In light of growing unencumbered public access to federated, online natural history collection data, the quality and validity of digitized specimen data must be more carefully evaluated than ever before. To this end, this project assessed the frequency at which museum specimens are erroneously identified and the extent to which these errors might impact specimen-based ecological study, using four closely related chipmunk species (Genus: Tamias) as a model group. Based on a combination of skull morphometrics, pelage, and locality, 5.6% of 1009 Tamias specimens investigated were found to be misidentified. These errors occurred largely when taxonomic revisions went unaccounted for in historic collections management, as well as when collectors mischaracterized specimens where species ranges overlap. Ecological niche models showed that verifying voucher specimen identity has observable impacts on predicted species’ distributions and that errors would tangibly affect ecological conclusions drawn from these specimens’ digital records. To mitigate these issues, natural history collections should prepare specimen using techniques that intentionally preserve species-specific diagnostic features (e.g., extracting and preserving small mammal genital bones); participate in active discourse with researchers to ensure that expert feedback is recorded and published to the collection’s public data set; and maintain and share longitudinal records of specimen identification determination history. Further, because small collections collectively preserve a substantive proportion of overall museum specimens, but have historically enjoyed less access to discipline-specific curatorial expertise, study findings highlight the need for on-going curatorial support to small collections and their inclusion in community knowledge-sharing initiatives, for example via Thematic Collections Networks.