Managing Database-Application Co-Evolution in a Scientific Data Ecosystem

Scientific databases used for organizing, archiving, collaborating and sharing research data depend on a well-defined schema to accurately reflect the scientific domain and on database-driven applications for supporting key user interactions with the database. Applications that interact with a database typically depend on some form of schema mappings, such as object-relational mappings, to inform the application of how to query and manipulate the database. The presence of schema mappings, however, further exacerbates the already difficult task of evolving the database schema. Database migration utilities provide some help by coordinating schema evolution scripts with application code changes, but only automate the simplest schema mapping changes. In this paper, we present an approach to coupled database-application evolution by extending a database evolution language with model management operations. We introduce a novel set of model management operations and define their semantics and then describe how they may be integrated into schema modification operators. We then present an evaluation of the concepts from real-world usage of model mappings in scientific database deployments.