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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Property Graph Schema Design |  Product Discovery Experiment Canvas |
|---|---|---|---|
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. | Property Graph Schema Design turns business and technical requirements into a robust graph schema. It fits when query patterns, constraints, and migrations need to be thought about together. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Medium | Medium | Low |
Timedifferent | Halber Tag pro Domain Slice | 4-8 h initial, dann iterativ | 30-60 min |
Participantsdifferent | 1-4 | 1-6 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Schema Diagram, Node and Relationship Catalog, Index Plan, Migration Scripts, Sample Queries | Completed Experiment Canvas, Success Metric |
Tagsno overlap | Knowledge graphValidationSemantic | Knowledge graphModelingSemantic | ExperimentsValidationDiscoveryHypothesis |
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