Why Semantics Matter: a Demonstration on Knowledge-Based Control System Design

Knowledge representation and reasoning are hot topics in academics and industry today, as they are enabling technologies for building more complex and intelligent future systems. At the Mercator Telescope, we’ve built a software framework based on these technologies to support the design of our control systems. At the heart of the framework is a metamodel: a set of ontologies based on the formal semantics of the Web Ontology Language (OWL), to provide meaningful reusable building blocks. Those building blocks are instantiated in the models of our control systems, via a Domain Specific Language (DSL). The metamodels and models jointly form a knowledge base, i.e. an integrated model that can be viewed from different perspectives, or processed by an inference engine for model verification purposes. In this paper we present a tool called OntoManager, which demonstrates the added value of semantic modeling to the engineering process. By querying the integrated model, our web-based tool is able to generate systems engineering views, verification test reports, graphical software models, PLCopen compliant software code, Python client-side code, and much more, in a user-friendly way.