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Developments such as smart cities, the Internet of Things (IoT) and the Infrastructure for Spatial Information in Europe (INSPIRE) are causing a growing amount of observation data to be produced. The Open Geospatial Consortium (OGC) has developed Sensor Web Enablement (SWE) standards for modelling and publishing this data online. However, their use is currently limited to geo information specialists, who have knowledge about which data services are available and how to access them. With the use of the semantic web, online processes can automatically find and understand observation metadata. This opens up the SWE services to a large user audience. Therefore, this thesis has designed a conceptual system architecture that uses the semantic web to improve sensor data discovery as well as the integration and aggregation of sensor data from multiple sources. A conceptual system architecture is presented containing two web processes. The first process automatically creates an online semantic knowledge base of sensor metadata, by harvesting Sensor Observation Services. Metadata based on the Observations and Measurements (O&M) data model are retrieved, which includes the location of deployed sensors, what they observe, how they observe it and at which SWE service their data can be requested. The second process automatically translates logical queries of users into observation data requests. It also performs further processing before returning the observation data to the user. Both of these processes have been tested in a proof of concept implementation. A Web Processing Service (WPS) has been created as a proof of concept, making the two processes available online. The proof of concept is able to harvest sensor metadata, convert it to linked data, and publish it on the semantic web with links to and from other metadata. It results in a semantic knowledge base of sensor metadata, which improves the discovery in a machine understandable way. It allows multiple Sensor Observati, Architecture and The Built Environment, OTB, Geomatics

Developments such as smart cities, the Internet of Things (IoT) and the Infrastructure for Spatial Information in Europe (INSPIRE) are causing a growing amount of observation data to be produced. The Open Geospatial Consortium (OGC) has developed Sensor Web Enablement (SWE) standards for modelling and publishing this data online. However, their use is currently limited to geo information specialists, who have knowledge about which data services are available and how to access them. With the use of the semantic web, online processes can automatically find and understand observation metadata. This opens up the SWE services to a large user audience. Therefore, this thesis has designed a conceptual system architecture that uses the semantic web to improve sensor data discovery as well as the integration and aggregation of sensor data from multiple sources. A conceptual system architecture is presented containing two web processes. The first process automatically creates an online semantic knowledge base of sensor metadata, by harvesting Sensor Observation Services. Metadata based on the Observations and Measurements (O&M) data model are retrieved, which includes the location of deployed sensors, what they observe, how they observe it and at which SWE service their data can be requested. The second process automatically translates logical queries of users into observation data requests. It also performs further processing before returning the observation data to the user. Both of these processes have been tested in a proof of concept implementation. A Web Processing Service (WPS) has been created as a proof of concept, making the two processes available online. The proof of concept is able to harvest sensor metadata, convert it to linked data, and publish it on the semantic web with links to and from other metadata. It results in a semantic knowledge base of sensor metadata, which improves the discovery in a machine understandable way. It allows multiple Sensor Observati, Architecture and The Built Environment, OTB, Geomatics

The direct use of explorative point cloud data for calculations, observations and classifications., Geomatics, Architecture and The Built Environment, Geomatics