III-COR-Medium: Providing Provenance through Workflows and Database Transformations

III-COR-Medium：通过工作流程和数据库转换提供来源

• 批准号: 0803524
• 负责人: Susan Davidson
• 金额: $ 81.66万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0803524&HistoricalAwards=false
• 关键词: III; COR; Medium; Providing; Provenance

Data provenance is a fundamental issue in the processing of scientific information and beyond. Two lines of research have been pursued in recent years with direct bearing on the issues of data provenance. In one of them, provenance in workflows, the emphasis is on extracting provenance from logs of events marking the execution of different modules to various intial and derived datasets. In the other line of research, provenance in databases, the emphasis is on the propagation of provenance through the operators that make up database views, or on propagation of provenance through copy/cut-and-paste operations within and among databases. These two bodies of work employ different techniques and at first glance their results appear quite different. However, in many scientific applications, database manipulations co-exist with the execution of workflow modules, and the provenance of the resulting data should integrate both kinds of processing into a usable paradigm. By analyzing the work on data provenance in workflows and in databases, the PIs identify what they believe are the main difficulties in unifying and integrating these two different kinds of data provenance:(1) the lack of a data model that is rich enough to capture the interaction between the structure of the data and the structure of the workflow; and(2) the lack of a high-level specification framework in which database operators and workflow modules can be treated uniformly. In this project, the PIs aim to overcome these difficulties and thus provide concepts and tools that allow a truly comprehensive approach to the provenace of scientific data. The project's approach relies on a data model that supports nested collections and on a functional language approach to workflow specification. Based on this, the project aims to deliver a framework and tools for defining, managing and querying data provenance in complexscientific workflows that include database manipulations. The project is expected to impact bioinformatics (through interdisciplinary collaborations in the Penn Center for Bioinformatics and the Penn Genome Frontiers Institute) and phyloinformatics (through contributions to the NSF AToL program) as well as ongoing standardization work on provenance in workflows and in the business processes (eg., BPEL) community.The results of this project are disseminated as publications, through direct collaborations and through the project website: http://db.cis.upenn.edu/research/UNIPROVE.html.

数据出处是处理科学信息及其他问题的基本问题。近年来，已经进行了两项研究，这与数据出处问题有关。在其中一个，在工作流程中的出处，重点是从标记不同模块执行到各种Intial和派生数据集的事件的日志中提取出处。在数据库中的其他研究中，重点是通过构成数据库视图的操作员或通过数据库内和数据库中的复制/剪切操作传播来源的运营商传播。 这两个工作的身体采用了不同的技术，乍一看它们的结果似乎完全不同。但是，在许多科学应用中，数据库操作与执行工作流模块共存，并且所得数据的出处应将两种处理过程集成到可用的范式中。通过分析工作流程和数据库中数据出处的工作，PIS确定了他们认为是统一和整合这两种不同类型的数据出处的主要困难：（1）缺乏足够丰富的数据模型，足以捕获数据结构之间的交互作用和工作流的结构； （2）缺乏高级规范框架，其中数据库运算符和工作流模块可以均匀处理。在这个项目中，PI旨在克服这些困难，从而提供概念和工具，从而为科学数据的验证提供真正的全面方法。该项目的方法依赖于支持嵌套集合和功能语言方法的数据模型。基于此，该项目旨在提供一个框架和工具，用于在包括数据库操作的复杂工作流中定义，管理和查询数据出处。预计该项目将影响生物信息学（通过宾夕法尼亚生物信息学中心和宾夕法尼亚基因组领域研究所的跨学科合作）和植物形式（通过对NSF ATOL计划的贡献）以及通过工作流程和业务群体（eg。项目网站：http：//db.cis.upenn.edu/research/uniprove.html。