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| Criterion |  Knowledge Modeling Shape-First Modeling |  Delivery MoSCoW |  Growth A/B Testing |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
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. | When a release carries too many demands and priorities are only ever negotiated, MoSCoW creates clear boundaries for the next cut. Must, Should, Could, and Won't make commitment, room for maneuver, and trade-off logic visible to everyone involved. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | 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 | Medium | Low | High | Medium |
Timedifferent | Halber Tag pro Domain Slice | 30-90 min | 1-4 Wochen | 2-4 h |
Participantsdifferent | 1-4 | 3-12 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Prioritized Backlog, Release Scope, Tradeoff Notes | Experiment results, Decision log, Learning summary | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | PrioritizationScopeDecision | ExperimentsGrowthAnalyticsValidation | OntologyKnowledge graphScopeRequirementsSemantic |