Projects
The guidelines for developing ontologies in the Internet of Production are now available as an interactive website. It includes full-text search with highlighted excerpts, a command palette, and an "Ask this guide" box for plain-English questions that point straight to the relevant passage. The running class/property example and the 42-ontology domain comparison from the Appendix are now explorable graphs instead of static diagrams. The Ontology Requirements, Competency Questions, and Class/Property/Individuals Definition templates are fillable directly on the page, autosave in your browser, and export to CSV, Markdown, or a ready-to-use OWL/Turtle file — and as you fill them in, your own classes and properties render as a live graph next to the book's example, with support for keeping multiple projects side by side. The site also includes a progress tracker for the 11-step workflow, dark mode, adjustable text size, and a citation/BibTeX section.
A practical, unified guideline for developing ontologies in the Internet of Production, letting Domain Experts and Knowledge Experts collaborate on semantic models without starting from scratch each time — built by studying and merging existing ontology-development methodologies.
Application profiles mapping domain-specific information models onto the IDS Information Model, aligning independently developed ontologies so data described under different schemas can be matched, related, and exchanged consistently across a Data Space.
A study evaluating how trustworthy the automatically-generated mappings between biomedical ontologies on BioPortal really are, using structural and terminological similarity metrics to flag matches that look correct by label but diverge semantically, benchmarked against a reference alignment.
Ongoing research into how Data Spaces achieve interoperability by grounding shared vocabularies in semantics rather than fixed schemas — using ontologies, controlled vocabularies, and mapping/matching techniques so participants from different domains (Mobility, Industry 4.0, Agriculture, Culture) can exchange and understand each other's data without agreeing on a single rigid format up front.