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While there has been significant focus on collecting and managing data feeds, it is only now that attention is turning to their quality. In this paper, we propose a principled approach to online data quality monitoring in a dynamic feed environment. Our goal is to alert quickly when feed behavior deviates from expectations. We make contributions in two distinct directions. First, we propose novel enhancements to the DFMS architecture to permit a publish-subscribe approach to incorporate datadoi:10.14778/2824032.2824070 fatcat:5stn34alg5fizcfotd2zjl5fxy