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| Criterion |  Knowledge Modeling NeOn Methodology |  Knowledge Modeling Shape-First Modeling |  Product Discovery Riskiest Assumption Test |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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. | 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. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | 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 | High | Medium | Medium | Medium |
Timedifferent | Mehrere Wochen bis Monate | Halber Tag pro Domain Slice | 1-2 Wochen pro Iteration | 1-5 Tage |
Participantsdifferent | 2-10 | 1-4 | 2-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Prioritized Assumption List, Test Plan, Results Report | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | OntologyMethodologyReuseSemanticEngineering | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryAssumptions | ValidationExperimentsDemandDiscovery |