CAREER: Data Quality Management through Statistical Quality Control and Data Mining

职业：通过统计质量控制和数据挖掘进行数据质量管理

• 批准号: 0542881
• 负责人: Wei Jiang
• 金额: --
• 依托单位: Stevens Institute of Technology
• 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: 2006-03-01 至 2009-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0542881&HistoricalAwards=false
• 关键词: CAREER; Data; Quality; Management; through

Data quality problem is of great importance due to the emergence of large volumes of data. Many business and industrial applications critically rely on the quality of information stored in diverse databases and data warehouses. The goal of this research project is to develop a systematic methodology of data quality analysis and improvement to achieve robust decision making under imperfect information environments. The project develops a unified framework for data quality assessment and evaluation, deliveries practical solutions to improve data quality through information production and management, and disseminates research findings by maintaining a website to increase the awareness of information quality among academic and industrial professionals. The approach consists of developing Bayesian network models to capture inter-relationships between data quality metrics, applying statistical sampling schemes and data mining methods for data quality assessment, and generalizing statistical techniques for root cause identification and data quality improvement. The techniques are evaluated and validated using synthetic examples and real-life cases from telecommunication and information technologies (IT) industries. The outcomes of the project are expected to be generic and provide a concrete basis of data quality management that can be applied to different data-intensive applications. The project will have broad impacts on advanced theory and methodology of information quality management, enhanced decision making, and the creation of a workforce of data quality assurance researchers and practitioners. Knowledge gained and results obtained from this research project will be broadly disseminated via Internet (http://www.stevens.edu/engineering/seem/Research/projects/DataQuality.html), in conferences, workshops, and various levels of courses.

数据质量问题由于出现了大量数据而非常重要。许多业务和工业应用程序非常依赖于存储在不同数据库和数据仓库中的信息的质量。该研究项目的目的是开发一种系统的数据质量分析和改进方法，以在不完美的信息环境下实现强大的决策。该项目为数据质量评估和评估开发了一个统一的框架，通过信息生产和管理提供实用解决方案，以提高数据质量，并通过维护网站来提高学术和工业专业人员的信息质量认识来传播研究结果。该方法包括开发贝叶斯网络模型，以捕获数据质量指标之间的相互关系，应用统计抽样方案和数据挖掘方法进行数据质量评估，并将统计技术概括为根本原因识别和数据质量改进。使用综合示例和现实生活中的电信和信息技术（IT）行业对技术进行评估和验证。该项目的结果有望是通用的，并提供了数据质量管理的具体基础，可以应用于不同的数据密集型应用程序。该项目将对信息质量管理，增强决策以及创建数据质量保证研究人员和从业者的劳动力的高级理论和方法产生广泛的影响。从该研究项目获得的知识和结果将通过Internet（http://www.stevens.edu/engineering/seem/Reseam/Reseam/project/projects/dataquality.html）广泛传播。