A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> Introduction <s> Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the semantic sensor Web (SSW) proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for situational knowledge. <s> BIB001 </s> A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> Introduction <s> Semantic sensor networks use declarative descriptions of sensors promote reuse and integration, and to help solve the difficulties of installing, querying and maintaining complex, heterogeneous sensor networks. This paper reviews the state of the art for the semantic specification of sensors, one of the fundamental technologies in the semantic sensor network vision. Twelve sensor ontologies are reviewed and analysed for the range and expressive power of their concepts. The reasoning and search technology developed in conjunction with these ontologies is also reviewed, as is technology for annotating OGC standards with links to ontologies. Sensor concepts that cannot be expressed accurately by current sensor ontologies are also discussed. <s> BIB002
In recent years, the sensor network is received more and more attention. It is increasingly deployed in all kinds of environments for different purposes. For example, In Environment-Monitor, urban traffic planning, flood prediction, health care, satellite sounding and other domains. It has been used in a wide range of applications. Therefore, mass sensor data can be produced continuously. However, the acquired sensor data lack of semantic information and may be heterogeneous in the syntax, schema and semantic level etc., and it's hard to be shared and integrated. If this issue can be solved, sensor network can has more application prospects BIB001 . In order to overcome the problem of lack of semantic in sensor network and manage a large number of heterogeneous data effectively, semantic web technology is introduced in the sensor network, which can describe information object, information sharing, information integration and knowledge reasoning. The added semantic can help to create the machine readable and self-describing data in the sensor network BIB001 .The study of the sensor network must consider how to use semantic technology effectively. Therefore, the combination of semantic web and sensor network becomes a hot research direction. Through the ontology technology, Semantic Sensor Web (SSW) can construct the shared conceptual model, enhance the sensor data semantics, and realize interaction and access of sensor data on the web. Semantic Sensor Web has the following characteristics: (1) Sensor data is annotated with semantic to improve the interoperability of data BIB002 . (2) The context information such as time, space, theme for the sensor data is added. (3) SSW combines multi-type sensor data to support intelligent decision synthetically. (4) SSW can resolve the heterogeneous of sensor data to express the data uniformly. The bottom layer is the data source layer of the sensor network. There are a large number of sensor data in the sensor network, and the sensor data are stream data which are the infinite timestamp tuple sequence. The timestamp character of the sensor stream data which indicates when the tuple occur is unique. Therefore, the following research content in this review must consider this issue. Sensor data has two representational forms: One is the data which is stored in the relational stream database, and another is the stream data which are collected in real time. The different data of representational forms is processed by different method when these data are integrated.