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Language-Based Access to Large Sensor Repositories

Sensor data have broadened their scope recently, ranging now from the simple time series measurements to, e.g., hyperspectral satellite image maps timeseries. In addition to observed data, simulation data increasingly have to be merged, for example 4-D ocean and atmospheric data. The majority of the...

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Detalles Bibliográficos
Autor principal: Baumann, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3348800/
https://www.ncbi.nlm.nih.gov/pubmed/22574054
http://dx.doi.org/10.3390/s90402926
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author Baumann, Peter
author_facet Baumann, Peter
author_sort Baumann, Peter
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description Sensor data have broadened their scope recently, ranging now from the simple time series measurements to, e.g., hyperspectral satellite image maps timeseries. In addition to observed data, simulation data increasingly have to be merged, for example 4-D ocean and atmospheric data. The majority of these data fall into the category of multi-dimensional rasters. However, when it comes to flexible retrieval, including sensor data search, aggregation, analysis, fusion, etc., standard query language support in the past has not kept up with the service level of, e.g., metadata retrieval. To close this gap, the Open GeoSpatial Consortium (OGC) has issued the Web Coverage Processing Service (WCPS) Standard in December 2008. WCPS defines a request language for multi-dimensional raster data, suitable for specifying navigation, download, and analysis of sensor, image, and statistics data. This contribution emphasises sensor data modeling and the perspectives for an integrated, cross-dimensional sensor data retrieval. Further, the WCPS reference implementation is briefly discussed.
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spelling pubmed-33488002012-05-09 Language-Based Access to Large Sensor Repositories Baumann, Peter Sensors (Basel) Article Sensor data have broadened their scope recently, ranging now from the simple time series measurements to, e.g., hyperspectral satellite image maps timeseries. In addition to observed data, simulation data increasingly have to be merged, for example 4-D ocean and atmospheric data. The majority of these data fall into the category of multi-dimensional rasters. However, when it comes to flexible retrieval, including sensor data search, aggregation, analysis, fusion, etc., standard query language support in the past has not kept up with the service level of, e.g., metadata retrieval. To close this gap, the Open GeoSpatial Consortium (OGC) has issued the Web Coverage Processing Service (WCPS) Standard in December 2008. WCPS defines a request language for multi-dimensional raster data, suitable for specifying navigation, download, and analysis of sensor, image, and statistics data. This contribution emphasises sensor data modeling and the perspectives for an integrated, cross-dimensional sensor data retrieval. Further, the WCPS reference implementation is briefly discussed. Molecular Diversity Preservation International (MDPI) 2009-04-22 /pmc/articles/PMC3348800/ /pubmed/22574054 http://dx.doi.org/10.3390/s90402926 Text en © 2009 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Baumann, Peter
Language-Based Access to Large Sensor Repositories
title Language-Based Access to Large Sensor Repositories
title_full Language-Based Access to Large Sensor Repositories
title_fullStr Language-Based Access to Large Sensor Repositories
title_full_unstemmed Language-Based Access to Large Sensor Repositories
title_short Language-Based Access to Large Sensor Repositories
title_sort language-based access to large sensor repositories
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3348800/
https://www.ncbi.nlm.nih.gov/pubmed/22574054
http://dx.doi.org/10.3390/s90402926
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