OpenStreetMap (OSM) produces a huge amount of labeled spatial data, but its quality has always been a deep concern. Numerous quality issues have been discussed in the vast literature, while the fitness of OSM for road navigability is only partly explored. Navigability depends on logical consistency, which focuses on the existence of logical contradictions within a data set. Researchers have discussed the insufficiency of established methods and the lack of a computational paradigm to assess the quality of the OSM data. To address the research gaps, the current work extended the capabilities of the Quantum GIS Processing Toolbox for assessment of spatial data. The models and scripts developed are able to assess logical consistency based on geographical topological consistency, semantic information, and morphological consistency. The established and proxy indicators are selected for measuring the logical consistency of OSM data for navigability. For empirical validation, OSM Punjab data are compared with authoritative data from HERE (proprietary) and the Remote Sensing Centre (RSC), Punjab, India. The results conclude that even the proprietary road data sets are not free from logical inconsistencies and data contributed by the masses are credible and navigable. OSM has produced better results than the RSC, but needs more crowd contributions to improve its quality.

中文翻译：

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扩展处理工具箱，用于评估OpenStreetMap数据的逻辑一致性

OpenStreetMap（OSM）产生大量的带标签的空间数据，但是其质量一直是人们深切关注的问题。大量文献讨论了许多质量问题，而OSM在道路通行性方面的适用性只是部分探讨。可导航性取决于逻辑一致性，逻辑一致性侧重于数据集中逻辑矛盾的存在。研究人员已经讨论了既定方法的不足和缺乏评估OSM数据质量的计算范式。为了解决研究空白，当前工作扩展了Quantum GIS处理工具箱用于评估空间数据的功能。开发的模型和脚本能够根据地理拓扑一致性，语义信息和形态一致性来评估逻辑一致性。选择已建立的和代理的指示器以测量OSM数据的逻辑一致性以进行导航。为了进行实证验证，将OSM Punjab数据与HERE（专有）和印度Punjab遥感中心（RSC）的权威数据进行比较。结果得出结论，即使是专有的道路数据集也无法摆脱逻辑上的矛盾，并且群众贡献的数据是可信且可导航的。OSM产生了比RSC更好的结果，但是需要更多的人群贡献来提高其质量。结果得出结论，即使是专有的道路数据集也无法摆脱逻辑上的矛盾，并且群众贡献的数据是可信且可导航的。OSM比RSC产生了更好的结果，但是需要更多的人群贡献来提高其质量。结果得出结论，即使是专有的道路数据集也无法摆脱逻辑上的矛盾，并且群众贡献的数据是可信且可导航的。OSM产生了比RSC更好的结果，但是需要更多的人群贡献来提高其质量。