Assessing bioinformatics software annotations: bio.tools case-study
Résumé
Reproducibility and reuse of digital bioinformatics resources are essential for the development
of open and cumulative science, in line with FAIR principles. To search and reuse bioinformatics tools, scientists need to be confident enough with the reliability of their annotations. Our study focuses on the quantitative and qualitative evaluation of semantic annotations in the bio.tools registry, which serves more than 30,000 bioinformatics tool descriptions, annotated with the EDAM ontology. In this work we propose to study how the EDAM ontology is used to categorize software based on scientific disciplines and the kind of data processing they allow. We also evaluate how qualitative are the annotations based on Shannon entropy. We emphasize that a particular attention should be given to the whole set of inherited annotations, from the used ontology. Our results underline the need for automatic tools to support annotation curation, reducing the annotation cost for domain experts. This study is a preliminary work aimed designing novel annotation approaches based on the combination of knowledge graphs and large language models towards more findable and reusable bioinformatics tools.
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