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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Competency Questions |  Operations Change Analysis |  Knowledge Modeling Property Graph Schema Design |
|---|---|---|---|---|
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. | Property Graph Schema Design turns business and technical requirements into a robust graph schema. It fits when query patterns, constraints, and migrations need to be thought about together. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 2-4 h | 45-120 min | 4-8 h initial, dann iterativ |
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 | Schema Diagram, Node and Relationship Catalog, Index Plan, Migration Scripts, Sample Queries |
Tagsno overlap | Knowledge graphValidationSemantic | OntologyKnowledge graphScopeRequirementsSemantic | ChangeRoot causeTroubleshootingComparison | Knowledge graphModelingSemantic |