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Criterion
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of NeOn Methodology with its method-specific working model.
Knowledge Modeling
NeOn Methodology
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Purposedifferent
ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.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.When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.
Complexitydifferent
MediumMediumHighMedium
Timedifferent
2–4 h review as a planning range; preparation and evaluation additional1-5 TageMehrere Wochen bis Monate45-75 min
Participantsdifferent
Designers, developers as users, and facilitationNutzertraffic2-102-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsClick Data, Interest Signal, Learning DecisionOntology Requirements Specification, Reuse Plan, Ontology Modules, Evaluation ReportTest Matrix, Test Plan
Tagsno overlap
ArchitectureEngineeringFeedbackValidationTasks
ValidationExperimentsDemandDiscovery
OntologyMethodologyReuseSemanticEngineering
ExperimentsValidationDiscoveryOptions
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