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Publications

Journal Article Epublish

PubMed: 40799495 DOI: 10.1093/bioadv/vbaf131

Next generation biobanking ontology: introducing-omics contextual data to biobanking ontology.

Bioinform Adv 5(1):vbaf131

Authors: Dalia Alghamdi, Damion M Dooley, Mannar Samman, Ali AlFaiz, William W L Hsiao

Affiliations

  • Bioinformatics Graduate Program, University of British Columbia, Genome Sciences Centre, BC Cancer, Vancouver, BC V5T 4S6, Canada. Centre for Infectious Disease Genomics and One Health (CIDGOH), Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. Executive Administration of Research Center, King Fahad Medical City, Riyadh 12231, Saudi Arabia.
  • Centre for Infectious Disease Genomics and One Health (CIDGOH), Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
  • Clinical Pathology Department, King Fahad Medical City, Riyadh 12231, Saudi Arabia.
  • Executive Administration of Research Center, King Fahad Medical City, Riyadh 12231, Saudi Arabia.
  • Bioinformatics Graduate Program, University of British Columbia, Genome Sciences Centre, BC Cancer, Vancouver, BC V5T 4S6, Canada.

Abstract

Motivation

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.

Results

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.

Availability and implementation

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