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| Criterion |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Property Graph Schema Design |  Knowledge Modeling Competency Questions |  Knowledge Modeling NeOn Methodology |
|---|---|---|---|---|
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. | 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. | 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. |
Complexitydifferent | Medium | Medium | Medium | High |
Timedifferent | Halber Tag pro Domain Slice | 4-8 h initial, dann iterativ | 2-4 h | Mehrere Wochen bis Monate |
Participantsdifferent | 1-4 | 1-6 | 2-8 | 2-10 |
Formatsame | Workshop + async | 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 | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report |
Tags1 shared | Knowledge graphValidationSemantic | Knowledge graphModelingSemantic | OntologyKnowledge graphScopeRequirementsSemantic | OntologyMethodologyReuseSemanticEngineering |