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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Discovery Test Card |  Knowledge Modeling Competency Questions |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
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. | The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success. | 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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | Medium | Low | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | 20-35 min | 2-4 h | 60-90 min |
Participantsdifferent | 1-4 | 1-5 | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Test Card with a pre-set threshold | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryHypothesis | OntologyKnowledge graphScopeRequirementsSemantic | ExperimentsPrioritizationDiscoveryHypothesis |