Using Ontology to Integrate Railway Condition Monitoring Data

This paper describes the requirement to integrate information and knowledge about a large domain such as a railway system. It describes how the problem of semantic heterogeneity between cooperating systems, i.e. condition monitoring systems, is overcome by applying ideas from the semantic Web. It illustrates by case study how remote condition monitoring system data, combined with multidiscipline context information in an ontology, enables complex queries to be determined to support decision making in the domain. This paper introduces the benefits of the approach over data base design, illustrated by describing key features such as class model retrieval in combination with instance retrieval and open world assumption (OWA)