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| Criterion |  Knowledge Modeling Linked Open Terms |  Knowledge Modeling Competency Questions |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | Linked Open Terms connects terminology work with linked-data thinking and makes terminology technically connectable. Vocabulary, meanings, and references can thereby be maintained consistently. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 | Medium | Low | Medium |
Timedifferent | Wochen bis Monate | 2-4 h | 30-60 min | 60-90 min |
Participantsdifferent | 2-8 | 2-8 | 1-5 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Ontology Requirements, Conceptual Model, Published Ontology, Documentation, Maintenance Plan | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | OntologyMethodologyAgileSemantic | OntologyKnowledge graphScopeRequirementsSemantic | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |