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  • The package brings together several aspects of biodiversity data cleaning in one place. 'bdc' is organized in thematic modules related to different biodiversity dimensions, including: 1) Merge datasets: standardization and integration of different datasets; 2) Pre-filter: flagging and removal of invalid or non-interpretable information, followed by data amendments; 3) Taxonomy: cleaning, parsing, and harmonization of scientific names from several taxonomic groups against taxonomic databases locally stored through the application of exact and partial matching algorithms; 4) Space: flagging of erroneous, suspect, and low-precision geographic coordinates; and 5) Time: flagging and, whenever possible, correction of inconsistent collection date. In addition, it contains features to visualize, document, and report data quality – which is essential for making data quality assessment transparent and reproducible. The reference for the methodology is Bruno et al. (2022) https://doi.org/10.1111%2F2041-210X.13868