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| Criterion |  Knowledge Modeling Knowledge Mapping |  Knowledge Modeling Competency Questions |  Product Discovery Assumption Mapping |  Knowledge Modeling Shape-First Modeling |
|---|---|---|---|---|
Purposedifferent | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | 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. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 1-3 h | 2-4 h | 45-60 min | Halber Tag pro Domain Slice |
Participantsdifferent | 3-12 | 2-8 | 2-8 | 1-4 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Assumption map, Test backlog, Risk ranking | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation |
Tagsno overlap | KnowledgeMappingRisk | OntologyKnowledge graphScopeRequirementsSemantic | AssumptionsRiskExperimentsValidation | Knowledge graphValidationSemantic |