OpenStreetMap Editor Tag Analysis using Crowd Lens

Document Type

Oral Presentation

Campus where you would like to present

Ellensburg

Event Website

https://digitalcommons.cwu.edu/source

Start Date

16-5-2019

End Date

16-5-2019

Abstract

As intelligent mapping and open source projects continue to develop globally, so does the question of whether or not this information is reliable. Observing an open source mapping project such as Open Street Map (OSM), one must consider the motives behind what has been mapped. Working with Dr. Sterling Quinn and his Crowd Lens for OSM tool, the contributors to 14 different cities around the globe have been analyzed dating back to 2007. Within OSM, editors use tags to delineate their changes. Analyzing these tags and their variance through different cities within Crowd Lens shows patterns within OSM, providing valuable insight into the different styles of editors and their motives for adding to the project. Several patterns emerged for tags that were commonly or nearly always used in union with others. These patterns varied slightly from study area to study area, but often broader patterns were visible which could be applied to many different locations. This kind of data allows for OSM critics or analysts to have a broader understanding of the observed editors, while also helping us to understand the reliability of OSM data.

Department/Program

Geography

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May 16th, 10:00 AM May 16th, 11:30 AM

OpenStreetMap Editor Tag Analysis using Crowd Lens

Ellensburg

As intelligent mapping and open source projects continue to develop globally, so does the question of whether or not this information is reliable. Observing an open source mapping project such as Open Street Map (OSM), one must consider the motives behind what has been mapped. Working with Dr. Sterling Quinn and his Crowd Lens for OSM tool, the contributors to 14 different cities around the globe have been analyzed dating back to 2007. Within OSM, editors use tags to delineate their changes. Analyzing these tags and their variance through different cities within Crowd Lens shows patterns within OSM, providing valuable insight into the different styles of editors and their motives for adding to the project. Several patterns emerged for tags that were commonly or nearly always used in union with others. These patterns varied slightly from study area to study area, but often broader patterns were visible which could be applied to many different locations. This kind of data allows for OSM critics or analysts to have a broader understanding of the observed editors, while also helping us to understand the reliability of OSM data.

https://digitalcommons.cwu.edu/source/2019/Oralpres/106