Aggregates in generalized temporally indeterminate databases

Dyreson and Snodgrass as well as Dekhtyar et. al. have provided a probabilistic model (as well as compelling exam-ple applications) for why there may be temporal indetermi-nacy in databases. In this paper, we rst propose a formal model for aggregate computation in such databases when there is uncertainty not just in the temporal attribute, but also in the ordinary (non-temporal) attributes. We identify two types of aggregates: event correlated aggregates, and non event correlated aggregations, and provide efcient al-gorithms for both of them. We prove that our algorithms are correct, and we present experimental results showing that the algorithms work well in practice.