Global Burden of Animal Diseases informatics strategy, data quality and model interoperability.

IF 1.9 4区 农林科学 Q2 VETERINARY SCIENCES
K Raymond, K E Sobkowich, J D Phillips, L Nguyen, I Mckechnie, R N Mohideen, W Fitzjohn, M Szurkowski, J Davidson, J Rushton, D A Stacey, T M Bernardo
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引用次数: 0

Abstract

The estimation of the global burden of animal diseases requires the integration of multidisciplinary models: economic, statistical, mathematical and conceptual. The output of one model often serves as input for another; therefore, consistency of the model components is critical. The Global Burden of Animal Diseases (GBADs) Informatics team aims to strengthen the scientific foundations of modelling by creating tools that address challenges related to reproducibility, as well as model, data and metadata interoperability. Aligning with these aims, several tools are under development: a) GBADs'Trusted Animal Information Portal (TAIL) is a data acquisition platform that enhances the discoverability of data and literature and improves the user experience of acquiring data. TAIL leverages advanced semantic enrichment techniques (natural language processing and ontologies) and graph databases to provide users with a comprehensive repository of livestock data and literature resources. b) The interoperability of GBADs'models is being improved through the development of an R-based modelling package and standardisation of parameter formats. This initiative aims to foster reproducibility, facilitate data sharing and enable seamless collaboration among stakeholders. c) The GBADs Knowledge Engine is being built to foster an inclusive and dynamic user community by offering data in multiple formats and providing user-friendly mechanisms to garner feedback from the community. These initiatives are critical in addressing complex challenges in animal health and underscore the importance of combining scientific rigour with user-friendly interfaces to empower global efforts in safeguarding animal populations and public health.

全球动物疾病负担信息学战略、数据质量和模型互操作性。
估算全球动物疾病负担需要整合多学科模型:经济、统计、数学和概念模型。一个模型的输出往往是另一个模型的输入;因此,模型组成部分的一致性至关重要。全球动物疾病负担(GBADs)信息学团队的目标是通过创建各种工具,应对与可重复性以及模型、数据和元数据互操作性有关的挑战,从而加强建模的科学基础。根据这些目标,目前正在开发以下几种工具:a) GBADs 的可信动物信息门户(TAIL)是一个数据获取平台,可提高数据和文献的可发现性,改善用户获取数据的体验。TAIL 利用先进的语义丰富技术(自然语言处理和本体论)和图形数据库,为用户提供全面的家畜数据和文献资源库。 b) 通过开发基于 R 的建模软件包和参数格式的标准化,GBADs 模型的互操作性正在得到改善。c) 正在建设 GBADs 知识引擎,通过提供多种格式的数据和方便用户的机制来收集社区的反馈意见,从而建立一个包容和充满活力的用户社区。这些举措对于应对动物健康方面的复杂挑战至关重要,并强调了将科学严谨性与用户友好界面相结合的重要性,以增强全球在保护动物种群和公共健康方面的努力。
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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
22
审稿时长
>24 weeks
期刊介绍: The Scientific and Technical Review is a periodical publication containing scientific information that is updated constantly. The Review plays a significant role in fulfilling some of the priority functions of the OIE. This peer-reviewed journal contains in-depth studies devoted to current scientific and technical developments in animal health and veterinary public health worldwide, food safety and animal welfare. The Review benefits from the advice of an Advisory Editorial Board and a Scientific and Technical Committee composed of top scientists from across the globe.
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