Putting Ubiquitous Computing into Context

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 (e.g., Points-of-Interests) 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 the contextual factors that determine 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 such as poverty of an area also play important roles. We discuss the implications of these findings in regards to the design of urban crowd-sourcing applications.