SDCI Data: New Toolkit for Provenance Collection, Publishing, and Experience Reuse

SDCI 数据：用于来源收集、发布和体验重用的新工具包

• 批准号: 0721674
• 负责人: Beth Plale
• 金额: $ 43.3万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0721674&HistoricalAwards=false
• 关键词: SDCI; Data; New; Toolkit; Provenance

OCI - SDCI Data: New Toolkit for Provenance Collection, Publishing, and Experience ReuseAs research digital data collections created through computational science experiments proliferate, it becomes increasingly important to address the provenance issues of the data validity and quality: to record and manage information about where each data object originated, the processes applied to the data products, and by whom. The first outcome of this work is a provenance collection and experience reuse tool that makes minimal assumptions about the software environment and imposes minimal burden on the application writer. It stores and produces results in a form suitable for publication to a digital library. The provenance collection system is a standalone system that imposes a minimal burden on users to integrate it into their application framework and it exhibits good performance. A second outcome of the work is a recommender system for workflow completion that employs case-based reasoning to provenance collections in order to make suggestions to users about future workflow-driven investigations. The workflow completion tool builds on computer models of case-based reasoning to develop a support system that leverages the collective experience of the users of the provenance system to provide suggestions. As a key part of effectively evaluating aspects of the tool, this work builds a gigabyte benchmark database of real and synthetic provenance information. Real workflows are sought from the community, with synthetic extensions to the data set for completeness for purposes of testing. The software and database are available to the research community.

OCI -SDCI数据：用于出处收集，发布和体验Reuseas研究数字数据收集的新工具包通过计算科学实验泛滥，解决数据有效性和质量的出处问题变得越来越重要：记录和管理有关每个数据对象的信息，以及应用于数据产品的过程以及对数据产品的应用以及通过谁。这项工作的第一个结果是出处收集和经验重用工具，对软件环境的假设最少，并对应用程序作者施加最小的负担。它存储并以适合出版的数字图书馆出版的形式存储并产生结果。 出处收集系统是一个独立的系统，它对用户施加最小的负担，将其集成到其应用程序框架中，并且表现出色。工作的第二个结果是用于完成工作流程的推荐系统，该系统采用基于案例的推理来出处收集，以向用户提出有关未来工作流驱动的调查的建议。工作流程完成工具基于基于病例的推理的计算机模型，以开发一个支持系统用户的集体体验的支持系统，以提供建议。作为有效评估该工具方面的关键部分，这项工作构建了一个千兆字节的基准数据库，这些数据库是真实和合成的出处信息。 从社区中寻求真正的工作流程，并将数据集的合成扩展为完整性，以进行测试。 该软件和数据库可用于研究社区。