The Crowd is the Territory: Assessing Quality in Peer-Produced Spatial Data During Disasters

Today, disaster events are mobilizing digital volunteers to meet the data needs of those on the ground. One form of this crowd work is Volunteered Geographic Information. This peer-produced spatial data creates the most up-to-date map of the affected region; maintaining the accuracy of these data is therefore a critical task. Accuracy is one aspect of data quality, a relative concept requiring standards to measure against. The field of Geographic Information Sciences has developed standards for this comparison, achieving widespread acceptance. However, the peer production model of spatial data presents new opportunitiesand challengesto traditional methods of quality assessment. Through analysis of the OpenStreetMap database, we show that temporal editing patterns and contributor characteristics can provide additional means of understanding spatial data quality. Drawing upon experiences from Wikipedia, we offer and evaluate three intrinsic quality metrics of peer-produced spatial data to assess the quality of contributions to OpenStreetMap for crisis response.