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An ontology framework for quality of geographical information services

Authors:

Richard Onchaga,

Ing Widya,

Javier Morales,

J. M. LambertAuthors Info & Claims

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

Article No.: 64, Pages 1 - 4

https://doi.org/10.1145/1463434.1463509

Published: 05 November 2008 Publication History

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Abstract

In recent years, there has been much research on ontologies for geographic information (GI) services. But to date, focus has been on semantics of data and operations. Much less attention has been given to semantics of quality of GI services. In addressing this gap, this paper proposes an ontology framework for quality of GI services. The framework has an upper ontology, two primary domain ontologies and potentially many application ontologies. The ontologies provide concepts for unambiguously defining and reasoning about quality of GI services. We see the main strength of the framework as being its holistic view of quality; it integrates data quality and quality of service (QoS) which hitherto have been defined separately. Besides, the framework builds on established data quality and QoS concepts which guarantees its relevance and acceptance.

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A.H. Selmy SE. Kucher DYang YJesús García-Navarro F(2024)Geospatial Data: Acquisition, Applications, and ChallengesExploring Remote Sensing - Methods and Applications10.5772/intechopen.1006635Online publication date: 14-Oct-2024
https://doi.org/10.5772/intechopen.1006635
Liu JDu QLiu Y(2012)A Trustworthy Approach to the Adaptive Composition of GeoServicesProcedia Engineering10.1016/j.proeng.2012.01.58629(3868-3875)Online publication date: 2012
https://doi.org/10.1016/j.proeng.2012.01.586
Stankute SAsche H(2012)A data fusion system for spatial data mining, analysis and improvementProceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II10.1007/978-3-642-31075-1_33(439-449)Online publication date: 18-Jun-2012
https://dl.acm.org/doi/10.1007/978-3-642-31075-1_33
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Published In

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

November 2008

559 pages

ISBN:9781605583235

DOI:10.1145/1463434

Program Chairs:
Walid G. Aref
Purdue University
,
Mohamed F. Mokbel
University of Minnesota
,
Markus Schneider
University of Florida

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Association for Computing Machinery

New York, NY, United States

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Published: 05 November 2008

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GIS '08: 16th International Symposium on Advances in Geographic Information Systems

November 5 - 7, 2008

California, Irvine

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Overall Acceptance Rate 257 of 1,238 submissions, 21%

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A.H. Selmy SE. Kucher DYang YJesús García-Navarro F(2024)Geospatial Data: Acquisition, Applications, and ChallengesExploring Remote Sensing - Methods and Applications10.5772/intechopen.1006635Online publication date: 14-Oct-2024
https://doi.org/10.5772/intechopen.1006635
Liu JDu QLiu Y(2012)A Trustworthy Approach to the Adaptive Composition of GeoServicesProcedia Engineering10.1016/j.proeng.2012.01.58629(3868-3875)Online publication date: 2012
https://doi.org/10.1016/j.proeng.2012.01.586
Stankute SAsche H(2012)A data fusion system for spatial data mining, analysis and improvementProceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II10.1007/978-3-642-31075-1_33(439-449)Online publication date: 18-Jun-2012
https://dl.acm.org/doi/10.1007/978-3-642-31075-1_33
Moses R(2011)Enabling Quality of Geospatial Web ServicesGeospatial Web Services10.4018/978-1-60960-192-8.ch003(36-63)Online publication date: 2011
https://doi.org/10.4018/978-1-60960-192-8.ch003
Stankutė SAsche H(2011)Improvement of Spatial Data Quality Using the Data ConflationComputational Science and Its Applications - ICCSA 201110.1007/978-3-642-21928-3_35(492-500)Online publication date: 2011
https://doi.org/10.1007/978-3-642-21928-3_35
Zhu QYang XLi H(2009)Optimal Composition Algorithm Concerned with Response Time for Remotely Sensed Image Processing ServicesGeospatial Technology for Earth Observation10.1007/978-1-4419-0050-0_14(381-396)Online publication date: 29-Aug-2009
https://doi.org/10.1007/978-1-4419-0050-0_14

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Visualizing and quantifying the movement of vegetative drought using remote-sensing data and GIS

Visualizing and quantifying the movement of vegetative drought using remote-sensing data and GIS

Ontology-Based Framework for Geospatial Web Services

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