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| Criterion |  Knowledge Modeling Shape-First Modeling |  Innovation Lean Startup |  Knowledge Modeling Competency Questions |  Knowledge Modeling Linked Open Terms |
|---|---|---|---|---|
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. | 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. | Linked Open Terms connects terminology work with linked-data thinking and makes terminology technically connectable. Vocabulary, meanings, and references can thereby be maintained consistently. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Halber Tag pro Domain Slice | Wochen bis Monate je Lernzyklus | 2-4 h | Wochen bis Monate |
Participantsdifferent | 1-4 | 2-8 | 2-8 | 2-8 |
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 | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Ontology Requirements, Conceptual Model, Published Ontology, Documentation, Maintenance Plan |
Tagsno overlap | Knowledge graphValidationSemantic | LeanStartupValidationMVP | OntologyKnowledge graphScopeRequirementsSemantic | OntologyMethodologyAgileSemantic |