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| Abstraction | Data access method | Technology interoperability | Ontology | Service discovery | Metadata | Processing |
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| OGC SWE | Publish/Subscribe, queried streams and historical values, events, and alerts | A set of XML specifications and interfaces for sensor interoperability | Ontology not mentioned, but SensorML describes uniform data structure and units, and O&M describes observation structure | SensorML models and XML schema can be mined for SensorML processes (includes connected sensors and actuators); SPS can be used to test asset availability for a task | SensorML contains process metadata and O&M contain observation metadata | Through SensorML processes and process chains; SAS for creating notifications from pattern matching data |
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| Bouillet et al. [30] | Stream, but the accessing method is not described | Through the input semantics that data sources must adapt | OWL ontologies | Data sources and PE outputs that match to a PE input can be discovered | Not mentioned | PEs can be interconnected; an algorithm to combine PEs into an application |
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| GNS | Query with streams and historical data | Abstracted technologies are described as virtual sensors | No ontology, but the virtual sensor describes the data structure freely | Virtual sensor can be discovered with their metadata descriptions | Each virtual sensor holds metadata descriptions | SQL like processing on the virtual sensors; virtual sensors can be sources to other virtual sensors |
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| SenseWeb | Query with streams and historical data | Uniform API, with data and time abstraction | Not used, but the API homogenizes data format, but the method is not described | For sensors, according to sensor type or location, and for transformers | Not mentioned | Transformers can convert units, aggregate, fuse, and visualize data |
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| SensorMap | Query with streams and historical data; location-based queries possible | Through SenseWeb DataHub | A lack of standard ontology discussed | Services can be discovered from GeoDB meta-data | GeoDB holds meta-data | Aggregate geographically close sensors and display on a map |
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| Lamses | Events for context-awareness and queries for data retrieval | Describes a common interface for attaching WSNs into it | Not mentioned, but uses XML for homogenizing data | Not mentioned | An XML based meta-information database for complementary hardware information | Context-aware event and data processing; internally integrates data for context-aware events |
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| SeNsIM | Query for real-time data and events | Wrappers connect technologies to a mediator and data is unified in an XML | Not mentioned, but an XML model is used for the data unifying | Wrappers discover sensors from abstracted technologies | Not mentioned. | Not mentioned clearly |
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| Smart-M3 | Publish/Subscribe and query/insert data | KPs can communicate through a SIB in a smart space without temporal connections | Any ontology can be used and there is an Ontology API for each used ontology | KPs can find different services through a SIB, if the semantics of their data match | Not mentioned | Not supported/possible |
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