A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> (2) Extending by Adding New Contents to SSN Ontology to Found More General Ontology <s> Wireless Sensor Networks (WSN) are designed to collect large amounts of heterogeneous data to monitor environmental phenomenon. Our aim is to adapt WSN nodes communication to their context, in order to optimize the lifetime of the network. Our description of context and WSN characteristics are based on ontologies. Based upon a critical analysis of existing ontologies which formalize the WSN domain, we determine that the Semantic Sensor Network (SSN) ontology is the most suitable to represent the WSN issues. However, as the communication data policy is not characterized either by SSN or by other ontologies, we propose to enrich the SSN ontology with a new pattern describing communication. In this paper, we will first integrate the different concepts related to WSN in the SSN ontology and then we will use the resulting ontology, called Wireless Semantic Sensor Network ontology, in an agri-environmental scenario to illustrate the interest of our approach. <s> BIB001 </s> A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> (2) Extending by Adding New Contents to SSN Ontology to Found More General Ontology <s> To address the shortcomings of existing sensor ontologies, such as lack of a unified ontology framework and being built completely manually, this work proposes the sensor ontology framework and algorithms for automatic sensor ontology update and extension. In addition, sensor discovery based on time, space and theme is implemented. Sensor core ontology and its update and extension are evaluated. The experimental result reveals that the proposed sensor ontology framework is feasible, and the algorithms for sensor ontology update and extension are effective. <s> BIB002 </s> A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> (2) Extending by Adding New Contents to SSN Ontology to Found More General Ontology <s> The recent years have seen a vast increase in the amount of environmental sensor data that is being published on the web. Semantic enrichment of sensor data addresses the problems of (re-)use, integration, and discovery. A critical issue is how to generate semantic sensor data from existing data sources. In this paper, we present our approach to semantically augment an existing sensor data infrastructure, in which data is published via a RESTful API as inter-linked json documents. In particular, we describe and discuss the use of ontologies and the design and development of seraw, a system that transforms a set of json documents into an rdf graph augmented with links to other resources in the Linked Open Data cloud. This transformation is based on user-provided mappings and supported by a library of purpose-built functions. We discuss lessons learned during development and outline remaining open problems. <s> BIB003
The more general ontologies are extended on the basis of SSN ontology in order to have more extensively applicable scope. WSSN ontology BIB001 SCO ontology BIB002 is also built by reusing and extending SSN ontology. The Sensor module in SCO ontology is the core module which is a bridge connecting to other modules. Sensor module directly reuses the Sensor module of SSN ontology, but the Stimulus class is replaced by SensorInput class. The OpeatingRestriction module is changed to the SystematicCharacter module and EnvironmentCondition class is added in the module. In addition, on the basis of SSN ontology modules, new modules such as the Component module, the Service module and the Context module, etc are added. In the Context module, three important classes are added: Space, Time and Theme. These three classes respectively show that Space, Time, and Theme of observations values by which the sensor data information can be described in more detail. SCO ontology is a major progress of SSN ontology extensions. In order to conduct semantic description of the sensor data on the sensor cloud, SCO (Sensor Cloud Ontology) Ontology appears BIB003 . SCO Ontology reuses and extends SSN ontology and many classes and properties don't have to be redefined. Through the derived subclass, the platform and network and other characteristics of sensor network on the Cloud can be defined. In SCO ontology, the Network class and Platform class derived from the System class of SSN ontology, the Sensor class derived from the SensingDevice class, while the ObservedPhenomenon class derived from the Observation class, the Observation Result class derived from the SensorOutput. Using SCO ontology, the transformation from sensor data to semantic very facilitate, so that we have convenient queries on the SERAW development platform.