMaps data being a Volunteered Geographic Information (VGI) it's normal to check the data accuracy. Fortunately, there are studies about this issue testing the data accuracy from China (Wang et al, 2013) through Turkey (Hacar et al, 2018) and Germany (Helbich et al, 2012) to Great Britain (Haklay, 2010) and Ireland (Ciepłuch et al, 2010). Hacar and collaborators emphasizes how the volunteers experience level determines the accuracy.…”