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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Strategy Lean Canvas |  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 an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | 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 | 45-90 min | Mehrere Wochen bis Monate | 2-4 h |
Participantsdifferent | 1-4 | 1-6 | 2-10 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Lean Canvas, Core Assumptions, Experiment Backlog | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | StartupLeanAssumptionsBusiness model | OntologyMethodologyReuseSemanticEngineering | OntologyKnowledge graphScopeRequirementsSemantic |