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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Decision Matrix |  Decision Making Trade-off Analysis |  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 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. | With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects. | 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 | 45-90 min | 45-120 min | 2-4 h |
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 | Decision Matrix, Scoring Rationale, Selected Option | Trade-off Matrix, Criteria List, Decision Rationale, Accepted Downsides | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | DecisionCriteriaScoringTradeoffs | TradeoffsDecisionCriteriaOptions | OntologyKnowledge graphScopeRequirementsSemantic |