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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
Descripción
Sumario: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.