Semantic Sensor Data Search in a Large-Scale Federated Sensor Network

Year: 
2011
Publication Date: 
Sunday, 23 October, 2011
Published in: 
International Workshop on Semantic Sensor Networks (SSN)
Authors: 
Jean-Paul Calbimonte, Hoyoung Jeung, Oscar Corcho, Karl Aberer

This paper was submitted at the International Workshop on Semantic Sensor Networks (SSN) in conjunction with ISWC 2011 (23-27 October 2011) and has been nominated best paper.

Abstract: 

Sensor network deployments are a primary source of massive amounts of data about the real world that surrounds us, measuring a wide range of physical properties in real time. However, in large-scale deployments it becomes hard to eectively exploit the data captured by the sensors, since there is no precise information about what devices are available and what properties they measure. Even when metadata is available, users need to know low-level details such as database schemas or names of properties that are specic to a device or platform. Therefore the task of coherently searching, correlating and combining sensor data becomes very challenging. We propose an ontology-based approach, that consists in exposing sensor observations in terms of ontologies enriched with semantic metadata, providing information such as: which sensor recorded what, where, when, and in which conditions. For this, we allow dening virtual semantic streams, whose ontological terms are related to the underlying sensor data schemas through declarative mappings, and can be queried in terms of a high level sensor network ontology.

AttachmentSize
PDF icon ssn2.pdf1.16 MB