Collaborative Geospatial Feature Search Full text

George Lamprianidis, Dieter Pfoser
Proc. 20th ACM SIGSPATIAL GIS Conference
Abstract. The ever-increasing stream of Web and mobile applications addressing geospatial data creation has been producing a large number of user-contributed geospatial datasets. This work proposes a means to query such data using a collab- orative Web-based approach. We employ crowdsourcing to the fullest in that used-generated point-cloud data will be mined by the crowd not only by providing feature names, but also by contributing computing resources. We employ browser-based collaborative search for deriving the extents of geospatial objects (Points of Interest) from point-cloud data such as Flickr image locations and tags. The data is aggregated by means of a hierarchical grid in connection with an exploratory and a refinement search phase. A per- formance study establishes the effectiveness of our approach with respect to the amount of data that needs to be retrieved from the sources and the quality of the derived spatial fea- tures.