A graded approach to database repair by context-aware distance semantics

The problem of inconsistent information in databases often arises in the context of data integration and data exchange. In these areas the common assumption is that the real world is consistent, thus an inconsistent database does not correspond to any reliable state and it needs to be "repaired" according to a chosen policy. Many of these policies have to deal with the problem of an exponential blowup in the number of possible repairs. For this reason, recent approaches advocate more flexible and fine-grained policies based on the user's preference. In this paper we take a further step towards more personalized inconsistency management by incorporating ideas from context-aware systems. The idea is to employ grades of different repairs according to their relevance for a particular user. The outcome is a graded framework for inconsistency maintenance in database systems, controlled by context-aware and distance-based considerations.