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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Strategy ICE Scoring |  Knowledge Modeling Competency Questions |  Decision Making Decision Matrix |
|---|---|---|---|---|
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 ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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 several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic. |
Complexitydifferent | Medium | Low | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 30-60 min | 2-4 h | 45-90 min |
Participantsdifferent | 1-4 | 2-8 | 2-8 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | ICE Table, Top Idea List | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Decision Matrix, Scoring Rationale, Selected Option |
Tagsno overlap | Knowledge graphValidationSemantic | PrioritizationScoringGrowthDecision | OntologyKnowledge graphScopeRequirementsSemantic | DecisionCriteriaScoringTradeoffs |