Schema Evolution publication categorizer

Schema mappings are high-level specifications that describe the relationship between two database schemas. They are an important tool in several areas of database research, notably in data integration and data exchange. However, a concrete theory of schema mapping optimization including the formulation of optimality criteria
and the construction of algorithms for computing optimal schema mappings is completely lacking to date. The goal of this work is to fill this gap. We start by presenting a system of rewrite rules to minimize sets of source-to-target tuple-generating dependencies (st-tgds, for short). Moreover, we show that the result of this minimization is unique up to variable renaming. Hence, our optimization also yields a schema mapping normalization. By appropriately
extending our rewrite rule system, we also provide a normalization of schema mappings containing equality-generating targetdependencies (egds). An important application of such a normalization is in the area of defining the semantics of query answering in data exchange, since several definitions in this area depend on the concrete syntactic representation of the st-tgds. This is, in particular, the case for queries with negated atoms and for aggregate
queries. The normalization of schema mappings allows us to eliminate the effect of the concrete syntactic representation of the st-tgds from the semantics of query answering. We discuss in detail how our results can be fruitfully applied to aggregate queries.