Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data
AbstractThe worldwide Sensor Web comprises observation data from diverse sources. Each data provider may process and assess datasets differently before making them available online. This information is often invisible to end users. Therefore, publishing observation data with quality descriptions is vital as it helps users to assess the suitability of data for their applications. It is also important to capture contextual information concerning data quality such as provenance to trace back incorrect data to its origins. In the Open Geospatial Consortium (OGC)’s Sensor Web Enablement (SWE) framework, there is no sufficiently and practically applicable approach how these aspects can be systematically represented and made accessible. This paper presents Q-SOS—an extension of the OGC’s Sensor Observation Service (SOS) that supports retrieval of observation data together with quality descriptions. These descriptions are represented in an observation data model covering various aspects of data quality assessment. The service and the data model have been developed based on open standards and open source tools, and are productively being used to share observation data from the TERENO observatory infrastructure. We discuss the advantages of deploying the presented solutions from data provider and consumer viewpoints. Enhancements applied to the related open-source developments are also introduced. View Full-Text
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Devaraju, A.; Jirka, S.; Kunkel, R.; Sorg, J. Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data. ISPRS Int. J. Geo-Inf. 2015, 4, 1346-1365.
Devaraju A, Jirka S, Kunkel R, Sorg J. Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data. ISPRS International Journal of Geo-Information. 2015; 4(3):1346-1365.Chicago/Turabian Style
Devaraju, Anusuriya; Jirka, Simon; Kunkel, Ralf; Sorg, Juergen. 2015. "Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data." ISPRS Int. J. Geo-Inf. 4, no. 3: 1346-1365.