Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data
The 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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-08-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2220-9964/4/3/1346 |
| _version_ | 1819238274767519744 |
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| author | Anusuriya Devaraju Simon Jirka Ralf Kunkel Juergen Sorg |
| author_facet | Anusuriya Devaraju Simon Jirka Ralf Kunkel Juergen Sorg |
| author_sort | Anusuriya Devaraju |
| collection | DOAJ |
| description | The 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. |
| first_indexed | 2024-12-23T13:33:38Z |
| format | Article |
| id | doaj.art-24ab77407b9341b9a6aa4fb6d9bda1ee |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-23T13:33:38Z |
| publishDate | 2015-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-24ab77407b9341b9a6aa4fb6d9bda1ee2022-12-21T17:45:05ZengMDPI AGISPRS International Journal of Geo-Information2220-99642015-08-01431346136510.3390/ijgi4031346ijgi4031346Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental DataAnusuriya Devaraju0Simon Jirka1Ralf Kunkel2Juergen Sorg3Institute for Bio- and Geosciences, Agrosphere Institute, Forschungszentrum Jülich GmbH, 52425 Jülich, GermanyNorth GmbH, Martin-Luther-King-Weg 24, 48155 Münster, GermanyInstitute for Bio- and Geosciences, Agrosphere Institute, Forschungszentrum Jülich GmbH, 52425 Jülich, GermanyInstitute for Bio- and Geosciences, Agrosphere Institute, Forschungszentrum Jülich GmbH, 52425 Jülich, GermanyThe 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.http://www.mdpi.com/2220-9964/4/3/1346quality controldata quality assessmentprovenancesensor websensor observation serviceenvironmental observatoriesTERENO |
| spellingShingle | Anusuriya Devaraju Simon Jirka Ralf Kunkel Juergen Sorg Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data ISPRS International Journal of Geo-Information quality control data quality assessment provenance sensor web sensor observation service environmental observatories TERENO |
| title | Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data |
| title_full | Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data |
| title_fullStr | Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data |
| title_full_unstemmed | Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data |
| title_short | Q-SOS—A Sensor Observation Service for Accessing Quality Descriptions of Environmental Data |
| title_sort | q sos a sensor observation service for accessing quality descriptions of environmental data |
| topic | quality control data quality assessment provenance sensor web sensor observation service environmental observatories TERENO |
| url | http://www.mdpi.com/2220-9964/4/3/1346 |
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