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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Argument Mapping |  Knowledge Modeling Competency Questions |  Delivery MoSCoW |
|---|---|---|---|---|
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 statements, evidence, and counterarguments get mixed up, a debate quickly loses its structure. Argument Mapping breaks a thesis down into its reasoning and makes visible what it really rests on. | 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. | 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. |
Complexitydifferent | Medium | Medium | Medium | Low |
Timedifferent | Halber Tag pro Domain Slice | 1-3 h | 2-4 h | 30-90 min |
Participantsdifferent | 1-4 | 1-8 | 2-8 | 3-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Argument Map, Evidence Gaps, Decision Rationale | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Prioritized Backlog, Release Scope, Tradeoff Notes |
Tagsno overlap | Knowledge graphValidationSemantic | SensemakingDecisionRationale | OntologyKnowledge graphScopeRequirementsSemantic | PrioritizationScopeDecision |