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| Criterion |  Knowledge Modeling Shape-First Modeling |  Innovation Lean Startup |  Knowledge Modeling NeOn Methodology |  Knowledge Modeling Ontology Design Patterns |
|---|---|---|---|---|
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. | For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight. | 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. | Ontology Design Patterns provide reusable building blocks for recurring modeling problems. The method brings structure to the search for clean concepts, relationships, and roles. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | Halber Tag pro Domain Slice | Wochen bis Monate je Lernzyklus | Mehrere Wochen bis Monate | 1-3 h pro Pattern |
Participantsdifferent | 1-4 | 2-8 | 2-10 | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | Selected Patterns, Adapted Schema Fragments, Pattern Documentation |
Tagsno overlap | Knowledge graphValidationSemantic | LeanStartupValidationMVP | OntologyMethodologyReuseSemanticEngineering | OntologyPatternsReuseSemanticModeling |