Abstract

Database systems are well suited to scientific data management and analysis workloads, however, a database must evolve to keep pace with changing requirements and adjust to changes in the domain conceptualization as applications mature. Evolving a database (i.e., updating its schema and instance data) is one of the greatest challenges in database maintenance and the difficulties are compounded by the lack of sufficient tools to support scientists. This paper presents a schema evolution framework based on an algebraic approach that introduces extended and higher-level composite relational operators tailored to the task of schema evolution. These higher-level operators simplify the task of evolving a database for non-expert users, while enabling efficient evaluation of schema evolution expressions.

Date

July 9, 2018

Authors

Robert E Schuler, Carl Kesselman

Book

Proceedings of the 30th International Conference on Scientific and Statistical Database Management

Pages

1-4