Semantic data modeling of spatiotemporal database applications

Due to the ubiquity of space-related and time-related information, the abil ity of a database system to deal with both spatial and temporal phenomenon facts in a spatiotemporal applications is highly desired. However, uncertai n and fuzzy information in these applications highly increases the complexi ty of database modeling. In this paper we introduce a semantic data modelin g approach for spatiotemporal database applications. We specifically focus on various aspects of spatial and temporal database issues and uncertainty and fuzziness in various abstract levels. The semantic data model that we i ntroduce in this paper utilizes unified modeling language (UML) for handlin g spatiotemporal information, uncertainty, and fuzziness especially at the conceptual level of database design. An environmental information system (E IS) application is used to illustrate our modeling approach and extension m ade to UML. By incorporating uncertainty and fuzziness into the semantic da ta model of a spatiotemporal EIS database application, one can handle pollu tion summary, analysis, and even pollution predictions, in addition to the other common uses of a database system. (C) 2001 John Wiley & Sons, Inc.