OpenStreetMap (OSM) data quality is a concern when compared to propriety data. Inspired by other OSM projects, the Map Quality Measurement initiative intends to visualize map quality with a heat-map approach by summarizing map error indicators within relevant grids. We are not simply indicating areas that are missing map quality, we are providing insight for prioritization by overlapping social-economic metrics (e.g., population density, road density, etc.) to enable people-first decision-making when deciding where to improve map quality. The Map Quality Measure (MQM) is a heat-map style representation showing the map quality. To make MQM informative, the size and value of each grid used to summarize quality is sensitive to local context. Our project is developing an automated process to find the optimal grid size and update in response to an update trigger on demand. As to quality indicators, our project provides several examples to illustrate the high-level workflow, so methods can be replicated by others in the OSM Community. Last, we plan to create an interface for community members to contribute and share their map quality indicators. As a collaborative effort going forward, MQM can work in concert with other community initiatives and inform on where to contribute efforts.
Map matching is a key part of many GIS applications, linking observed GPS traces to road networks via a map, and allowing inference both of more accurate trajectories and of properties of...
