Formal models for managing spatiotemporal data

Databases supposedly model reality, but conventional database management systems lack the capability to record and process time-varying aspects of the real world. Besides the agony of the accidental delete, this is the main drawback that digital databases have in comparison to analog ones. The problem of managing temporal data in a spatial database is further exacerbated by the veritable explosion of data encountered if multiple, time-stamped copies of already large spatial images are stored. This work presents several formal models for managing spatiotemporal data. Full formal models based on the space-time composite data structure are developed using first order predicate calculus for raster and vector data. The correctness of the models is shown along with examples of how to use them. A less formal model for managing spatiotemporal databases with multiple spatial representations is presented. This model follows guidelines used in designing heterogeneous databases. The work also presents an abstract, machine-independent strategy for measuring spatiotemporal complexity and developing spatiotemporal software metrics.