BioRels’ data infrastructure: a scientific schema and exchange standard to transform and enhance biological data sciences

Our understanding of biology and medicinal sciences augmented by advances in data structures and algorithms has resulted in proliferation of thousands of open-sourced resources, tools, and websites that are made by the scientific community to access, process, store, and visualize biological data. However, such data have become increasingly complex and heterogeneous, leading to an entangled web of relationships and external identifiers. Despite emergence of infrastructure such as data lakes, the scientists are still responsible for the time consuming and costly exercise to find, extract, clean, prepare, and maintain such data sources while following the FAIR principles. To better understand the complexity, we lay down a representation of the mainstream data ecosystem, describing the natural relationships and concepts found in biology. Built upon it and the fundamental principles of data unicity and atomicity, we introduce BioRels, an automated and standardized data preparation workstream aiming at improving reproducibility and speed for all scientists and handling up to 145 billion data points. BioRels allows complex querying capabilities across several data sources seamlessly and provides an exchange format, BIORJ, to export and import data with all its dependency and metadata. At last, we describe the advantages, limitations, applications, and perspectives of a future approach BioRels-KB to expand future data preparation capabilities.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-03-20
DOI
https://doi.org/10.1093/nar/gkaf254
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

BioRels’ data infrastructure: a scientific schema and exchange standard to transform and enhance biological data sciences

Bruno Cesar Fettermann Nogueira dos Santos, Lewis William Murray, Ji‐Bo Wang, Andrew M. Craven et al.
Nucleic Acids Research
Biomedical Text Mining and Ontologies
article

BioRels’ data infrastructure: a scientific schema and exchange standard to transform and enhance biological data sciences

Bruno Cesar Fettermann Nogueira dos Santos, Lewis William Murray, Ji‐Bo Wang, Andrew M. Craven, Jérémy Desaphy, Amanda Turney, Patty Bragger-Wilkinson, Jaroslav Martasek
article en

Abstract

Our understanding of biology and medicinal sciences augmented by advances in data structures and algorithms has resulted in proliferation of thousands of open-sourced resources, tools, and websites that are made by the scientific community to access, process, store, and visualize biological data. However, such data have become increasingly complex and heterogeneous, leading to an entangled web of relationships and external identifiers. Despite emergence of infrastructure such as data lakes, the scientists are still responsible for the time consuming and costly exercise to find, extract, clean, prepare, and maintain such data sources while following the FAIR principles. To better understand the complexity, we lay down a representation of the mainstream data ecosystem, describing the natural relationships and concepts found in biology. Built upon it and the fundamental principles of data unicity and atomicity, we introduce BioRels, an automated and standardized data preparation workstream aiming at improving reproducibility and speed for all scientists and handling up to 145 billion data points. BioRels allows complex querying capabilities across several data sources seamlessly and provides an exchange format, BIORJ, to export and import data with all its dependency and metadata. At last, we describe the advantages, limitations, applications, and perspectives of a future approach BioRels-KB to expand future data preparation capabilities.

Nucleic Acids ResearchVol. 53(6)
Eli Lilly (United States) (US)
Openalex Percentile: Top 94%
Biomedical Text Mining and Ontologies
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