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Metadata produced by members of a diverse community of peers tend to contain low-quality or even mutually inconsistent assertions. Trust values computed on the basis of users' feedback can improve metadata quality and reduce inconsistency, eliminating untrustworthy assertions. In this paper, we describe an approach to metadata creation and improvement, where community members express their opinions on the trustworthiness of each assertion. Our technique aggregates individual trustworthiness values to obtain a community-wide assessment of each assertion. We then apply a global trustworthiness threshold to eliminate some assertions to reduce the metadatabase's overall inconsistency.