Pfizer Inc, 1 Portland Street, Cambridge, MA, 02139, USA.
Scibite an Elsevier Company, Scibite Ltd, Biodata Innovation Centre, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1DR, UK.
J Biomed Semantics. 2023 Aug 11;14(1):10. doi: 10.1186/s13326-023-00288-6.
With the capacity to produce and record data electronically, Scientific research and the data associated with it have grown at an unprecedented rate. However, despite a decent amount of data now existing in an electronic form, it is still common for scientific research to be recorded in an unstructured text format with inconsistent context (vocabularies) which vastly reduces the potential for direct intelligent analysis. Research has demonstrated that the use of semantic technologies such as ontologies to structure and enrich scientific data can greatly improve this potential. However, whilst there are many ontologies that can be used for this purpose, there is still a vast quantity of scientific terminology that does not have adequate semantic representation. A key area for expansion identified by the authors was the pharmacokinetic/pharmacodynamic (PK/PD) domain due to its high usage across many areas of Pharma. As such we have produced a set of these terms and other bioassay related terms to be incorporated into the BioAssay Ontology (BAO), which was identified as the most relevant ontology for this work. A number of use cases developed by experts in the field were used to demonstrate how these new ontology terms can be used, and to set the scene for the continuation of this work with a look to expanding this work out into further relevant domains. The work done in this paper was part of Phase 1 of the SEED project (Semantically Enriching electronic laboratory notebook (eLN) Data).
随着电子数据的生成和记录能力的提高，科学研究及其相关数据以前所未有的速度增长。然而，尽管现在已经有相当数量的数据以电子形式存在，但科学研究仍然以非结构化的文本格式记录，上下文（词汇）不一致，这极大地降低了直接进行智能分析的可能性。研究表明，使用语义技术（如本体）来结构化和丰富科学数据可以极大地提高这种可能性。然而，虽然有许多可用于此目的的本体，但仍有大量的科学术语没有足够的语义表示。作者确定的一个需要扩展的关键领域是药代动力学/药效学（PK/PD）领域，因为它在制药的许多领域都有很高的使用率。因此，我们生成了一组这些术语和其他与生物测定相关的术语，将其纳入生物测定本体（BAO），这被确定为这项工作最相关的本体。该领域的专家开发了一些用例，用于演示如何使用这些新的本体术语，并为继续这项工作奠定基础，进一步将这项工作扩展到其他相关领域。本文所做的工作是 SEED 项目（语义增强电子实验室笔记本（eLN）数据）第一阶段的一部分。
