CAREER: Evolving Heterogeneous Autonomous Databases

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The heterogeneous, autonomous, and highly dynamic nature of databases on the Web renders most traditional data management techniques ineffective. Consequently, keeping abreast of relevant information as it evolves in this environment requires a large amount of human effort. The goal of this research is to develop, implement, and evaluate methods for data management in a heterogeneous, autonomous, and dynamic environment. The history of changes made to data is the major focus of this project. Methods for efficiently discovering, storing, browsing, and querying changes are developed. In sharp contrast to traditional database techniques, these methods try to make the best possible use of the structure in data without requiring data to conform to a fixed structure or schema. The educational component includes redesigning the current database curriculum; development of new courses on XML, related Web technologies, and semistructured data; and experimenting with pedagogical tools such as teaching by program dissection (the use of the source code of a large program as an anchor for studying related topics). In addition to graduate students, undergraduate students are involved in research by working on the system prototype, which in turn benefits from their efforts. In summary, this research will bring the benefits of database technology (e.g., faster, easier, and more precise information access) to the Web by developing methods that cope with the heterogeneous, autonomous, and dynamic nature of Web databases. http://www.cs.umd.edu/~chaw/