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 BeeDC, a new R package, and a global bee occurrence dataset to address this issue. We combined >17.7 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 BeeDC R-workflow. Specifically, we harmonised species names following established global taxonomy, country, and collection date and we added record-level flags for a series of potential quality issues. These data are provided in two formats, “completely-cleaned” and “flagged-but-uncleaned”. Our data cleaning process is open and documented for transparency and reproducibility. The BeeDC package and R Markdown are provided, and will be improved and updated regularly. 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.