Guided learning path
Ontology & Semantic Systems Engineering
Master formal semantic modeling, RDF/OWL triple stores, Domain-Driven Design integration, enterprise Data Mesh virtualization, and Neuro-Symbolic GraphRAG.
How origin ownership version and transformation metadata make knowledge auditable.
Entity-relation extraction, community detection (Leiden algorithm), hierarchical graph summarization, and query traversal.
Formal semantic modeling principles, Subject-Predicate-Object triples, RDF/OWL standards, and Open-World reasoning.
Mapping Domain-Driven Design (DDD) Bounded Contexts, Entity Classes, Invariants, and API Contracts using formal ontologies.
Milestone: Semantic Foundations & Software DDD
Master RDF/OWL SPO triples, Open-World assumption, and DDD Ubiquitous Language alignment.
Semantic data catalogs, unified schema governance, FAIR data principles, and Knowledge Graphs over relational data (R2RML, SPARQL).
Grounding LLMs with formal ontologies, ontology-driven prompt constraint schemas, Neuro-Symbolic AI, and deterministic reasoning boundaries.
Ontology versioning, mapping disparate domain schemas, automated SHACL constraint validation, and CI/CD ontology deployment.
Milestone: Data Mesh & Neuro-Symbolic GraphRAG
Deploy OBDA SPARQL data virtualization, Ontological GraphRAG grounding, and SHACL shapes governance.
Required labs
Required projects
Path outcomes
- Model domain knowledge formally using SPO triples and W3C RDF/OWL standards
- Unify enterprise Data Mesh and DDD Bounded Contexts with semantic ontologies
- Ground LLM retrieval and agent tools using Neuro-Symbolic GraphRAG and SHACL shapes