Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.
Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.
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流行病学建模的可视化：挑战，解决方案，反思和建议。
DOI：
10.1098/rsta.2021.0299
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发表时间：
2022-10-03
期刊：
影响因子：
5
通讯作者：
Xu, Kai
中科院分区：
文献类型：
--
作者：
Dykes, Jason;Abdul-Rahman, Alfie;Archambault, Daniel;Bach, Benjamin;Borgo, Rita;Chen, Min;Enright, Jessica;Fang, Hui;Firat, Elif E.;Freeman, Euan;Gonen, Tuna;Harris, Claire;Jianu, Radu;John, Nigel W.;Khan, Saiful;Lahiff, Andrew;Laramee, Robert S.;Matthews, Louise;Mohr, Sibylle;Nguyen, Phong H.;Rahat, Alma A. M.;Reeve, Richard;Ritsos, Panagiotis D.;Roberts, Jonathan C.;Slingsby, Aidan;Swallow, Ben;Torsney-Weir, Thomas;Turkay, Cagatay;Turner, Robert;Vidal, Franck P.;Wang, Qiru;Wood, Jo;Xu, Kai
我们报告了流行病学建模者和可视化研究人员之间正在进行的合作，通过记录和反思知识结构（从现有可视化研究和实践中获得的一系列想法、方法和方法）来部署和开发以支持COVID-19大流行的建模。结构化的独立评论，这些努力是通过迭代式的反思，以开发：在这种情况下可视化的有效性和价值的证据;开放的问题，研究界可能会关注;指导未来的活动，这类和建议，以保障成就和促进，推进，安全和准备未来的这种合作。在描述和比较在前所未有的条件下开展的一系列相关项目时，我们希望这份独特的报告及其丰富的互动补充材料将指导科学界在观察、分析和建模数据以及传播研究结果时采用可视化。同样，我们希望鼓励可视化社区参与有影响力的科学，以解决其新兴的数据挑战。如果我们取得成功，这一展示活动可能会刺激具有互补专业知识的社区之间的互利接触，以解决流行病学及其他领域的重要问题。明白了这篇文章是“模拟现实生活中的流行病的技术挑战和克服这些挑战的例子”主题的一部分。
We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs—a series of ideas, approaches and methods taken from existing visualization research and practice—deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. See . This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.
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作者：
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通讯作者：
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DOI：
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DOI：
10.1109/tvcg.2013.193
发表时间：
2013-12-01
影响因子：
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作者：
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