Enhancing user-generated spatial data
More than ever before, citizens are harnessing web tools to create, collect and disseminate geographic data. This growth in volunteered geographic information (VGI) can lead to the inclusion of subjective or emotional data by people with no formal training. The quality and reliability of VGI techniques is a topic of much debate among government agencies and private industry responsible for accessing, manipulating or analysing spatial data via geographic information systems. To address the issue, the EU-funded 'Deriving spatial data from volunteered geographic information' (VGI_SLAM) project is designing new methodologies to supply first-rate spatial data from VGI. To better understand what influences the quality of spatial data, project members began by examining both VGI and traditional mapping carried out by the geospatial community. They found that quality can be improved by automating both mapping processes, thus reducing the amount of labour required to complete geospatial information tasks. Project partners are developing a methodology to automate the procedure for adding semantic data to street networks generated by a free and editable global map. To achieve this, they used a Boston street network supplied by the popular collaborative mapping wiki. VGI_SLAM envisions cost-effective and superior quality data for the geospatial community and citizens alike. The project will provide ways to benefit from user-generated geospatial content and crowdsourcing of high-quality geospatial data sets.
