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

被引:0
|
作者
Raymond, K. [1 ,2 ]
Sobkowich, K. E. [1 ,3 ]
Phillips, J. D. [1 ,2 ,3 ]
Nguyen, L. [1 ,2 ]
McKechnie, I. [1 ,2 ]
Mohideen, R. N. [1 ,2 ]
Fitzjohn, W. [1 ,2 ]
Szurkowski, M. [1 ,2 ]
Davidson, J. [1 ,2 ]
Rushton, J. [1 ,4 ]
Stacey, D. A. [1 ,2 ]
Bernardo, T. M. [1 ,3 ]
机构
[1] Univ Liverpool, Inst Infect Vet & Ecol Sci, Global Burden Anim Dis GBADs Programme, 146 Brownlow Hill, Liverpool L3 5RF, England
[2] Univ Guelph, Sch Comp Sci, Reynolds Bldg,474 Gordon St, Guelph, ON N1G 2W1, Canada
[3] Univ Guelph, Ontario Vet Coll, Dept Populat Med, 50 Stone Rd East, Guelph, ON N1G 2W1, Canada
[4] Univ Liverpool, Inst Infect Vet & Ecol Sci, Dept Livestock & One Hlth, 146 Brownlow Hill, Liverpool L3 5RF, England
关键词
Data management; Data quality; Data science; GBADs; Global Burden of Animal Diseases; Interoperability; Reproducibility;
D O I
10.20506/rst.43.3522
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
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. - 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. - 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. - 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.
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页数:203
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