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| Criterion |  Product Discovery Hypothesis Prioritization Canvas |  Knowledge Modeling Linked Open Terms |  Product Discovery Learning Card |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | 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. | Linked Open Terms connects terminology work with linked-data thinking and makes terminology technically connectable. Vocabulary, meanings, and references can thereby be maintained consistently. | The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 60-90 min | Wochen bis Monate | 25-40 min | 1-5 Tage |
Participantsdifferent | 3-8 | 2-8 | 1-5 | Nutzertraffic |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Async |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | Ontology Requirements, Conceptual Model, Published Ontology, Documentation, Maintenance Plan | Learning Card with evidence and next action | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | OntologyMethodologyAgileSemantic | ExperimentsValidationDiscoveryLearning | ValidationExperimentsDemandDiscovery |