Design and Development of a Data Management System for Uncertain Data

不确定数据的数据管理系统的设计与开发

• 批准号: 0534702
• 负责人: Sunil Prabhakar
• 金额: --
• 依托单位: Purdue University
• 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: 2006-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0534702&HistoricalAwards=false
• 关键词: Design; Development; Data; Management; System

Current database management systems require all data to be modeled in terms of precise values. However, there is a large number of application domains where data values are imprecise or uncertain. Examples of such data include measurements for sensors, locations of moving objects, and experimental data. For these applications there is a need to develop a database management system that supports uncertain data types. The project aims to develop a comprehensive database management system for storing and querying uncertain, or imprecise data. The project encompasses the creation of a comprehensive model for uncertain data based upon the relational model, the extension of SQL to support probabilistic queries over uncertain data, techniques for efficient and accurate evaluation of probabilistic queries, and the development of a prototype system. The specific optimization issues addressed include indexing, join algorithms, and query optimization for uncertain data. The prototype will be developed as an extension of the open-source PostgreSQL database management system. A realistic moving objects' application is targeted for testing of the prototype. In addition, collaboration with experts in biology and chemistry will serve as validations of the applicability of the developments in these domains. The project is expected to have a significant impact on application domains that are in need of an uncertain data management system, and also on the database community. The proposal is expected to provide a single model for multiple types of uncertainty, and to develop indexing, join, and query optimization techniques for uncertain data. This project will integrate research and education through student participation in research projects, course development, and research seminar. The results from this research will be included in course projects and will be disseminated via peer-reviewed publications in journals and conferences, conference presentations, and the Web pages (http://wwww.cs.purdue.edu/homes/sunil/UncertainDB) that will also provide the prototype dissemination.

当前的数据库管理系统要求所有数据都按照精确值进行建模。然而，有大量的应用领域的数据值是不精确或不确定的。这种数据的示例包括传感器的测量、移动对象的位置和实验数据。对于这些应用程序，有必要开发一个数据库管理系统，支持不确定的数据类型。该项目旨在开发一个综合数据库管理系统，用于存储和查询不确定或不精确的数据。该项目包括创建一个全面的模型，不确定数据的关系模型的基础上，SQL的扩展，以支持概率查询不确定的数据，技术的有效和准确的评估概率查询，并开发一个原型系统。具体的优化问题包括索引，连接算法，查询优化不确定的数据。 该原型将作为开放源码PostgreSQL数据库管理系统的扩展开发。一个真实的移动物体的应用程序的目标是测试的原型。此外，与生物学和化学专家的合作将验证这些领域发展的适用性。 预计该项目将对需要不确定数据管理系统的应用领域以及数据库界产生重大影响。该提案有望为多种类型的不确定性提供一个单一的模型，并为不确定数据开发索引，连接和查询优化技术。该项目将通过学生参与研究项目，课程开发和研究研讨会来整合研究和教育。这项研究的结果将纳入课程项目，并将通过期刊和会议上的同行评审出版物、会议介绍和网页（http：//www.cs.purdue.edu/homes/sunil/UncertainDB）传播，这些网页也将提供原型传播。