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Reliability extracted from the history file as an intrinsic indicator for assessing the quality of OpenStreetMap

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Abstract

Volunteered geographic information (VGI) is a large and up-to-date data source, which is available to the public easily. VGI enables public participation by leveraging scientific research and ease of data entry. OpenStreetMap (OSM) is one of the most popular examples of a volunteered geographic information project that has turned into a major source as the substitution of geographical data over the past years. Because OSM data quality is very variable, its various aspects have been investigated in previous studies. Assessing the reliability of volunteered geographic data has been a topic of interest to researchers during recent years. The objective of this study is to introduce an approach for computing the reliability indicators as tools for assessing OSM data quality using the history of data. To prepare the data required, the history file of the OSM dataset for the study region was extracted. Then, historical data cleaning was carried out by identifying and eliminating the outlier data. Afterward, the reliability indicator was calculated through criteria such as the number of versions, the number of user participation, temporal variations, and the number of tags editing. In the last step, to evaluate the proposed approach in calculating the reliability indicator, the level of feature reliability was compared with their spatial accuracy calculated via feature matching of the OSM and official data. The results show among 7478 reliability features of the OSM, approximately 4338 feature involves reliability of above 50%, containing 58.01% of the datasets, and among 5659 matching features of the OSM dataset, 4429 features have a similarity percentage of above 70%, containing 78.26% of the datasets. Increasing the number of versions, the number of users, and the temporal variation range of a route increased the reliability. Contrastingly, tag editing reduces reliability. Moreover, according to the results, a correlation coefficient of 0.695 between the reliability and spatial accuracy indicates a direct relationship of reliability in the quality of the OSM dataset.

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Authors and Affiliations

  1. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Najmeh Teimoory & Rahim Ali Abbaspour

  2. Faculty of Mining Engineering, Sahand University of Technology, Tabriz, Iran

    Alireza Chehreghan

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  1. Najmeh Teimoory
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  2. Rahim Ali Abbaspour
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  3. Alireza Chehreghan
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Correspondence to Alireza Chehreghan.

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Communicated by: H. Babaie

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Teimoory, N., Ali Abbaspour, R. & Chehreghan, A. Reliability extracted from the history file as an intrinsic indicator for assessing the quality of OpenStreetMap. Earth Sci Inform 14, 1413–1432 (2021). https://doi.org/10.1007/s12145-021-00675-6

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