Indexing Techniques for Continuously Evolving Phenomena

The management of spatial, temporal, and spatiotemporal data is becoming increasingly important in a wide range of applications. This ongoing Ph.D. project focuses on applications where spatial or temporal aspects of objects are continuously changing and there is a need for indexing techniques that ”track” the changing data, even in-between explicit updates. In spatiotemporal applications, there is a need to record and efficiently query the history, the current state, and the predicted future behavior of continuously moving objects, such as vehicles, mobile telephones, and people. Likewise, in temporal applications and spatiotemporal applications with discrete change, time intervals may be naturally related to the current time, which continuously progresses. The paper outlines the research agenda of the Ph.D. project and describes briefly two access methods developed so far in this project.