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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Linked Open Terms |  Product Strategy DIBB |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
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. | Linked Open Terms connects terminology work with linked-data thinking and makes terminology technically connectable. Vocabulary, meanings, and references can thereby be maintained consistently. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | Halber Tag pro Domain Slice | Wochen bis Monate | 1-2 h | 45-60 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 | Ontology Requirements, Conceptual Model, Published Ontology, Documentation, Maintenance Plan | DIBB document, Belief list, Bet list, Learning report | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | Knowledge graphValidationSemantic | OntologyMethodologyAgileSemantic | StrategyDecisionAssumptionsHypothesis | AssumptionsRiskExperimentsValidation |