Core schema mappings: Scalable core computations in data exchange

Research has investigated mappings among data sources under two perspectives. On one side, there are studiesof practical tools for schema mapping generation; these focus on algorithms to generate mappings based on visualspecifications provided by users. On the other side, we have theoretical researches about data exchange. These studyhow to generate a solution – i.e., a target instance – given a set of mappings usually specified as tuple generatingdependencies. Since the notion of a core solution has been formally identified as an optimal solution, it is veryimportant to efficiently support core computations in mapping systems. In this paper we introduce several newalgorithms that contribute to bridge the gap between the practice of mapping generation and the theory of dataexchange. We show how, given a mapping scenario, it is possible to generate an executable script that computescore solutions for the corresponding data exchange problem. The algorithms have been implemented and tested usingcommon runtime engines to show that they guarantee very good performances, orders of magnitudes better than thoseof known algorithms that compute the core as a post-processing step.