Capturing Fuzziness and Uncertainty of Spatiotemporal Objects

For the majority of spatiotemporal applications, we assume that the modeled world is precise and bound. This simplification seems unnecessary crude for many environments handling spatial and temporal extents, such as navigational applications. In this work, we explore fuzziness and uncertainty, which we subsume under the term indeterminacy, in the spatiotemporal context. We first show how the fundamental modeling concepts of spatial objects, attributes, relationships, time points, time periods, and events are influenced by indeterminacy, and then show how these concepts can be combined. Next, we focus on the change of spatial objects according to their geometry over time. We outline four scenarios, which identify discrete and continuous change, and we present how to model indeterminate change. We demonstrate the applicability of this proposal by describing the uncertainty related to the movement of point objects, such as the recording of the whereabouts of taxis.