# BioSamples database: the global hub for sample metadata and multi-omics integration

## TL;DR

BioSamples is a central database for biological sample metadata, supporting data integration and reuse across multiple repositories.

## Contribution

The paper introduces technical updates and use cases showing how BioSamples enhances multi-omics data integration and user experience.

## Key findings

- BioSamples supports increased sample registration and improved user experience through recent technical updates.
- Four use cases demonstrate how communities use BioSamples to connect multi-omics data and build public data portals.
- The database is freely accessible and distributed under the Apache 2.0 license.

## Abstract

The BioSamples database (https://www.ebi.ac.uk/biosamples/) at the European Bioinformatics Institute (EMBL-EBI) is a core infrastructure resource that provides a centralized platform for the storage, curation, and dissemination of biological sample metadata. BioSamples holds sample descriptions across diverse datasets, enhancing their reusability and integrability in accordance with the FAIR (findable, accessible, interoperable, and reusable) principles. BioSamples serves as the central place to store the sample metadata for multiple repositories and archives at EMBL-EBI, including the European Nucleotide Archive, ArrayExpress, and the European Phenome-Genome Archive. In this article, we outline technical updates made to support increased sample registration and provide a better user experience. We describe four use cases whereby different communities have leveraged BioSamples to connect multi-omics data and enable the creation of public data portals and data status trackers. BioSamples is freely available, and its content is distributed under the EMBL-EBI Terms of Use available at https://www.ebi.ac.uk/about/terms-of-use. The BioSamples code is available at https://github.com/EBIBioSamples/biosamples-v4 and https://doi.org/10.5281/zenodo.17304021 and is distributed under the Apache 2.0 license.

Graphical Abstract