Optimized Spatial Query for Data Integration Based on Semantics

Article Preview

Abstract:

Data integration of geospatial data in distributed, heterogeneous environment involves the use of semantic ontologies. In this kind of integration system, semantic technologies play an important role in improving performance and effectiveness of spatial queries. This paper focuses on methods of query optimization based on spatial semantics at the top level of semantic layer in central data integration systems. After analyzing the hybrid approach for spatial data integration, two categories of query optimization strategies are proposed based on detailed examination of special characteristics of spatial data. With spatial knowledge explicitly specified in ontologies and associated rules, spatial queries can be optimized intelligently.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1895-1899

Citation:

Online since:

November 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Peter L. Pulsifer, An Ontological Exploration of Antarctic Environmental Governance: Towards a Model for Geographic Information Mediation, Ph.D., Carleton University , 2008, 381 pages, NR43905. DAI-A 69/11, p. , May (2009).

DOI: 10.22215/etd/2008-06514

Google Scholar

[2] Isabel F. Cruz, Huiyong Xiao, The Role of Ontologies in Data Integration, Journal Of Engineering Intelligent Systems, vol. 13/2005, Apr. 2005, pp.245-252.

Google Scholar

[3] Gruber T R, A Translation Approach to Portable Ontology Specifications, Knowledge System Laboratory KSL 92-71. (1993).

Google Scholar

[4] Tian Zhao, Chuanrong Zhang, Mingzhen Wei and Zhong-Ren Peng, Ontology-based Geospatial Data Query and Integration, Geographic Information Science, vol. 5266, 2008, pp.370-392, doi: 10. 1007/978-3-540-87473-7_24.

DOI: 10.1007/978-3-540-87473-7_24

Google Scholar

[5] Vânia M.P. Vidal, Eveline R. Sacramento, José Antonio Fernandes de Macêdo and Marco Antonio Casanova, An Ontology-based Framework for Geographic Data Integration, Proc. ER 2009 Workshops CoMoL, Advances in Conceptual Modeling - Challenging Perspectives, vol. 5833/2009, 2009, pp.337-346.

DOI: 10.1007/978-3-642-04947-7_40

Google Scholar

[6] S. Zlatanova, M. de Vries and P.J.M. van Oosterom, Ontology-based Query of Two Dutch Topographic Datasets: an Emergency Response Case, Proc. Core Spatial Databases–Updating, maintenance and services from theory to practice. Haifa, Israel, ISPRS, vol. XXXVIII , Part 4-8-2-W9, p.193–198, Dec. (2010).

Google Scholar

[7] Fernando Bacao, Victor Lobo and Marco Painho, On the Particular Characteristics of Spatial Data and Its Similarities to Secondary Data Used in Data Mining, http: /www. isegi. unl. pt, (2005).

Google Scholar

[8] Ho-hyun Park, Yong-ju Lee and Chin-wan Chung, Spatial Query Optimization Utilizing Early Separated Filter and Refinement Strategy, Information Systems, vol. 25, Jan. 2000, pp.1-22, doi: 10. 1016/S0306-4379(00)00006-5.

DOI: 10.1016/s0306-4379(00)00006-5

Google Scholar

[9] Matthias Jarke and Jurgen Koch, Query Optimization in Database Systems, ACM Computing Surveys, vol. 16, Feb. 1984, pp.111-143, doi: 10. 1145/356924. 356928.

DOI: 10.1145/356924.356928

Google Scholar

[10] Hichul An and Lawrence J. Henschen, Knowledge based semantic query optimization, Methodologies for Intelligent Systems, Volume 542/1991, 1991, pp.82-91, doi: 10. 1007/3-540-54563-8_72.

DOI: 10.1007/3-540-54563-8_72

Google Scholar