The SMOL language can be used as a framework for developing digital twins. For digital twins, the knowledge graphs can be used to capture asset models. SMOL programs can then seamlessly interact with asset models and domain knowledge to configure and adapt, e.g., simulators. SMOL uses Functional Mock-Up Objects (FMOs) as a programming layer to encapsulate simulators compliant with the FMI standard into OO structures and integrates FMOs into the class and type systems. By means of the semantic lifting, the FMOs can be integrated into knowledge graphs and used to ensure structural correctness properties for cyber-physical applications.
Imperative, object-oriented language
Seamless integration of programs and knowledge bases
Built-in reflection of program state in the knowledge base
Knowledge bases can be queried from SMOL programs
Encapsulation of simulators in objects based on the FMI standard
- Open source. SMOL is released under the terms of the 3-clause BSD licence,
the source is available at https://github.com/smolang/SemanticObjects.
Digital Twins and SMOL¶
Digital Twins and similar applications typically connect simulators with data-rich components and domain knowledge, both commonly formalised as knowledge graphs. Engineering such applications poses challenges to developers, which we address using a language-based approach to enable their efficient development, as well as explore analysis and design: SMOL is an imperative, object-oriented research language which integrates semantic web technologies and numerical simulation blocks, and can serve as a test bed for creating digital twins.
Semantic Web Technologies and SMOL¶
SMOL supports semantic lifting of program state: objects and their fields are represented as RDF triples and can be processed via standard semantic web technologies like SPARQL. An external ontology can be used to give additional semantics to the lifted program state. Section Semantic Access describes this in detail.
SMOL proposes a language-based integration of knowledge graphs and object-oriented programs. SMOL programs can contain queries to external knowledge graphs that contain, e.g., domain knowledge about an application domain. SMOL further proposes semantic reflection of programs into knowledge graphs by lifting the runtime state of the program into an associated knowledge graph, which enables programs to directly query this semantic representation of itself at runtime. This way, programs can make use of domain knowledge in the knowledge graph. Semantic reflection in SMOL can be used in interesting ways by giving the program access to formalised domain knowledge about its own runtime state, for example for debugging but also for system reconfiguration.
Co-Simulation and SMOL¶
Dynamic simulation model components (FMUs) that follow the FMI standard can be directly integrated into SMOL code. A SMOL program can drive the dynamic model inputs and controls the advancement of time for all FMUs, and can access the dynamic model outputs, making them available for semantic lifting. This is discussed further in Section Functional Mock-Up Objects.