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Bridging the spatio-temporal semanti...

Khatri, Vijay.

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Bridging the spatio-temporal semantic gap: A theoretical framework, evaluation and a prototype system.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Bridging the spatio-temporal semantic gap: A theoretical framework, evaluation and a prototype system./
作者:	Khatri, Vijay.
面頁冊數:	320 p.
附註:	Director: Sudha Ram.
Contained By:	Dissertation Abstracts International63-05A.
標題:	Education, Business. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3053898
ISBN:	0493689427

Bridging the spatio-temporal semantic gap: A theoretical framework, evaluation and a prototype system.
Khatri, Vijay.

Bridging the spatio-temporal semantic gap: A theoretical framework, evaluation and a prototype system. - 320 p.

Director: Sudha Ram.

Thesis (Ph.D.)--The University of Arizona, 2002.

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.

ISBN: 0493689427Subjects--Topical Terms:

1017515
Education, Business.

Bridging the spatio-temporal semantic gap: A theoretical framework, evaluation and a prototype system.
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520 $a 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.
520 $a 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.
520 $a 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.
520 $a 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.
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