Collaborative Research: Elements: TRAnsparency CErtified (TRACE): Trusting Computational Research Without Repeating It

协作研究：要素：TRAnsparency CErtified (TRACE)：信任计算研究而不重复它

• 批准号: 2209629
• 负责人: Lars Vilhuber
• 金额: $ 15万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2209629&HistoricalAwards=false
• 关键词: Collaborative; Research; Elements; TRAnsparency; CErtified

Research communities across the natural and social sciences are increasingly concerned about the transparency and reproducibility of results obtained by computational means. Calls for increased transparency can be found in the policies of peer-reviewed journals and processing pipelines employed in the creation of research data products made available through science gateways, data portals, and statistical agencies. These communities recognize that the integrity of published results and data products is uncertain when it is not possible to trace their lineage or validate their production. Verifying the transparency or reproducibility of computational artifacts—by repeating computations and comparing results—is expensive, time-consuming, and difficult, and may be infeasible if the research products rely on resources that are subject to legitimate restrictions such as the use of sensitive or proprietary data; streaming, transient, or ephemeral data; and large-scale or specialized computational resources available only to approved or authorized users. The TRACE project is addressing this problem through an approach called certified transparency - a trustworthy record of computations signed by the systems within which they were performed. Using TRACE, system owners and operators certify the original execution of a computational workflow that produces findings or data products. By using a TRACE-enabled system, researchers produce transparent computational artifacts that no longer require verification, reducing burden on journal editors and reviewers seeking to ensure reproducibility and transparency of computational results. TRACE presents an innovative and efficient approach to ensuring the transparency of research that uses computational methods, is consistent with the vision outlined by the National Academies, and enables evidence-based policymaking based on transparent and trustworthy science.The central goal of the TRACE project is the development, validation, and implementation of a technical model of certified transparency. This includes a set of infrastructure elements that can be employed by system owners to (1) declare the dimensions of computational transparency supported by their platforms; (2) certify that a specific computational workflow was executed on the platform; and (3) bundle artifacts, records of their execution, technical metadata about their contents, and certify them for dissemination. The first phase of the project focuses on the development of a conceptual model and technical specification that can be used to certify the description of a system, termed a Transparency-Certified System (TRACE system), and the aggregation of artifacts along with records of their execution, termed Transparency-Certified Research Objects (TROs). The second phase focuses on the development of reusable software components implementing the TRACE model and approach. To demonstrate certified transparency, the toolkit is used to TRACE-enable existing platforms including Whole Tale, SKOPE, and the SLURM workload manager. These TRACE-enabled systems produce certified TROs that can be trusted and do not need to be repeated or re-executed to verify that results were obtained as claimed.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Social and Economic Sciences within the Directorate for Social, Behavioral and Economic Sciences; and by the Division of Information and Intelligent Systems within the Directorate for Computer and Information Science and Engineering.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.

自然科学和社会科学的研究界越来越关注通过计算手段获得的结果的透明度和可重复性。提高透明度的呼吁可以在同行评审期刊的政策和通过科学网关、数据门户和统计机构提供的研究数据产品的创建过程中使用的处理管道中找到。这些社区认识到，如果无法追踪其来源或验证其生产，则已公布的结果和数据产品的完整性是不确定的。通过重复计算和比较结果来验证计算伪像的透明度或可再现性是昂贵的、耗时的和困难的，并且如果研究产品依赖于受到合法限制的资源，则可能是不可行的，例如使用敏感或专有数据;流数据、瞬时数据或短暂数据;以及仅对经批准或授权的用户可用的大规模或专用计算资源。TRACE项目正在通过一种被称为认证透明度的方法来解决这个问题--一种由执行这些计算的系统签名的可信赖的计算记录。使用TRACE，系统所有者和操作员可以证明产生结果或数据产品的计算工作流程的原始执行。通过使用支持TRACE的系统，研究人员可以生成透明的计算工件，不再需要验证，从而减轻期刊编辑和审稿人的负担，以确保计算结果的可重复性和透明度。TRACE是一种创新和有效的方法，以确保使用计算方法的研究的透明度，与美国国家科学院概述的愿景一致，并使基于透明和值得信赖的科学的循证决策成为可能。TRACE项目的中心目标是开发，验证和实施认证透明度的技术模型。这包括一组基础设施元素，系统所有者可以使用这些元素来（1）声明其平台支持的计算透明度的维度;（2）证明特定的计算工作流在平台上执行;以及（3）捆绑工件，其执行记录，关于其内容的技术元数据，并证明它们用于传播。该项目的第一阶段集中在概念模型和技术规范的开发上，这些模型和技术规范可用于证明系统的描述，称为合格性认证系统（TRACE系统），以及工件沿着及其执行记录的聚合，称为合格性认证研究对象（TRO）。 第二阶段的重点是开发可重用的软件组件，实现TRACE模型和方法。为了证明经过认证的透明度，该工具包用于TRACE启用现有平台，包括Whole Tale、SKOPE和SLURM工作负载管理器。这些支持TRACE的系统生成经过认证的TRO，这些TRO值得信赖，不需要重复或重新执行来验证所获得的结果是否如声明的那样。高级网络基础设施办公室的这一奖项由社会和经济部门共同支持。社会、行为和经济科学理事会;该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的学术价值和更广泛的影响审查标准。