Semantic Representation of Raster Spatial Data

When people think spatially, they do not usually consider geographic coordinates nor projections. Facing questions having a spatial sense, people do not answer with maps or coordinates, but use some references whose spatial location is "well known". For instance, the answer of a convention...

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Detalhes bibliográficos
Autor: Rolando Quintero Téllez
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2011
País:México
Recursos:Instituto Politécnico Nacional
Repositorio:Redalyc-IPN
OAI Identifier:oai:redalyc.org:61520765010
Acesso em linha:https://www.redalyc.org/articulo.oa?id=61520765010
Access Level:acceso abierto
Palavra-chave:Computación
Semantic
ontology
knowledge
representation
raster spatial data
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spelling Semantic Representation of Raster Spatial DataRolando Quintero TéllezComputaciónSemanticontologyknowledgerepresentationraster spatial dataWhen people think spatially, they do not usually consider geographic coordinates nor projections. Facing questions having a spatial sense, people do not answer with maps or coordinates, but use some references whose spatial location is "well known". For instance, the answer of a conventional geographic information system to the question "Where is the CIC?" would be "in coordinates 19.50314°N, 99.14759°W". In contrast, a person would answer "in Zacatenco" or "near to Eje Central". The semantic processing attempts to enrich an abstraction level similar to the one that people use commonly. This processing, applied to spatial data, does not depend on scales, resolutions, projections or others that are fundamental in conventional systems. We assume that the first step for making semantic processing is the semantic description of "raw" spatial data. Such description is the identification of the objects contained in data and the location of such objects within a conceptual framework, where they get a meaning. In this work, we present a methodology for making this semantic description using as a case study the digital elevation models. The methodology is build up of three stages: conceptualization, to define the conceptual framework of the description; synthesis, to process "raw" spatial data and to obtain the spatial objects contained in data; and description, to generate the representation of results from the synthesis according to the conceptual framework.Instituto Politécnico Nacional2011info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdf1405-5546https://www.redalyc.org/articulo.oa?id=61520765010Computación y Sistemas (México) Num.3 Vol.14reponame:Redalyc-IPNinstname:Instituto Politécnico Nacionalinstacron:IPNenhttp://www.redalyc.org/revista.oa?id=615Computación y Sistemasinfo:eu-repo/semantics/openAccessoai:redalyc.org:615207650102026-01-29T02:55:26Z
dc.title.none.fl_str_mv Semantic Representation of Raster Spatial Data
title Semantic Representation of Raster Spatial Data
spellingShingle Semantic Representation of Raster Spatial Data
Rolando Quintero Téllez
Computación
Semantic
ontology
knowledge
representation
raster spatial data
title_short Semantic Representation of Raster Spatial Data
title_full Semantic Representation of Raster Spatial Data
title_fullStr Semantic Representation of Raster Spatial Data
title_full_unstemmed Semantic Representation of Raster Spatial Data
title_sort Semantic Representation of Raster Spatial Data
dc.creator.none.fl_str_mv Rolando Quintero Téllez
author Rolando Quintero Téllez
author_facet Rolando Quintero Téllez
author_role author
dc.subject.none.fl_str_mv Computación
Semantic
ontology
knowledge
representation
raster spatial data
topic Computación
Semantic
ontology
knowledge
representation
raster spatial data
description When people think spatially, they do not usually consider geographic coordinates nor projections. Facing questions having a spatial sense, people do not answer with maps or coordinates, but use some references whose spatial location is "well known". For instance, the answer of a conventional geographic information system to the question "Where is the CIC?" would be "in coordinates 19.50314°N, 99.14759°W". In contrast, a person would answer "in Zacatenco" or "near to Eje Central". The semantic processing attempts to enrich an abstraction level similar to the one that people use commonly. This processing, applied to spatial data, does not depend on scales, resolutions, projections or others that are fundamental in conventional systems. We assume that the first step for making semantic processing is the semantic description of "raw" spatial data. Such description is the identification of the objects contained in data and the location of such objects within a conceptual framework, where they get a meaning. In this work, we present a methodology for making this semantic description using as a case study the digital elevation models. The methodology is build up of three stages: conceptualization, to define the conceptual framework of the description; synthesis, to process "raw" spatial data and to obtain the spatial objects contained in data; and description, to generate the representation of results from the synthesis according to the conceptual framework.
publishDate 2011
dc.date.none.fl_str_mv 2011
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 1405-5546
https://www.redalyc.org/articulo.oa?id=61520765010
identifier_str_mv 1405-5546
url https://www.redalyc.org/articulo.oa?id=61520765010
dc.language.none.fl_str_mv en
language_invalid_str_mv en
dc.relation.none.fl_str_mv http://www.redalyc.org/revista.oa?id=615
dc.rights.none.fl_str_mv Computación y Sistemas
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Computación y Sistemas
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Politécnico Nacional
publisher.none.fl_str_mv Instituto Politécnico Nacional
dc.source.none.fl_str_mv Computación y Sistemas (México) Num.3 Vol.14
reponame:Redalyc-IPN
instname:Instituto Politécnico Nacional
instacron:IPN
instname_str Instituto Politécnico Nacional
instacron_str IPN
institution IPN
reponame_str Redalyc-IPN
collection Redalyc-IPN
repository.name.fl_str_mv
repository.mail.fl_str_mv
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