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What can AutomationML learn from other modeling communities?

AutomationML between metamodel and ontology: DSLs, constraints and validation

Interoperability is not only about exchanging engineering data. It also depends on making the rules, constraints and semantics behind models explicit and machine-readable. Two contributions at the AutomationML Conference 2026 show how ideas and technologies from the MBSE and Semantic Web communities can be leveraged within AutomationML.

AutomationML as an Exchange Format for Tool-Independent Domain-Specific Modeling Language Specifications

Tirth Joshi, Simon Eschlberger, Katharina Polanec and David Hoffmann

Drawing on ideas from MBSE and domain-specific modeling, the contribution investigates how AutomationML can exchange DSL specifications across modeling tools, including concepts, constraints, validation rules and modeling configurations.

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Formal Description for AutomationML – Mapping AutomationML to Ontologies

Sandra Eisenmann and Miriam Schleipen

From the Semantic Web and ontology perspective, the FD4AML approach maps AutomationML to ontologies and uses SHACL to support machine-readable semantics and automated compliance checks.

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Different communities and technologies, but a closely related question: how can we make engineering models easier to understand, constrain and validate across tools?

For AutomationML, this also means looking beyond our own community and building on established ideas from MBSE, metamodeling, ontologies and the Semantic Web.

AutomationML Conference 2026
22–23 September, Hochschule Pforzheim

All accepted contributions for the AutomationML Conference 2026 are published individually on the Conference Highlights page.