How a personalized geowiki can help bicyclists share information more effectively
Proceedings of the 2007 international symposium on Wikis
The computational geowiki: what, why, and how
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Measuring self-focus bias in community-maintained knowledge repositories
Proceedings of the fourth international conference on Communities and technologies
Eliciting and focusing geographic volunteer work
Proceedings of the 2010 ACM conference on Computer supported cooperative work
On the "localness" of user-generated content
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Lurking? cyclopaths?: a quantitative lifecycle analysis of user behavior in a geowiki
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
WP:clubhouse?: an exploration of Wikipedia's gender imbalance
Proceedings of the 7th International Symposium on Wikis and Open Collaboration
Proceedings of the 7th International Symposium on Wikis and Open Collaboration
On the accuracy of urban crowd-sourcing for maintaining large-scale geospatial databases
Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration
Temporal analysis of activity patterns of editors in collaborative mapping project of OpenStreetMap
Proceedings of the 9th International Symposium on Open Collaboration
Mind the map: the impact of culture and economic affluence on crowd-mapping behaviours
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Modelling growth of urban crowd-sourced information
Proceedings of the 7th ACM international conference on Web search and data mining
| Hi-index | 0.00 |
Ubiquitous crowd-sourcing has become a popular mechanism to harvest knowledge from the masses. OpenStreetMap (OSM) is a successful example of ubiquitous crowd-sourcing, where citizens volunteer geographic information in order to build and maintain an accurate map of the changing world. Research has shown that OSM information is accurate, by comparing it with centrally maintained spatial information such as Ordnance Survey. However, we find that coverage is low and non uniformly distributed, thus challenging the suitability of ubiquitous crowd-sourcing as a mechanism to map the whole world. In this paper, we investigate what contextual factors correlate with coverage of OSM information in urban settings. We find that, although there is a direct correlation between population density and information coverage, other socio-economic factors also play an important role. We discuss the implications of these findings with respect to the design of urban crowd-sourcing applications.