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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Argument Mapping |  Decision Making Cynefin Workshop |  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 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. | When problems are unclear, chaotic, or only seemingly familiar, standard recipes fall short. A Cynefin Workshop sorts situations by the nature of their problem and connects them with matching action logic. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-3 h | 60-180 min | 2-4 h |
Participantsdifferent | 1-4 | 1-8 | 4-20 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Argument Map, Evidence Gaps, Decision Rationale | Cynefin Map, Domain-specific Actions, Sensemaking Notes | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | SensemakingDecisionRationale | ComplexitySensemakingDecision | OntologyKnowledge graphScopeRequirementsSemantic |