Evaluation for insight

Evaluator: Automated Evaluation

Evaluated on: 2026-01-06

⚠️ Automated Evaluation: This evaluation was generated automatically using an AI-based system. It is distinct from manual evaluations curated by human experts. Please review findings carefully and report any inaccuracies.

Evaluation Criteria: This evaluation uses the KG-Registry evaluation rubric as described in Cortes et al. (2025) . The rubric assesses knowledge graphs across multiple dimensions including access, provenance, documentation, maintenance, and fitness for purpose.


Access Level and Types

QuestionAnswerComment
Access to data outside of the knowledge graphY
API or online access to the knowledge graphN
Multiple access options availableN
Source code availabilityN
Downloadable knowledge graphN

Section Score: 1/5

Provenance of Nodes and Edges

QuestionAnswerComment
Source list providedY
Source versions informationN
Import dependenciesN
Node and edge sourcesN
Edges deduplicationN
Triples source detailsN
Edge type schemaN

Section Score: 1/7

Documented standards, schema, construction

QuestionAnswerComment
Biological usable dataY
Resolvable IDsN
Construction documentationN
Transformation documentationN
Schema usedN

Section Score: 1/5

Update frequency and versioning

QuestionAnswerComment
Stable versionsN
Public tracker informationN
Knowledge graph contact informationY
Updated annuallyN
Prior versions accessN

Section Score: 1/5

Evaluation - Metrics and Fitness for Purpose

QuestionAnswerComment
Use case providedY
Evaluation against other modelsN
Defined scopeY
Multiple evaluation methodsN
Accuracy metricsN

Section Score: 2/5

License Information

QuestionAnswerComment
License