Quiz: Testing, CI and Governance: ROBOT, ODK and Falsifiability

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Question 1 of 3

1. Question

What is the lesson’s central claim about what makes an ontology trustworthy?

Axiom count and committee years, because a larger ontology covers more of the domain and therefore constrains more of it
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Axiom placement beats axiom count: what matters is whether axioms sit where real data could collide with them, so an ontology that no data could ever contradict is refutation-inert and asserts almost nothing
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Conformance to an ISO-standardised upper ontology, which guarantees that domain extensions stay consistent
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Passing a reasoner consistency check, which on its own is sufficient evidence of assurance
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Question 2 of 3

2. Question

Which description of ROBOT’s role in an ontology CI pipeline is correct?

It is a SHACL engine that validates instance data against shapes graphs under closed-world semantics
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It is a containerised repository template that generates an editors file, managed imports, a Makefile-driven release pipeline and CI configuration
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It is the command-line workhorse that merges imports into release artifacts, runs a reasoner and fails loudly on unsatisfiable classes, extracts modules, diffs versions, runs report for standard defects and runs verify to execute SPARQL-based checks
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It is a triple store that materialises OWL 2 RL entailments over billions of triples in production
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Question 3 of 3

3. Question

How does the lesson propose to measure whether an ontology is actually falsifiable?

Generate deliberately corrupted data such as category errors, impossible cardinalities and cross-branch hybrids, then count what fraction of the corruptions any check actually catches
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Count the ratio of equivalence axioms to primitive subclass axioms in the released artifact
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Time how long a complete DL reasoner takes to classify the ontology and compare it against a profile reasoner
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Measure how many of the competency questions a frontier LLM can answer from the ontology text alone
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Quiz: Testing, CI and Governance: ROBOT, ODK and Falsifiability

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