Semantic Translation of Sensor Data

Sensor data presents the input of further simulations and plays a major role in early warning systems. Processing a high amount of data collected from different sensors requires interoperability at different levels. One of the remaining challenges is to overcome semantic heterogeneity during discovery, retrieval and integration of geodata within the open and distributed environments of current Spatial Data Infrastructures (SDIs). Therefore finding and accessing suitable information is the first step. The second step aims at data integration by transforming the data sources according to the requirements of the data sink In the future sensor networks of the data sink will be services for further information processing like simulation and interpolation The crucial task is not the execution of data transformation but rather to find translation rules in a generic way. This paper introduces an architecture for ontology-based translation of geographic information that solves semantic heterogeneity problems of data integration based on a (real-world) scenario from the area of flood management.