Interoperability among the “Thing” on the IoT is the most fundamental requirements to support object address, tracking, and discovery as well as exchange, storage, and representation information. In order to these goals, the suite of technologies developed in the Semantic Web such as ontologies, semantic annotation, Linked Data and semantic web service is used as principal solution.
1. Sematic for interoperation:
IOT Interoperation is ability to access and interpret the unambiguous data from different stakeholder. Applying Semantic annotation of the data in data description is the way to make unambiguous data can be processed and interpreted by machines and software agents in order to archive automated information communication and interaction in IoT. Semantic data description can describes what the data represents, where it originates from, who is providing, what are the quality, technical attributes.
2. Sematic for data abstraction:
Data abstraction in IoT is the way that physical data from sensor devices is represented and managed. Recently, W3C’s SSN ontology have been developed, which provide a number of construct to describe sensor resources and the sensor observation and measurement data. Data is presented by different characterized on different abstraction levels. This is accomplished with semantic reasoning offered by semantic query languages.
3. Resource/service search and discovery:
Resource is referred to as a device or entity that can provide data or perform actuation such as sensor or actuator. A service is a software which can perform functionality of its corresponding resource.
Search and discovery mechanism allow locating resources and services in the physical devices. This is important function that requested in IoT. Define semantic annotation in the IoT resources and services allow search and discovery by different attributes and functionalities. In addition, the idea of linked sensor data can also be applied to support discovery and search using the linked data principle (semantic links) on web base.
4. Semantic reasoning and interpretation:
Semantic reasoning is to infer new information or knowledge from existing assertions and rules. This technique can be applied in many IoT operation such as resource discovery, data abstraction and knowledge extraction. IoT developer can use many exist algorithms implemented within available reasoners such as FACT++, Jena so they do not need to concern the complexities of reasoning process. SPARQL supports construct queries to explore the semantic description. SPARQL query structure is the same with SQL.