Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2178
Title: Systematic literature review of data quality within openstreetmap
Authors: Kaur J
Singh J
Sehra S.S
Rai H.S.
Keywords: Crowdsourcing
OpenStreetMap
Quality Assessment
Tags
Volunteered Geographic Information
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
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. � 2017 IEEE.
URI: 10.1109/ICNGCIS.2017.35
http://hdl.handle.net/123456789/2178
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