Development of an ontology for modeling risks and temporal dependencies in global supply chains (BA/MA)
in
- Ausschreibung wissenschaftlicher Arbeiten
- Bachelorarbeit
- Masterarbeit
Global supply chains are increasingly complex, digitally networked and susceptible to disruptions caused by geopolitical crises, natural disasters, logistics bottlenecks or regulatory changes. Structured semantic modeling of such risks - taking into account temporal dependencies and process relationships - offers great potential for transparency, early warning and automated analysis.
Ontologies (OWL/RDF) enable the formal description and linking of entities, relationships and events. The aim of this thesis is to develop a supply chain risk ontology that is suitable for knowledge-based systems, AI applications or Neo4j data models.
In this thesis, a domain-specific ontology will be designed, implemented and evaluated with a focus on
- Identification and modeling of typical risk categories in the supply chain
- Linking risks with processes, actors, products and points in time
- Mapping of temporal dependencies and causalities
- Compatibility with existing standards such as SCOR, ISO 28000, IOF-SCRO
- Implementation in OWL or RDF(S)
Task definition
- Literature and standard analysis
- Evaluate existing ontologies, ISO standards, scientific models on supply chain risks - Concept development
- Definition of relevant classes, relations, vocabularies
- Risk model (sources, severity, probability of occurrence, etc.)
- Time model (events, processes, "before/after" relations) - Implementation of the ontology
- Creation with OWL / RDF / Protégé - Example data & test scenarios
- Model example instances (suppliers, risks, delays, etc.) - Evaluation & discussion
- Comparison with existing models
- Reflect on practical applicability / extensibility
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