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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Delphi Method |  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. | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 | High | High | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-4 Wochen | Mehrere Wochen bis Monate | 1-3 h pro Pattern |
Participantsdifferent | 1-4 | 6-30 Experten | 2-10 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Expert Forecast, Consensus Range, Assumption Notes | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report | Selected Patterns, Adapted Schema Fragments, Pattern Documentation |
Tagsno overlap | Knowledge graphValidationSemantic | ForecastingExpertsDecisionStrategy | OntologyMethodologyReuseSemanticEngineering | OntologyPatternsReuseSemanticModeling |