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| Criterion |  Knowledge Modeling Shape-First Modeling |  Innovation Lean Startup |  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. | Ontology Design Patterns provide reusable building blocks for recurring modeling problems. The method brings structure to the search for clean concepts, relationships, and roles. |
Complexitysame | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | Wochen bis Monate je Lernzyklus | 1-3 h pro Pattern |
Participantsdifferent | 1-4 | 2-8 | 1-6 |
Formatsame | 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 | Selected Patterns, Adapted Schema Fragments, Pattern Documentation |
Tagsno overlap | Knowledge graphValidationSemantic | LeanStartupValidationMVP | OntologyPatternsReuseSemanticModeling |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
