# Next generation biobanking ontology: introducing–omics contextual data to biobanking ontology

## TL;DR

This paper introduces a new ontology to standardize and structure contextual data in biobanks, improving data discovery and reuse.

## Contribution

The paper introduces the Next Generation Biobanking Ontology (NGBO) for representing omics contextual data in biobanks.

## Key findings

- NGBO captures information on wet bench, bioinformatics, and data management activities.
- The ontology enables semantic statements and querying of previously unstructured data.
- NGBO is open-source and freely accessible for reuse and integration.

## Abstract

With improvements in high throughput sequencing technologies and the constant generation of large biomedical datasets, biobanks increasingly take on the role of managing and delivering not just specimens but also specimen-derived data and associated contextual data. However, reusing data from different biobanks is challenged by incompatible data representations. Contextual data describing biobank resources often contains unstructured textual information incompatible with computational processes such as automated data discovery and integration. Therefore, a consistent and comprehensive contextual data framework is needed to increase discovery, reusability, and integrability across data sources.

The next generation biobanking ontology is an open-source application ontology representing omics contextual data, licensed under the Creative Commons 4.0 license. The ontology focuses on capturing information about three main activities: wet bench analysis used to generate omics data, bioinformatics analysis used to process and interpret data, and data management. In this paper, we demonstrated the use of the ontology to add semantic statements to real-life use cases and query data previously stored in unstructured textual format.

NGBO is freely available at https://github.com/Dalalghamdi/NGBO, and accessible from OLS https://www.ebi.ac.uk/ols4/ontologies/ngbo.