# Automatic Mapping of AutomationML Files to Ontologies for Graph Queries and Validation

arXiv: https://arxiv.org/abs/2504.21694 · HTML: https://mlsanity.com/paper/2504.21694/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 49 references that are in the map.
- First posted on arXiv 30 Apr 2025.

## Builds on (most cited first, 1 of 1)

- [Interpreting OWL Complex Classes in AutomationML based on Bidirectional Translation](https://mlsanity.com/paper/1906.04240/) (2019)

## Built on by (most cited first, 1 of 1)

- [Automated Validation of Textual Constraints Against AutomationML via LLMs and SHACL](https://mlsanity.com/paper/2506.10678/) (2025)

## Abstract (arXiv)

AutomationML has seen widespread adoption as an open data exchange format in the automation domain. It is an open and vendor neutral standard based on the extensible markup language XML. However, AutomationML extends XML with additional semantics that limit the applicability of common XML-tools for applications like querying or data validation. This article demonstrates how the transformation of AutomationML into OWL enables new use cases in querying with SPARQL and validation with SHACL. To support this, it provides practitioners with (1) an up-to-date ontology of the concepts defined in the AutomationML standard and (2) a declarative mapping to automatically transform any AutomationML model into RDF triples. A study on examples from the automation domain concludes that transforming AutomationML to OWL opens up new powerful ways for querying and validation that would have been impossible without this transformation.