In this paper, we develop a decision-theoretic framework for ordering candidate matches for user confirmation using the concept of the value of perfect information (VPI). At the core of this concept is a utility function that quantifies the desirability of a given state; thus, we devise a utility function for dataspaces based on query result quality. We show in practice how to efficiently apply VPI in concert with this utility function to order user confirmations. A detailed experimental evaluation shows that the ordering of user feedback produced by this VPI-based approach yields a dataspace with a significantly higher utility than a wide range of other ordering strategies. Finally, we outline the design of Roomba, a system that incorporates this decision-theoretic framework to guide a dataspace in soliciting user feedback in a pay-as-you-go manner.