Using the Web of Data in Semantic Sensor Networks

In this paper we investigated new methods of effectively performing data modelling for making Internet of Things information accessible to humans and machines. In the current era of technology, we need efficient methods and solutions able to structure, annotate, share and make sense of the IoT data. We assumed that Things are basically active participants in information processes by exchanging data and information "sensed" about the environment. Semantics provide unambiguous machine-interpretable descriptions for data related to Things. In our methodology we proposed to encode sensor and observation data annotations through Semantic Web technologies and to embed them within devices. Moreover, we transformed such annotations to semantic descriptions, by using the cloud-based ThingSpeak middleware. The obtained descriptions are expected to compound a shared RDF Knowledge Base, useful to improve integration and communication processes between different networks.