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

数据来源是科学信息处理和其他领域的一个基本问题。近年来，与数据来源问题直接相关的研究有两条主线。其中一种是工作流中的起源，重点是从事件日志中提取起源，这些事件标记了不同模块对各种初始和派生数据集的执行。在数据库中的另一项研究中，重点是通过构成数据库视图的操作符传播种源，或通过数据库内和数据库之间的复制/剪切和粘贴操作传播种源。这两个机构使用了不同的技术，乍一看，他们的结果似乎截然不同。然而，在许多科学应用程序中，数据库操作与工作流模块的执行共存，结果数据的来源应该将这两种处理集成到一个可用的范例中。通过分析工作流和数据库中的数据来源工作，PI确定了他们认为统一和集成这两种不同类型的数据来源的主要困难：(1)缺乏足够丰富的数据模型来捕获数据结构和工作流结构之间的交互；(2)缺乏可以统一处理数据库操作员和工作流模块的高级规范框架。在这个项目中，PIs旨在克服这些困难，从而提供概念和工具，以便能够真正全面地处理科学数据的来源。该项目的方法依赖于支持嵌套集合的数据模型和对工作流规范的函数式语言方法。在此基础上，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科学工作流程中定义、管理和查询数据来源。该项目预计将影响生物信息学(通过宾夕法尼亚大学生物信息学中心和宾夕法尼亚大学基因组前沿研究所的跨学科合作)和系统信息学(通过对NSF ATOL计划的贡献)以及正在进行的关于工作流程和商业流程(例如，商业流程)来源的标准化工作。该项目的结果以出版物的形式传播，通过直接合作和通过项目网站：http://db.cis.upenn.edu/research/UNIPROVE.html.

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.