Assessing the Topological Consistency of Crowdsourced OpenStreetMap Data

Sukhjit Singh Sehra
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引用次数: 10

Abstract

OpenStreetMap is world leader in collecting map data contributed by users, called crowdsourcing. But we have little knowledge about the people who collect it, their skills, knowledge or patterns of data collection. Also OpenStreetMap has loose coordination and no top-down quality assurance processes. This makes map data more vulnerable to errors and incomplete. To make the map data navigable, it must not have errors. The current proposal has been conducted to identify errors OpenStreetMap data. Small area of Punjab has been taken as test data for finding inconsistencies. It has been concluded that data contains lots of such errors and is not mature enough to be commercial purposes.
评估众包OpenStreetMap数据的拓扑一致性
OpenStreetMap在收集用户贡献的地图数据方面处于世界领先地位,这被称为众包。但我们对收集数据的人、他们的技能、知识或数据收集模式知之甚少。此外,OpenStreetMap有松散的协调,没有自上而下的质量保证过程。这使得地图数据更容易出错和不完整。要使地图数据可导航,它必须没有错误。目前的建议是用来识别OpenStreetMap数据中的错误。旁遮普的一小块地区被用作发现不一致的测试数据。得出的结论是,数据中包含了很多这样的错误,并且还不够成熟,无法用于商业目的。
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