Viewing streaming spatially-referenced data at interactive rates

Abstract

Given the increasing prevalence of streaming spatially-referenced datasets resulting from sensor networks usually consisting of text objects of varying length (termed labels) as well as streaming spatially oriented queries leads to closer scrutiny of mapping interfaces to present the data to users. These interfaces must cope with the fact that the labels associated with each location are constantly changing and that there are too many objects to display clearly within the interface. An algorithm meeting these challenges is presented. It differs from classical methods by avoiding expensive pre-computation steps, thereby allowing different labels to be associated with locations without needing to completely recompute the layout. In other words, we are addressing a write-many read-many setting instead of the conventional write-once read-many setting. Our experiments show consistent sub-second query times for query windows that contain as many as 11 million data objects, with only slight differences in the set of displayed labels when compared to an exhaustive baseline algorithm. This enables the algorithm to be used in a mapping application that involves both streaming data and streaming queries such as windowing realized by real-time, continuous zooming and panning operations.