2024/12/10 by Meznah Aloqalaa, Stian Soiland‐Reyes, Aloqalaa, Meznah +4 · 1 voice
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · #Biomedical Text Mining and Ontologies #Research Data Management Practices #Scientific Computing and Data Management
paper · pdf · doi:10.5334/dsj-2026-024
openalex publication_date 2026/01/01 · openalex created_date 2026/07/15 · openalex updated_date 2026/07/16
Reproducibility is a core expectation of computational pipelines in biomedical research, particularly in health-critical applications. To support the standardised reporting of high-throughput sequencing (HTS) analyses, the IEEE 2791-2020 standard, known as the BioCompute Object (BCO), was developed with support from the U.S. Food and Drug Administration. While the BCO serves as a pragmatic framework for documenting pipelines and is intended to improve transparency and reproducibility, its claims of reproducibility have not been systematically evaluated. This study employs the PRIMAD (Platform, Research objectives, Implementation, Methods, Actor, Data) model, a conceptual framework for describing computational experiments for reproducibility purposes, to systematically review the BCO in terms of depth and coverage. A systematic mapping of BCO and PRIMAD elements onto a published BCO use case, accompanied by a quantitative scoring rubric to evaluate the completeness of the mapping, highlights potential omissions and necessary enhancements in both frameworks. This emphasises the significance of systematically validating claims of reproducibility for published digital objects, thereby enhancing the reliability of scientific research in bioscience and related fields.