Count Constraints for Inverse OLAP and Aggregate Data Exchange

A classical problem in database theory is to verify whether there exists a relation (or database) instance satisfying a number of given dependency constraints but the issue of handling constraints on aggregate data has not been much investigated so far. This paper introduces a new type of data dependency, called count constraint, that requires the results of given count operations on a relation to be within a certain range. Count constraints are defined by a suitable extension of first order predicate calculus, based on set terms, and they are then used in a new decisional problem, the Inverse OLAP: given a fact table, does there exist an instance satisfying a set of given count constraints? Count constraints can also be used into a data exchange system context, where data from the source database are transferred to the target database using aggregate operations.