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| Criterion |  Product Strategy DIBB |  Knowledge Modeling Linked Open Terms |  Decision Making Force Field Analysis |  Knowledge Modeling NeOn Methodology |
|---|---|---|---|---|
Purposedifferent | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | Linked Open Terms connects terminology work with linked-data thinking and makes terminology technically connectable. Vocabulary, meanings, and references can thereby be maintained consistently. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | 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 | Low | Medium | Low | High |
Timedifferent | 1-2 h | Wochen bis Monate | 45-90 min | Mehrere Wochen bis Monate |
Participantsdifferent | 2-8 | 2-8 | 3-12 | 2-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Ontology Requirements, Conceptual Model, Published Ontology, Documentation, Maintenance Plan | Force Field Map, Change Levers, Risk Notes | Ontology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation Report |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | OntologyMethodologyAgileSemantic | ChangeDecisionStrategy | OntologyMethodologyReuseSemanticEngineering |