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| Criterion |  Architecture C4 Model |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Ontology Design Patterns |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
Purposedifferent | The C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes. | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | Ontology Design Patterns provide reusable building blocks for recurring modeling problems. The method brings structure to the search for clean concepts, relationships, and roles. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. |
Complexitydifferent | Low | Medium | Medium | Medium |
Timedifferent | 1-4 h | Halber Tag pro Domain Slice | 1-3 h pro Pattern | 2-4 h |
Participantsdifferent | 1-5 | 1-4 | 1-6 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Context Diagram, Container Diagram, Component Diagram | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Selected Patterns, Adapted Schema Fragments, Pattern Documentation | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | ArchitectureCommunicationVisualization | Knowledge graphValidationSemantic | OntologyPatternsReuseSemanticModeling | OntologyKnowledge graphScopeRequirementsSemantic |