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: 0347903
• 负责人: AnHai Doan
• 金额: $ 50万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-01 至 2007-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0347903&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://anhai.cs.uiuc.edu/home/projects/aida.html that will include the resulting research results, data and system artifacts.

数据集成系统提供了对大量数据源的统一访问。它们有可能彻底改变我们访问数据的方式，并为构建更先进的信息处理架构提供基础。然而，今天这样的系统仍然非常难以建立和昂贵的维护。必须详细地告诉它们如何与数据源交互，并且必须不断修改以处理数据源的更改。为了解决这个问题，该项目设想构建数据集成系统，该系统可以随着时间的推移学会进化和自我管理，而人工干预最少。为了实现这一愿景，该项目采用数据库和人工智能（特别是机器学习）技术来应对以下核心挑战：(a)有效地自动化关键的劳动密集型任务，包括模式匹配、全局模式创建和重复检测；(b)以最小的人工干预检测由于源更改而导致的系统故障；(c)通过将负担分散到大量用户上，进一步减少系统管理员的巨大数据集成负担。教育计划利用这项研究为学生和更广泛的社区做好准备，以应对互联网世界提出的新的数据管理挑战。就智力价值而言，该项目在数据集成研究方面迈出了合乎逻辑的下一步。它为几乎所有数据集成或共享工作背后的基本问题提供了概念上新颖的解决方案。该项目的结果具有自主计算应用的潜力。就更广泛的影响而言，该项目将促进数据集成系统的广泛部署，从而为社会带来更有效的信息管理和获取。它在培养下一代专业工作者和研究人员方面发挥着不可或缺的作用。该研究还将帮助伊利诺伊州农村消防人员整合数据，并培训他们如何访问和使用综合信息系统。项目信息将通过出版物、讲习班、教程和网站http://anhai.cs.uiuc.edu/home/projects/aida.html传播，该网站将包括最终的研究结果、数据和系统工件。