ArticleTransactions in GIS : TG2025
Mapping the Completeness and Positional Accuracy of OpenStreetMap Road Data at the County Level in the Contiguous United States.
Article in Transactions in GIS : TG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The OpenStreetMap (OSM) project allows volunteers in the community to contribute and manage spatial data collaboratively and provides free spatial data with global coverage to the public. OSM data have been widely used in many applications. However, the quality of OSM data can be inconsistent due to the crowdsourcing nature of the OSM project. This study compares the OSM road data with the national road data from the U.S. Census Topologically Integrated Geographic Encoding and Referencing system (TIGER) project in the contiguous United States. Specifically, we used three indicators to examine the completeness and positional accuracy of the OSM road data at the county level. Then we performed spatial analysis to study the patterns of the discrepancies. Our results show that OSM road data are inconsistent in completeness and positional accuracy across different counties. Finally, we compared the three indicators among metropolitan, nonmetropolitan, and rural counties with Analysis of Variance (ANOVA) and Boxplot. The results show that the OSM road data in metropolitan counties have better completeness and positional accuracy than those in nonmetropolitan and rural counties. This study can improve our understanding of the quality of OSM road data in the United States, which in turn can help the OSM community improve the quality of road data and allow data users to better use OSM road data in different applications.
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Registered trials
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