ACCELERATE-BASSO: early experiences and emerging best practices for ontology development in behavioral and social science research.

IF 2.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yue Yu, Lu Kang, Susan Michie, William D Duncan, John Beverley, Fang Li, Daniel W McNeil, Nan Huo, HaiFang Li, Matthew Horridge, Mark A Musen, Jiang Bian, Cui Tao
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引用次数: 0

Abstract

Background: Behavioral and social science research (BSSR) is essential for understanding human behavior and informing interventions, policy, and health outcomes; however, such research faces persistent challenges related to fragmented knowledge, imprecise and inconsistent terminology, and limited interoperability across studies. Ontologies provide a promising solution by enabling standardized, machine-readable representations of concepts and relationships to support data integration, knowledge synthesis, and reproducibility.

Results: We present an initial overview of the ACCELERATE-BASSO Research Network, an NIH-supported consortium established to advance BSSR through ontology-driven approaches. Specifically, we describe the role of the Dissemination and Coordination Center (DCC) and the Best Practices Working Group (BPWG) in supporting a network of projects focusing on accelerating BSSR through ontology development and use. Based on the consortium's early experiences, we summarize emerging ontology-driven practices, current interoperability efforts, and common methodological considerations identified across the participating projects. Rather than proposing a formal consensus framework, this work provides an initial consortium perspective on current ontology development activities and shared lessons learned. We also discuss the potential role of ontologies in supporting AI-related applications in BSSR.

Conclusions: This paper provides an initial consortium perspective on ontology-driven approaches for advancing BSSR. By synthesizing early experiences, emerging practices, and shared challenges across multiple projects, it offers insights to inform future ontology development, interoperability, and community consensus while laying the foundation for more systematic evaluation and broader adoption within the BSSR community.

加速- basso:行为和社会科学研究中本体发展的早期经验和新兴最佳实践。
背景:行为和社会科学研究(BSSR)对于理解人类行为和为干预措施、政策和健康结果提供信息至关重要;然而,此类研究面临着与知识碎片化、术语不精确和不一致以及研究之间有限的互操作性相关的持续挑战。本体提供了一个很有前途的解决方案,它支持概念和关系的标准化、机器可读的表示,以支持数据集成、知识合成和再现性。结果:我们提出了加速- basso研究网络的初步概述,这是一个由美国国立卫生研究院支持的联盟,旨在通过本体驱动的方法推进BSSR。具体来说,我们描述了传播和协调中心(DCC)和最佳实践工作组(BPWG)在支持通过本体开发和使用加速BSSR的项目网络中的作用。基于联盟的早期经验,我们总结了新兴的本体驱动实践、当前的互操作性工作,以及在参与项目中确定的通用方法考虑。这项工作并没有提出一个正式的共识框架,而是提供了一个关于当前本体开发活动和共享经验教训的初步联盟视角。我们还讨论了本体在支持BSSR中人工智能相关应用方面的潜在作用。结论:本文提供了本体驱动方法推进BSSR的初步联盟视角。通过综合早期经验、新兴实践和跨多个项目的共同挑战,它为未来的本体开发、互操作性和社区共识提供了见解,同时为BSSR社区中更系统的评估和更广泛的采用奠定了基础。
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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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