An Ontology-based Knowledge Modelling Approach for River Water Quality Monitoring and Assessment

The increasingly deterioration of the water environment has attracted attention in water quality monitoring area, most researchers focus on the acquisition of water quality data but seldom the assessment and decision support for water quality. This paper proposed an approach for ontology modelling which could be used in evaluating the river water quality and its relevant processing knowledge. Ontology can describe the objective world better with its own syntax and provides the general understanding of the specialized knowledge in a domain. The ontology model built in this paper is specially designed for river water quality monitoring to represent the river water quality data with semantic properties and build the semantic relevance among the different concepts involved in river water quality monitoring domain. Combining the ontology model with a comprehensive water quality assessment method, the water quality assessment information could be achieved through the analysing and reasoning. On that basis, suggested treatments for solving the river water quality problems which could be easily understood are achieved with the ontology model and the inference rules built in the ontology reasoner. The accuracy and reliability of the system was verified by the analysis of five sets of sample water.