CAREER: Techniques and Applications of Derived Data Maintenance

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The goal of this research project is to develop efficient methods for maintaining derived data in database systems. The approach combines ideas that have been traditionally developed separately for different forms of derived data (e.g., caches, indexes, replicas, etc.) to develop new techniques for derived data maintenance, including (1) caching auxiliary data to improve database view maintenance, (2) optimizing update processing using characteristics of update streams, and (3) approximate view maintenance with bounded error. The research has a broad range of applications such as data warehousing, wide-area replication, and caching of dynamic data. Specifically, the results of this project will be applied to the development of an integrated dataspace for biomedical research and database replication tools for building scalable Web services, and generate practical impacts beyond the database field. This has broader impact on society in general. Further information on this project can be found on the web site http://www.cs.duke.edu/dbgroup/ddm/. The educational component of this project focuses on updating the database curriculum with three new courses at graduate and undergraduate levels, incorporating current research topics into teaching, attracting students with diverse academic and cultural backgrounds and helping them apply database skills to their fields of research or in their careers.