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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Competency Questions |  Operations Change Analysis |  Knowledge Modeling Ontology Design Patterns |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | Ontology Design Patterns provide reusable building blocks for recurring modeling problems. The method brings structure to the search for clean concepts, relationships, and roles. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 2-4 h | 45-120 min | 1-3 h pro Pattern |
Participantsdifferent | 1-4 | 2-8 | 2-6 | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Selected Patterns, Adapted Schema Fragments, Pattern Documentation |
Tagsno overlap | Knowledge graphValidationSemantic | OntologyKnowledge graphScopeRequirementsSemantic | ChangeRoot causeTroubleshootingComparison | OntologyPatternsReuseSemanticModeling |