A prototype for ontology driven on-demand mapping of urban traffic accidents

Gould, N and Cheng, J (2016) A prototype for ontology driven on-demand mapping of urban traffic accidents. [Conference or Workshop Item]

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Abstract

Government, both national and local, is making increasing amounts of spatial data freely available. The DataGM website, for example, provides access to georeferenced data for road traffic accidents, fire and rescue incidents, bus stops, bus routes and traffic signals in Greater Manchester. However, how can thousands of road accidents be mapped legibly by the non-expert cartographer without obscuring the underlying road network? Tools such as the Google maps API provide only a partial solution in that they merely overlay data on base maps. There is no integration of user-supplied data. What is required is cartographic generalisation on-demand. But to automate the map creation process it is necessary to formalise the knowledge required for generalisation.