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Research >> Projects

DISTIL: A Design Support Environment for Conceptual Modeling of Spatiotemporal Requirements
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Geographic information is increasingly employed for a wide array of applications, e.g., land information systems, environmental modeling, resource management, transportation planning, geo-marketing, geology and archaeology. Geographic information may be defined as having a theme-the phenomenon or object being observed, the location of the phenomenon, and the time related to the phenomenon. Conventional conceptual models do not provide a mechanism to capture the semantics related to location and time; as a result, the users' spatiotemporal data requirements cannot be adequately captured during conceptual design.
We are developing DISTIL (Distributed design of SpaTIotemporaL data), a web-based conceptual modeling tool that can help capture the semantics of spatiotemporal data, e.g., event and state, valid time, existence time and transaction time, various types of geometries associated with spatiality, user-defined granularities, indeterminacy, and topological relationships. DISTIL is based on an annotated semantic model, referred to as ST-USM (Spatiotemporal Unifying Semantic Model). An annotation-based approach in DISTIL divides conceptual design into two steps; it first captures the current reality of an application using a conventional semantic model without considering the spatial aspects, and only then annotates the schema with spatiotemporal semantics of the application resulting in an ST-USM schema. We provide mapping rules from an annotated ST-USM schema to a conventional conceptual schema, from which the logical schema can be derived. A geographically distributed database development team can use DISTIL to capture and validate their data requirements.
Using DISTIL we demonstrate an approach for capturing spatiotemporal requirements that is straightforward to implement, that satisfies ontology-based and cognition-based requirements, and that integrates seamlessly into the existing database design methodology.
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