KG Quality Flashcards

(23 cards)

1
Q

What does ‘Garbage In, Garbage Out’ imply for KG quality?

A

A KG’s quality directly depends on input data; poor-quality inputs yield poor-quality graphs.

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2
Q

Why is KG quality multi-dimensional?

A

It involves multiple aspects (accuracy, completeness, consistency, etc.) and is use-case dependent.

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3
Q

How does KG quality differ from software quality?

A

KGs lack modularization, power unknown downstream systems, and follow unique development processes.

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4
Q

Define ‘Accuracy’ in a KG.

A

Closeness of recorded values to true values, measured via correctness (bool) or distance metrics.

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5
Q

How can Accuracy be aggregated across a KG?

A

As the proportion of accurate triples or as a weighted average accuracy.

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6
Q

Define ‘Completeness’ in a KG.

A

Degree to which required knowledge is present: schema, property, and population completeness.

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7
Q

What is ‘Population Completeness’?

A

Extent to which all entities in the scoped domain are present in the KG.

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8
Q

Define ‘Consistency’ in a KG.

A

Absence of conflicting statements; measured by number of inconsistencies detected.

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9
Q

What are ‘Reference Values’?

A

Ground-truth facts from experts used to measure accuracy and population completeness.

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10
Q

What are ‘Competency Questions’?

A

SPARQL queries with known results serving as unit tests for KG capabilities.

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11
Q

What role does SHACL play in KG quality?

A

Defines shape constraints (cardinality, datatype, class) for automated quality validation.

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12
Q

Define ‘Syntactic Validity’.

A

Conformance to RDF syntax: well-formed triples, correct prefixes, literals, and serialization grammar.

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13
Q

Define ‘Timeliness’ for a KG.

A

Degree to which KG data is up-to-date, measured via timestamps, update latency, and volatility.

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14
Q

What is ‘Freshness’ in KG quality?

A

Coverage and recency of timestamped data and the age-to-volatility ratio.

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15
Q

Define ‘Conciseness’.

A

Avoidance of redundant or duplicate schema elements and data instances in the KG.

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16
Q

Name a metric for Conciseness.

A

Ratio of unique instances to total instances; ratio of unique predicates in schema.

17
Q

Define ‘Understandability’.

A

Ease of human comprehension, supported by labels, comments, and readable IRI patterns.

18
Q

What metric measures Understandability?

A

Proportion of classes/properties with rdfs:label and rdfs:comment annotations.

19
Q

Why is Human Judgment valid in KG quality?

A

Quality is subjective and context-dependent; expert judgment is valid when acknowledged.

20
Q

Define ‘Availability’ in decentralized KGs.

A

Accessibility of KG data via endpoints, dumps, or dereferenceable URIs.

21
Q

Define ‘Latency’ in KG performance.

A

Delay between query request and the start of the response from the KG service.

22
Q

What is ‘Interlinking’ in Linked Data?

A

Degree of external links (e.g., owl:sameAs) per entity, indicating cross-KG connections.

23
Q

How can interlinking affect KG quality?

A

Improves completeness but may introduce conciseness and consistency challenges when merging.