STARS: Sharing Tools and Artifacts for Reproducible Simulation

STARS：共享可重复模拟的工具和工件

• 批准号: MR/Z503915/1
• 负责人: Thomas Monks
• 金额: $ 41.56万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FZ503915%2F1
• 关键词: STARS; Sharing; Tools; Artifacts; Reproducible

Background:Simulation models are computational tools that use detailed logic, data, and computer code to provide a quantitative way for researchers to make predictions about drug effectiveness, and health services operational flow. These models are used extensively in health and medical research to assess the effects of changes to patient care and to manage and understand pandemics like Covid-19. The most common approach used in these studies is called discrete-event simulation.Challenges:Very few published studies using discrete-event simulation meet the scientific standard for being open to (re)use, and scrutiny by others. In contrast, fields outside of healthcare, such as Ecology, have seen growth in model sharing. This means that healthcare results are more difficult to fully check or reproduce, and models are not tested for mistakes. Even when a model is shared with a scientific paper, there are considerable challenges in installing specialist simulation software, researcher concerns about intellectual property, time/effort needed to do the sharing, and how long a model remains available.

背景：仿真模型是使用详细逻辑，数据和计算机代码的计算工具，为研究人员提供了有关药物有效性和卫生服务运营流量的定量方式。这些模型在健康和医学研究中广泛使用，以评估患者护理的变化以及管理和理解Covid-19等大流行的影响。这些研究中使用的最常见方法称为离散事件模拟。挑战：很少使用离散事实模拟的发表研究符合科学标准，以开放（重新）使用（重新）和其他人的审查。相比之下，医疗保健以外的领域（例如生态学）已经看到了模型共享的增长。这意味着医疗保健结果更难完全检查或复制，并且未针对错误进行测试。即使与科学论文共享模型，安装专家仿真软件也面临着巨大挑战，研究人员对知识产权，需要进行分享的时间/精力以及模型可用的时间。