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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Red Teaming |  Knowledge Modeling Competency Questions |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
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. | For strategic decisions with high reach, agreement and gut feeling are often not enough. Red teaming brings deliberate opposition into the situation and tests where a plan breaks under real counterarguments. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Medium | High | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-4 h | 2-4 h | 45-60 min |
Participantsdifferent | 1-4 | 3-8 | 2-8 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Challenge Findings, Risk Register, Mitigation Plan | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Knowledge graphValidationSemantic | RiskDecisionSensemaking | OntologyKnowledge graphScopeRequirementsSemantic | AssumptionsRiskExperimentsValidation |