Research has deeply investigated several issues related to the use of
integrity constraints on relational databases. In particular, a great
deal of attention has been devoted to the problem of extracting reliable
information from databases containing pieces of information inconsistent
with regard to some integrity constraints. In this manuscript, the
problem of extracting consistent information from relational databases
violating integrity constraints on numerical data is addressed.
Aggregate constraints defined as linear inequalities on aggregate-sum
queries on input data are considered. The notion of repair as consistent
set of updates at attribute-value level is exploited, and the
characterization of several data-complexity issues related to repairing
data and computing consistent query answers is provided. Moreover, a
method for computing "reasonable" repairs of inconsistent numerical
databases is introduced, for a restricted but expressive class of
aggregate constraints. An extension of this method for dealing with the
data repairing problem in the presence of weak aggregate constraints
which are expected to be satisfied, but not required to, is presented.
Furthermore, a technique for computing consistent answers of aggregate
queries in the presence of a wide form of aggregate constraints is
provided. Finally, extensions of the framework as well as several open
problems are discussed.