Knowledge Graph Data Model
To support a consistent and structured digital representation of our car sharing enterprise, we designed a knowledge graph data model tailored to the needs of this use case. It defines the key elements, their attributes, and how they are related — forming the semantic foundation for our enterprise architecture and the AI Assistant’s understanding.
At the core of the model are key concepts from enterprise modeling — extended with the following domain-specific elements:
- Organizational Structure: (Company, Organizational Units, Departments, Teams)
- Goals: defined at company and department level, including target value and year
- Strategic Initiatives: aligned with long-term goals
- Transformation Projects: that modify or redesign processes
- KPIs: to measure goal achievement (including current and target values)
- Services: which are realized by one or more Processes
- Processes: structured sequences composed of Activities
- Activities: including attributes such as execution type, frequency, error rate, manual workarounds and CO₂ impact
- Systems and Data Flows: capturing IT dependencies and technical interfaces
Each relationship is clearly defined and enriched with cardinalities to support unambiguous interpretation and downstream reasoning.
This semantic data model enables AI-supported navigation, analytics, and visualization — and forms the backbone for our digital twin approach.
