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10.1145/1999320.1999345acmotherconferencesArticle/Chapter ViewAbstractPublication Pagescom-geoConference Proceedingsconference-collections
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Formalizing fuzzy spatial data model for integrating heterogeneous spatial data

Published: 23 May 2011 Publication History

Abstract

The geospatial information is becoming a major input for various decision making processes. The heterogeneity in the spatial data sets, usually collectd and maintained by diverse organizations in their proprietary formats, posses a serious challenge for the integration process. Thus, the first step in this integration process is to develop a standardize geospatial data model from the individual data models. Then the model needs to be encoded in standard schema (GML) and the spatial web services need to be instantiated. Typically, an Enterprise-GIS (E-GIS) framework incorporates the OGC compliant geospatial web services for integration of heterogeneous spatial data sets. Further, the fuzziness exists in the properties of the geospatial objects and their relationships. Thus, there is a need to incorporate the fuzzy characteristics in the data model (application schema) of the E-GIS framework. The present work proposes a fuzzy geospatial data modeling technique for generation of fuzzy application schema. An approach for formalizing the fuzzy model using description logic has also been attempted. The formalization facilitate automated schema mapping required for the integration process. The efficacy of the proposed methodology has been demonstrated with help of an example.

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  • (2013)Formal Representation of Fuzzy Data Model Using Description LogicComputational Science and Its Applications – ICCSA 201310.1007/978-3-642-39649-6_8(108-119)Online publication date: 2013

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COM.Geo '11: Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications
May 2011
292 pages
ISBN:9781450306812
DOI:10.1145/1999320
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2011

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  1. enterprise GIS
  2. fuzzy data model
  3. spatial data model

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  • (2013)Formal Representation of Fuzzy Data Model Using Description LogicComputational Science and Its Applications – ICCSA 201310.1007/978-3-642-39649-6_8(108-119)Online publication date: 2013

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