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: 2209628
• 负责人: Bertram Ludaescher
• 金额: $ 35万
• 依托单位: University of Illinois at Urbana-Champaign
• 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=2209628&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。在创建通过科学门户、数据门户和统计机构提供的研究数据产品时使用的同行评议期刊和处理管道的政策中，可以找到增加透明度的呼吁。这些社区认识到，当无法追踪其血统或验证其生产时，发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人工产物的透明度或重现性是昂贵、耗时和困难的，如果研究产品依赖于受合法限制的资源，例如使用敏感或专有数据；流、瞬时或短暂数据；以及仅对经批准或授权的用户可用的大规模或专门计算资源，则可能是不可行的。TRACE项目正在通过一种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署的可信的计算记录。使用TRACE，系统所有者和操作员验证产生结果或数据产品的计算工作流的原始执行。通过使用支持跟踪的系统，研究人员制作出不再需要验证的透明计算人工制品，从而减轻了寻求确保计算结果的重复性和透明度的期刊编辑和审查员的负担。TRACE提供了一种创新和高效的方法来确保研究的透明度，它使用计算方法，与国家科学院概述的愿景一致，并使基于证据的决策建立在透明和值得信赖的科学的基础上。TRACE项目的中心目标是开发、验证和实施经认证的透明度的技术模型。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)证明在平台上执行了特定的计算工作流程；以及(3)捆绑人工制品、其执行的记录、关于其内容的技术元数据，并对其进行认证以供传播。该项目的第一阶段侧重于开发一个概念模型和技术规范，可用来证明一个系统的描述，称为透明度认证系统(TRACE系统)，以及人工制品及其执行记录的集合，称为透明度认证研究对象(TRO)。第二阶段侧重于实现跟踪模型和方法的可重用软件组件的开发。为了演示经过认证的透明度，该工具包用于跟踪启用现有平台，包括Whole Tale、Skope和Slurm工作负载管理器。这些启用跟踪的系统产生可信任的认证的TRO，不需要重复或重新执行来验证获得了声称的结果。这一奖项由高级网络基础设施办公室获得，由社会、行为和经济科学局内的社会和经济科学部以及计算机和信息科学与工程局内的信息和智能系统部联合支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。