An Object-Oriented Modeling and Implementation of Spatio-Temporal Knowledge Discovery System

Abstract

Spatiotemporal databases deal with changes to spatial objects with time. The Spatiotemporal knowledge discovery process involves the integration of such database systems with data warehousing, data mining and online-analytical processing technologies. The applications in this domain will process spatial, temporal and attribute data elements and use spatio-temporal relationships among these elements. These applications deal with the evolution of spatial objects and changes in their topological relationships, associations along with time. These advanced database applications require storing, management and processing of complex spatiotemporal data. In this paper we consider the classification and modeling requirements for spatiotemporal applications, System modeling, preprocessing spatiotemporal data, discovering spatiotemporal topological relationships and extension of apriori algorithm for mining spatiotemporal frequent predicates. The design of an appropriate system that can capture spatiotemporal features of datasets is discussed. Prototype implementation of the system is carried out on top of open source object relational spatial database management system called postgresql and postgis. The algorithms are experimented on historical cadastral datasets which are created using OpenJump. The results that are visualized using OpenJump software are presented.