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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Discovery Assumption Mapping |  Knowledge Modeling NeOn Methodology |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. | 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. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | Halber Tag pro Domain Slice | 45-60 min | Mehrere Wochen bis Monate | 2-4 h |
Participantsdifferent | 1-4 | 2-8 | 2-10 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Assumption map, Test backlog, Risk ranking | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | AssumptionsRiskExperimentsValidation | OntologyMethodologyReuseSemanticEngineering | OntologyKnowledge graphScopeRequirementsSemantic |