Scalability of an Ontology-Based Data Processing System
Jinyu Wei · 2018
In recent years, ontology-based data integration has gained increasing interest from rail industry stakeholders and the research community. However, despite the huge potential benefits, to date there has not been any specific discussion of the scalability and effectiveness of ontology-based architectures when used to process high-velocity data, such as that produced by condition monitoring systems. This paper will present early work towards these goals using a simulated ontology-based water-level monitoring system. Computer-generated data, representative of a sensor network, is used to produce alert information. Curves are generated for overall processing time from sensor networks at different scales, allowing conclusions about the expected performance of such systems in the field to be drawn.