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| Criterion |  Knowledge Modeling NeOn Methodology |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Fake Door Test |  Knowledge Modeling Linked Open Terms |
|---|---|---|---|---|
Purposedifferent | The NeOn Methodology structures ontology work as a controlled process with reuse, scenarios, and reviews. It is useful when ontologies should not emerge ad hoc but modularly and reusably. | 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. | 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. | Linked Open Terms connects terminology work with linked-data thinking and makes terminology technically connectable. Vocabulary, meanings, and references can thereby be maintained consistently. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | Mehrere Wochen bis Monate | 60-90 min | 1-5 Tage | Wochen bis Monate |
Participantsdifferent | 2-10 | 3-8 | Nutzertraffic | 2-8 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop + async |
Outputdifferent | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | Prioritization Canvas, Hypothesis Backlog | Click Data, Interest Signal, Learning Decision | Ontology Requirements, Conceptual Model, Published Ontology, Documentation, Maintenance Plan |
Tagsno overlap | OntologyMethodologyReuseSemanticEngineering | ExperimentsPrioritizationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery | OntologyMethodologyAgileSemantic |