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A biobank contains a collection of biological samples, along with associated medical information of sample donors, for further research use. Given the wealth of information that can be derived from stored information and biological materials, there is a pressing need for structuring biobank data in a manner that allows subsequent computer-based analyses. Currently, the value of biobank data lies in how it can be linked with other molecular and clinical data (“-omics data”), to provide new insights into health and disease. Linking data has thus far, however, proven challenging due to unstructured and incompatible data types. Here, we describe the development of a Next-Generation biobanking ontology (NGBO) that is capable of supporting both Biospecimen processing, management, storage and retrieval infrastructure, and acting as a knowledge hub for an integrated clinical and translational research ecosystem integrating –omics data.
The value of biobank data could be optimized if the broad array of content of various biobank records could be standardized and integrated. A key development of facilitating data standardization includes the application of semantics and ontologies (Andrade et al. 2012). In this work, we integrated biobank –omics data through the creation of next-generation biobanking ontology in order to better structure data for various scientific research and personalized medicine analyses. NGBO harmonizes the instrumentation and procedures used to prepare and process specimens, and also covers terminology used to describe computational biology algorithms, analytical tools, electronic-communication protocols, in vitro assays along with integrating requirements.
principles include the application of the Basic Formal Ontology (BFO), a small upper level ontology mostly used to support information retrieval, analysis and integration across scientific and biomedical and other biological domains (Arp, Smith, and
investigation (OBI) and Genomic Epidemiology Ontology (GENEPIO). Additional terms were identified and added to
use cases from King Fahad Medical City clinical genomics reports and standard operating procedures, mainly terms describing (-omics) data and processes, such as the description of the output data files of analytical bioinformatics process.
The ontology files are publicly available at https://github.com/Dalalghamdi/NGBO. NGBO depends primarily on the (is-a) relation between classes and subclasses, thereby providing a hierarchy of classes that also enables inheritance of the properties. Additionally, pre-existing relations such as (is_specified_input_of) were used when appropriate. The ontology is still under development.
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