Systematic Literature Review of Data Quality Within OpenStreetMap

Jasmeet Kaur, Jaiteg Singh, Sukhjit Singh Sehra, H. Rai
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引用次数: 11

Abstract

This paper conducts a systematic literature review aims to identify current research and directions in terms of quality of OpenStreetMap data. OpenStreetMap is a valuable source of geographical data. Worldwide several people with different mapping experience and skills are contributing data to the free geo-database by using different mapping gadgets. This makes the OpenStreetMap data more vulnerable to errors and gaps. So we have performed a systematic literature review to find existing literature which is focused upon various quality issues in crowd-sourced data. The results are analyzed that addresses different formulated research questions. After performing systematic analysis, we have found that major focus of researchers is on assessment of positional accuracy of OpenStreetMap data. Many types of errors are still unexplored. The results of our study also showed that most of the researchers have assessed OpenStreetMap data by comparing it with other datasets. These methods are not suitable in absence of authoritative datasets. Hence assessment through intrinsic indicators would be more preferable.
OpenStreetMap数据质量的系统文献综述
本文进行了系统的文献综述,旨在确定目前在OpenStreetMap数据质量方面的研究和方向。OpenStreetMap是一个有价值的地理数据来源。在世界范围内,许多具有不同制图经验和技能的人正在使用不同的制图工具向免费的地理数据库提供数据。这使得OpenStreetMap的数据更容易受到错误和空白的影响。因此,我们进行了系统的文献综述,寻找现有的文献,这些文献主要关注众包数据中的各种质量问题。结果分析,解决不同的制定研究问题。经过系统分析,我们发现研究人员的主要关注点是OpenStreetMap数据的定位精度评估。许多类型的错误仍未被探索。我们的研究结果还表明,大多数研究人员通过将OpenStreetMap数据与其他数据集进行比较来评估它。这些方法在缺乏权威数据集的情况下不适用。因此,通过内在指标进行评估更为可取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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