EAGER: Collaborative Research: Conflict Resolution and Exchange of Temporal Data

越来越多的应用程序（如欺诈检测和个人电子健康记录）都依赖于实体的集成、一致和可查询视图的可用性。这样的视图作为一个集成的存档实现，可以整合来自不同数据源的时间信息，并通过明确显示有关实体的事实为真的时间来创造重要的附加价值。即使使用最先进的数据集成技术，创建集成归档的任务仍然不是简单的。这是一个高风险的研究项目，目标是在几个研究领域的联系具有挑战性的问题：数据交换，时间数据库，冲突解决和数据不一致。该项目有潜力通过开发一个基础框架，促进整合来自不同异构时间数据源的时间数据的过程，从而产生重大的社会影响。预计这样一个平台的可用性将导致新的应用程序类别，特别是那些涉及分析、跟踪、监视和理解实体随时间演变的应用程序。该项目将涉及对科学和工程专业的研究生和本科生，包括计算机科学领域代表性不足的群体的成员，在数据集成的相关领域进行研究和培训。该调查的结果将被纳入纽约州立大学布法罗分校和加州大学圣克鲁斯分校开发和教授的大规模数据集成高级研究生数据管理课程。从这个项目的成果中选出的材料也将被纳入两所大学教授的高年级本科数据库课程。该建议将为交换时间数据（即将时间数据从一种格式转换为另一种格式）和解决时间数据冲突的问题提供正式的基础和原则性的解决方案。管理时态数据的独特挑战是管理时态数据的抽象声明性视图与其相应的具体实现视图之间的差异，这是该建议的所有方面的基础。该建议采用的一般方法将是两层的：使用基于声明性观点的视图声明性地指定时态数据的数据交换和冲突解决，而交换数据和解决冲突所需的计算任务则操作底层时间间隔。这项调查的结果也将为长期研究奠定基础，例如回答对不一致时间数据库的查询。欲了解更多信息，请访问项目网站http://greenwich.cs.ucsc.edu或http://www.cse.buffalo.edu/~chomicki/。

An increasing number of applications, such as fraud detection and personal electronic health records, all rely on the availability of an integrated, consistent, and query-able view of entities over time. Such a view, implemented as an integrated archive, consolidates temporal information from different data sources and creates significant added value by making explicit the times when facts about the entities are true. The task of creating an integrated archive remains non-trivial even with the state-of-the-art data integration techniques. This is a high-risk research project that targets challenging problems in the nexus of several research areas: data exchange, temporal databases, conflict resolution and data inconsistency. This project has the potential to make significant societal impact through the development of a foundational framework that facilitates the process of consolidating temporal data from different heterogeneous temporal data sources. It is anticipated that the availability of such a platform will lead to new classes of applications, particularly those involving profiling, tracking, monitoring, and understanding of the evolution of entities over time. This project will involve the research and training of graduate and undergraduate students in science and engineering, including members of groups underrepresented in computer science, in pertinent areas of data integration. Results obtained from this investigation will be incorporated into advanced graduate data management courses on large-scale data integration that will be developed and taught at both SUNY at Buffalo and UC Santa Cruz. Selected material from the outcomes of this project will also be incorporated into upper-division undergraduate database courses taught at both universities. This proposal will develop formal foundations and principled solutions to the problems of exchanging temporal data (i.e., transformations of temporal data from one format into another) and resolving conflicts of temporal data. The unique challenge in managing temporal data that underlies all aspects of this proposal is the management of the discrepancy between the abstract declarative view of temporal data and its corresponding concrete implementation view. The general approach adopted by this proposal will be two-tiered: data exchange and conflict resolution over temporal data are declaratively specified using the declarative point-based view, while computational tasks required to exchange data and resolve conflicts manipulate the underlying time intervals. Results from this investigation will also lay the groundwork for longer-term research such as answering queries over inconsistent temporal databases. For further information see the project web site at http://greenwich.cs.ucsc.edu or http://www.cse.buffalo.edu/~chomicki/.