Duarte-2018a

Conference proceedings article

There are a growing number of applications and services based on spatiotemporal data in the most diverse areas of knowledge and human activity. This comes from the emergence of technologies that can obtain data about real-world phenomena over time. These data consist of discrete observations of the evolution i.e., the changes in position or shape and extent, of these phenomena over time but we are often interested in the representation of its continuous evolution. As a consequence, we need to have methods capable of representing the evolution of a phenomenon at all times between two known observations. The representation of the continuous evolution of moving regions, i.e., entities (or objects) whose position, shape and extent change continuously over time, is an ongoing research topic. In this paper we present a framework for the representation and management of moving objects data (in particular moving regions data) that uses compatible triangulation and rigid interpolation methods to represent their continuous evolution over time. The aim is to obtain a realistic representation of such evolution and at the same time maintain compatibility with existing spatial data management systems currently in use. We also present a spatiotemporal database extension that uses this framework and usage examples showing how to perform operations combining numeric, spatial, and spatiotemporal data.