Toward Spatio-Temporal Patterns

Our world is changing at an increasing pace causing the validity intervals of information to shrink. Therefore, the change of information becomes important information itself an important information resource that should be exploitable by query languages. In particular, information about the position and extent of objects is of high interest in many areas of science and elsewhere (vehicle tracking, history, security, health care, ecology, weather prediction, urban planning, and so on). In all these areas relevant information has to be extracted from huge data sets. Beyond data mining that often serves the purpose of identifying interesting objects in spatial or spatiotemporal data sets, queries are of interest that find out about relationships between objects once they have been identified. In the realm of spatiotemporal databases this means to find out, in particular, about the changes that objects and their relationships undergo. Moreover, many applications require not only the detection of one single change, but rather look for sequences of changes describing particular developments.