What question did this study set out to answer?

To establish a standardized, machine-readable methodology and open-source tooling for bioinformatics natural language questions and SPARQL queries across federated knowledge graphs.

October 8, 2024Open Access

A large collection of bioinformatics question-query pairs over federated knowledge graphs: methodology and applications

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To establish a standardized, machine-readable methodology and open-source tooling for bioinformatics natural language questions and SPARQL queries across federated knowledge graphs.
Curated human-written natural language questions and corresponding SPARQL queries over several years across research groups at the SIB Swiss Institute of Bioinformatics.
Established a standardized representation framework based on existing Semantic Web standards requiring minimal metadata.
Developed open-source web utilities including query graph visualizations and smart query editors for knowledge graph maintainers.
Generated a catalog of more than 1,000 standardized question-query pairs, containing 65 federated queries spanning distributed knowledge graphs.
Deployed reusable, open-source visualization and editing interfaces that integrate with standardized knowledge graph metadata.

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Implication

Methodological study demonstrates a standardized framework of bioinformatics question-query pairs across federated knowledge graphs, highlighting improved data accessibility and semantic search.

Cite This Study

Bolleman et al. (2024) studied this question.

synapsesocial.com/papers/6a8bfc7390fae8fd47e9a06f https://doi.org/10.48550/arxiv.2410.06010

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Implication

Methodological study demonstrates a standardized framework of bioinformatics question-query pairs across federated knowledge graphs, highlighting improved data accessibility and semantic search.

A large collection of bioinformatics question-query pairs over federated knowledge graphs: methodology and applications

Key Points

Discussion

Implication

Cite This Study

A large collection of bioinformatics question-query pairs over federated knowledge graphs: methodology and applications

Key Points

Discussion

Implication

Cite This Study

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