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

科学越来越多地基于科学模拟、数据管理和分析、仪器控制和协作的计算。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。通过探索在激光干涉仪引力波天文台（LIGO）项目中工作的引力波天文学研究人员的实践，该项目旨在创建一套案例研究，记录可重复计算科学的广泛适用方法。具体来说，该项目将探索和阐明引力波天文学中基于计算的研究的可重复性、自动化和信任意味着什么，确定、实施和验证一组实验实践，其中将包括计算技术，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谨的方法之上，由三个关键要素组成：(1)可重复性，这使得科学家的发现能够得到验证和利用；(2)自动化，它加快了对替代解决方案的探索和对大量数据的处理，同时减少了错误的引入；(3)信任，为软件和数据提供安全性和可靠性，同时为科学家自己的结果和他人的结果提供必要的信任属性。本项目在引力波天文学的背景下，通过以下活动探索了LIGO项目中可靠的科学：(1)阐明了引力波天文学中再现性、自动化和信任的作用；（二）确定、实施和验证一套实验实践，包括计算技术；(3)通过评估如何将实验实践扩展到其他科学领域，推进该项目对稳健科学的通用计算方法的愿景。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、计算和数据操作步骤组成。对调查的分析将产生一份文件，描述LIGO背景下的再现性意味着什么，并帮助确定LIGO实践中的潜在改进。该项目将通过记录LIGOÕs的原始和增强方法到其他科学工作流程（包括分子动力学和生物信息学社区的工作流程）的映射来推广这些发现。最终的项目文件将面向包括不同教育水平的研究人员和学生在内的广泛受众，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、数据和工作流信息以再生发现，学习科学方法，并参与STEM研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.