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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling NeOn Methodology |  Decision Making Argument Mapping |  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. | 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 statements, evidence, and counterarguments get mixed up, a debate quickly loses its structure. Argument Mapping breaks a thesis down into its reasoning and makes visible what it really rests on. | 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 | High | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | Mehrere Wochen bis Monate | 1-3 h | 2-4 h |
Participantsdifferent | 1-4 | 2-10 | 1-8 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | Argument Map, Evidence Gaps, Decision Rationale | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | OntologyMethodologyReuseSemanticEngineering | SensemakingDecisionRationale | OntologyKnowledge graphScopeRequirementsSemantic |