Maintaining consistency of vague databases using data dependencies

Vague information is common in many database applications due to intensive data dissemination arising from different pervasive computing sources, such as the high volume data obtained from sensor networks and mobile communications. In this paper, we utilize functional dependencies (FDs) and inclusion dependencies (INDs), which are the most fundamental integrity constraints that arise in practice in relational databases, to maintain the consistency of a vague database. First, we tackle the problem, given a vague relation r and a set of FDs F , of how to obtain the “best” approximation of r with respect to F when taking into account the median membership (m) and the imprecision membership (i) thresholds. Using these two thresholds of a vague set, we define the notion of mioverlap between vague sets and a merge operation on r. Second, we consider, given a vague database d and a set of INDs N , how to obtain the minimal possible change in value precision for d. Satisfaction of an FD in r is defined in terms of values being mi-overlapping while satisfaction of an IND in d is defined in terms of value-precision. We show that Lien’s and Atzeni’s axiom system is sound and complete for FDs being satisfied in vague relations and that Casanova et al.’s axiom system is sound and complete for INDs being satisfied in vague databases. Finally, we study the chase procedure V Chase(d, F ∪N ) as a means to maintain consistency of d with respect to F and N . Our main result is that the output of the procedure is the most object-precise approximation of r with respect to F and the minimum value-precision change of d with respect to N . The complexity of V Chase(r, F ) is polynomial time in the sizes of r and F whereas the complexity of V Chase(d, F ∪ N ) is exponential.