An ontological representation for Tsunami early warning system
Wireless sensors are used for monitoring environments such as climate change, water quality and disaster management. Disaster management is a critical and emergent operation now, especially tsunami warning and prediction system. The Indian National Centre for Ocean Information Services (INCOIS) runs a tsunami early warning system for mitigation of oceanogenic disasters. The early warning system comprises of systems like seismic stations, Bottom Pressure Recorder (BPR) and tide gauges. The critical task of the warning system is interpretation of the complex multidimensional data generated by various sensors and interoperability among the systems and handling of heterogeneous data. The issues are in developing a methodology to integrate heterogeneous data received from various components of tsunami early warning system and providing web based data service. To address these requirements importance is given to both syntactic and semantic nature of the data. The syntactic part is responsible for the interoperability of the sensor data. Interoperability is addressed by using Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) framework. Ontologies are used as a means for solving the information heterogeneity problems because of their capability to provide explicit meaning to the information. In this paper we propose a Service Oriented Architecture (SOA) model for the interoperability of sensor networks data and semantics of the data. The purpose of the paper is to provide more meaningful information for Tsunami early warning system using ontology and Jena rule representation.