A globally synthesised and flagged bee occurrence dataset and cleaning workflow - Dorey, James B.; Fischer, Erica E.; Chesshire, Paige R.; Nava-Bolaños, Angela; O’Reilly, Robert L.; Bossert, Silas; Collins, Shannon M.; Lichtenberg, Elinor M.; Tucker, Erika M.; Smith-Pardo, Allan; Falcon-Brindis, Armando; Guevara, Diego A.; et al. (Scientific data, 2023)
Species occurrence data are foundational for research, conservation, and science communication, but the limited availability and accessibility of reliable data represents a major obstacle, particularly for insects, which face mounting pressures. We present BeeBDC , a new R package, and a global bee occurrence dataset to address this issue. We combined >18.3 million bee occurrence records from multiple public repositories (GBIF, SCAN, iDigBio, USGS, ALA) and smaller datasets, then standardised, flagged, deduplicated, and cleaned the data using the reproducible BeeBDC R -workflow. Specifically, we harmonised species names (following established global taxonomy), country names, and collection dates and, we added record-level flags for a series of potential quality issues. These data are provided in two formats, “cleaned” and “flagged-but-uncleaned”. The BeeBDC package with online documentation provides end users the ability to modify filtering parameters to address their research questions. By publishing reproducible R workflows and globally cleaned datasets, we can increase the accessibility and reliability of downstream analyses. This workflow can be implemented for other taxa to support research and conservation.