Data-driven understanding and refinement of schema mappings

At the heart of many data-intensive applications is the problem of quickly and accurately transforming data into a new form. Database researchers have long advocated the use of declarative queries for this process. Yet tools for creating, managing and understanding the complex queries necessary for data transformation are still too primitive to permit widespread adoption o f this approach. We present a new framework that uses data examples as the basis for understanding and refining declarative schema mappings, We identi fy a small set of intuitive operators for manipulating examples. These oper ators permit a user to follow and refine an example by walking through a da ta source. We show that our operators are powerful enough both to identify a large class of schema mappings and to distinguish effectively between alt ernative schema mappings. These operators permit a user to quickly and intu itively build and refine complex data transformation queries that map one d ata source into another.