CAREER: Evolving and Self-Managing Data Integration Systems

职业：不断发展和自我管理的数据集成系统

• 批准号: 0712836
• 负责人: AnHai Doan
• 金额: --
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-31 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0712836&HistoricalAwards=false
• 关键词: CAREER; Evolving; Self; Managing; Data

Data integration systems provide a uniform access to a multitude of data sources. They have the potential to revolutionize the way we access data, and provide a basis on which to build even more advanced information processing architectures. However, today such systems are still extremely hard to build and costly to maintain. They must be told in tedious detail how to interact with data sources, and must be constantly modified to deal with changes at the sources. To address this problem, the project envisions building data integration systems that learn to evolve and self-manage over time, with minimal human intervention. To make fundamental contributions toward realizing this vision, the project employs database and artificial intelligence (especially machine learning) techniques to attack the following central challenges: (a) effectively automating key labor-intensive tasks, including schema matching, global schema creation, and duplicate detection, (b) detecting system failures due to changes at the sources, with minimal human intervention, and (c) further reducing the tremendous data integration burden of the system administrators by spreading the burden thinly over the mass of users. The education plan leverages the research to prepare students and the broader community for the novel data management challenges raised by the Internet world. In terms of intellectual merit, the project takes a next logical step in data integration research. It brings conceptually novel solutions to fundamental issues underlying virtually any data integration or sharing efforts. The project results have the potential for autonomic-computing applications. In terms of broader impacts, the project will facilitate the widespread deployment of data integration systems, thus resulting in more effective information management and access for society. It plays an integral part in educating next-generation professional workers and researchers. The research will also help integrate data for rural Illinois fire fighters, and train them in access and use of the integrated information systems. The project information will be disseminated via publications, workshops, tutorials, and the Web site http://www.cs.wisc.edu/~anhai/projects/career.html that will include the resulting research results, data and system artifacts.

数据集成系统提供了对多种数据源的统一访问。他们有可能彻底改变我们访问数据的方式，并为建立更高级的信息处理架构提供基础。但是，如今，这样的系统仍然很难构建，并且维护成本很高。必须详尽地将它们告知如何与数据源进行交互，并且必须经常修改以处理来源的更改。为了解决这个问题，该项目设想建立数据集成系统，这些系统随着时间的流逝而学会发展和自我管理，并且人类干预最少。为了为实现这一愿景做出基本贡献，该项目采用数据库和人工智能（尤其是机器学习）技术来攻击以下核心挑战：（a）有效地自动化关键的关键劳动密集型任务，包括架构匹配，全球架构创建，以及由于源造成的检测而导致的the the Munters Internition the Munter Internity（c），（b）contection and the the Internect andim nime news（c）系统管理员通过将负担稀薄地扩展到大量用户中。教育计划利用研究为学生和更广泛的社区做好准备，以使互联网世界提出的新型数据管理挑战。就智力优点而言，该项目在数据集成研究中迈出了下一个逻辑步骤。它从概念上将新颖的解决方案带入了几乎任何数据集成或共享工作的基本问题。该项目的结果有可能进行自动计算应用程序。在更广泛的影响方面，该项目将促进数据集成系统的广泛部署，从而为社会提供更有效的信息管理和访问。它在教育下一代专业工作者和研究人员中起着不可或缺的作用。这项研究还将有助于整合伊利诺伊州农村消防员的数据，并培训它们以访问和使用集成信息系统。项目信息将通过出版物，研讨会，教程和网站http://www.cs.wisc.edu/~anhai/projects/career.html传播，其中将包括所得的研究结果，数据和系统工件。