The objective of this research is to formally define a spatio-temporal conceptual model that captures data semantics required for temporal and geospatial applications. We show how the proposed model provides a metaphor that bridges the semantic gap between the real world and its spatio-temporal representation in information systems. Our multi-methodological research approach includes: (i) formally defining a spatio-temporal semantic model called ST USM (Spatio-Temporal Unifying Semantic Model); (ii) evaluating the proposed model using a case study and a laboratory study; and (iii) demonstrating practicality of our proposed model using a proof-of-concept prototype system. We describe a spatio-temporal conceptual modeling approach--applicable to any conventional conceptual model--that incorporates sequenced and nonsequenced space/time semantics. We have applied our annotation-based approach to the Unifying Semantic Model (USM)--a conventional conceptual model--to propose ST USM. ST USM is an upward-compatible, snapshot reducible, annotation-based spatio-temporal conceptual model that can comprehensively capture semantics related to space and time without adding any new spatio-temporal constructs. We provide formal semantics of ST USM via a mapping to conventional USM and constraints (expressed in first-order logic), from which the logical schema can be derived. To evaluate the proposed model, we conducted a case study at the US Geological Survey that helped us assess the extent to which the proposed formalism helps capture all the spatio-temporal data semantics for an application. We show that ST USM is ontologically expressive and leads to schemas that completely capture the requisite spatio-temporal semantics. We conducted a laboratory study and found that an annotation-based approach to capturing the spatio-temporal semantics does not adversely impact the schema comprehension as compared with conventional conceptual models (e.g., USM). This implies that annotations provide an intuitive straightforward mechanism to capture the spatio-temporal requirements and can be usefully employed to capture spatio-temporal semantics accurately. We describe DISTIL (DesIgn-support environment for SpaTIo-temporaL data), a web-based conceptual modeling prototype system that can help capture semantics of spatio-temporal data. Using DISTIL, we demonstrate that the annotation-based approach to capturing spatio-temporal requirements is straightforward to implement, satisfies ontology-based and cognition-based requirements, and integrates seamlessly into existing database design methodologies.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/280030 |
| Date | January 2002 |
| Creators | Khatri, Vijay |
| Contributors | Ram, Sudha |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Dissertation-Reproduction (electronic) |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
Page generated in 0.0022 seconds