A practical approach to ontology-enabled control systems for astronomical instrumentation

TL;DR

This paper presents a practical method for integrating ontologies into control systems for astronomical instruments, enhancing flexibility, verification, and runtime semantics through OWL-based models and domain-specific languages.

Contribution

It introduces a novel approach using OWL ontologies as a meta-model for control systems, enabling formal verification and dynamic semantic access in astronomical instrumentation.

Findings

Ontologies can serve as effective meta-models for control systems.

Domain-specific languages facilitate system modeling and documentation.

Semantic layers enable runtime querying and monitoring.

Abstract

Even though modern service-oriented and data-oriented architectures promise to deliver loosely coupled control systems, they are inherently brittle as they commonly depend on a priori agreed interfaces and data models. At the same time, the Semantic Web and a whole set of accompanying standards and tools are emerging, advocating ontologies as the basis for knowledge exchange. In this paper we aim to identify a number of key ideas from the myriad of knowledge-based practices that can readily be implemented by control systems today. We demonstrate with a practical example (a three-channel imager for the Mercator Telescope) how ontologies developed in the Web Ontology Language (OWL) can serve as a meta-model for our instrument, covering as many engineering aspects of the project as needed. We show how a concrete system model can be built on top of this meta-model via a set of Domain Specific Languages (DSLs), supporting both formal verification and the generation of software and documentation artifacts. Finally we reason how the available semantics can be exposed at run-time by adding a "semantic layer" that can be browsed, queried, monitored etc. by any OPC UA-enabled client.