Collaborative Research: EAGER: Exploring and Advancing the State of the Art in Robust Science in Gravitational Wave Physics

科学越来越多地以计算为基础，用于科学模拟、数据管理和分析、仪器控制和协作。为了使通过计算产生的科学结果被认为是可靠的并被广泛接受，计算技术应该是自动化的、可重复的和值得信赖的。通过探索激光干涉仪引力波天文台(LIGO)项目中引力波天文学研究人员的做法，该项目试图创建一套案例研究，记录可重复使用的计算科学的广泛适用方法。具体地说，该项目将探索和阐明引力波天文学中基于计算的研究的重复性、自动化和信任意味着什么，确定、实施和验证一套包括计算技术的实验实践，最后评估这些实验实践如何扩展到其他科学领域。稳健的计算科学建立在严格的方法基础上，由三个关键要素组成：(1)重复性，使科学家的发现得以验证和利用；(2)自动化，加快探索替代解决方案和处理大量数据的速度，同时减少错误的引入；(3)信任，为软件和数据提供安全和可靠性，同时提供必要的属性，以信任科学家自己的结果和他人的结果。该项目通过引力波天文学方面的下列活动探索LIGO项目中的稳健科学：(1)阐明重复性、自动化和信任在引力波天文学中的作用；(2)确定、实施和验证一系列实验做法，包括计算技术；(3)通过评估如何将实验做法扩展到其他科学领域，推进该项目关于稳健科学的一般计算方法的愿景。该项目将开发并使用一项调查来收集有关LIGO工作流程的信息，该工作流程由一系列实验、计算和数据处理步骤组成。对调查的分析将产生一份文件，描述可重复性在LIGO背景下的含义，并帮助确定LIGO实践中的潜在改进。该项目将通过记录LIGO S对其他科学工作流程的原始和增强方法的映射来推广这些发现，包括分子动力学和生物信息学社区的工作流程。最终的项目文件将面向广泛的受众，包括不同教育水平的研究人员和学生，目标是向他们介绍稳健计算研究的概念，以及可重复性、自动化和信任的基本概念，教他们访问代码、数据和工作流程信息以重新生成结果，了解科学方法，并参与STEM研究。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Science is increasingly based on computation for science simulations, data management and analysis, instrument control and collaboration. For scientific results generated through computation to be considered robust and become widely accepted, the computational techniques should be automated, reproducible and trustworthy. By exploring the practices of gravitational-wave astronomy researchers working on the Laser Interferometer Gravitational-Wave Observatory (LIGO) project, this project seeks to create a set of case studies documenting broadly applicable methods for reproducible computational science. Specifically, the project will explore and articulate what reproducibility, automation, and trust mean with respect to computation-based research in gravitational-wave astronomy, identify, implement and validate a set of experimental practices, that will include computational techniques, and finally, evaluate how these experimental practices can be extended to other science domains. Robust computational science builds on rigorous methods and is composed of three key elements: (1) reproducibility, which enables the verification and leveraging of scientists' findings; (2) automation, which speeds up the exploration of alternative solutions and the processing of large amounts of data while reducing the introduction of errors; and (3) trust, providing security and reliability for software and data, while supplying the necessary attributes for confidence in the scientist's own results and results from others. This project explores robust science in the LIGO project through the following activities within the context of gravitational-wave astronomy: (1) articulating the roles of reproducibility, automation, and trust in gravitational-wave astronomy; (2) identifying, implementing and validating a set of experimental practices, including computational techniques; and (3) advancing towards the project's vision of general computational methods for robust science by evaluating how the experimental practices can be extended to other science domains. The project will develop and use a survey to collect information about LIGO workflows that are composed of a series of experimental, computational, and data manipulation steps. The analysis of the survey will result in a document that describes what reproducibility means in the LIGO context and help identify potential improvements in LIGO's practices. The project will generalize these findings by documenting a mapping of LIGOÕs original and enhanced approach to other science workflows including those of the molecular dynamics and bioinformatics communities. The final project document will target a broad audience that includes researchers and students at various levels of education, with the goal of introducing them to the concept of robust computational research, and the underlying concepts of reproducibility, automation and trust, teaching them to access code, data, and workflow information to regenerate findings, learn about the scientific methods, and to engage in STEM research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.