Temporal Zooming

Spatio-temporal knowledge representation often requires changing from one level of detail or granularity to another so users can carry out a desired task. Meteorological occurrences, geological processes, or population movements, for example, can be examined at different granularities. This includes different spatial perspectives as well as temporal views where phenomena may be examined under real time conditions, or over hourly, daily, weekly, or longer periods. Moving back and forth among granularities is a necessary routine for many domain scientists. Changing to a more detailed view uncovers information that otherwise is unknown. Conversely, moving to a simpler view can improve our understanding of phenomena. Although people routinely abstract information from their environment at different granularities and perform mental shifts that increase or decrease detail, formalization of these alterations for use in information systems has proved difficult. Geographic information systems typically treat changes in granularity from the perspective of changes to the geometric properties of objects through graphic zooming. None of the current approaches to zooming offer support for performing this operation over time. This work focuses on the temporal aspects of changing granularity or temporal zooming . The approach is based on a model of change to identifiable objects. In this paper, temporal zooming involves expanding or collapsing the transitions among identity states of the same object as well as revealing or omitting other objects that are linked through transitions. A set of operations to support refining and coarsening the evolution of objects over time is presented. This work offers a new perspective on zooming important for spatio-temporal query languages and for users of large spatio-temporal databases who require the means to shift back and forth among simpler or summarized views of data and more detailed views.