BioRels' data infrastructure: a scientific schema and exchange standard to transform and enhance biological data...

Area of Science:

• Bioinformatics
• Computational Biology
• Data Science

Background:

• The scientific community has generated numerous open-source resources for biological data management.
• Biological data is increasingly complex and heterogeneous, creating challenges in data integration and accessibility.
• Existing infrastructure like data lakes still require scientists to manually find, extract, clean, and prepare data, adhering to FAIR principles.

Purpose of the Study:

• To address the complexities of biological data management and preparation.
• To introduce BioRels, an automated and standardized workstream for biological data preparation.
• To improve the speed and reproducibility of scientific research involving large biological datasets.

Main Methods:

• Developed a representation of the mainstream biological data ecosystem, detailing natural relationships and concepts.
• Introduced BioRels, built on principles of data unicity and atomicity, for automated data preparation.
• Created BIORJ, an exchange format for exporting and importing data with dependencies and metadata.

Main Results:

• BioRels handles up to 145 billion data points, streamlining data preparation.
• Enables complex, seamless querying across multiple data sources.
• Provides a standardized exchange format (BIORJ) for data and metadata.

Conclusions:

• BioRels significantly enhances the efficiency and reproducibility of biological data preparation.
• The BioRels framework offers a scalable solution for managing complex biological data.
• Future work includes BioRels-KB to further expand data preparation capabilities.