bdc
Biodiversity Data Cleaning
It 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) doi:10.1111/2041-210X.13868.
- Version1.1.4
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Languageen-gb
- Last release03/13/2023
Documentation
Team
Bruno Ribeiro
Santiago Velazco
Karlo Guidoni-Martins
Geiziane Tessarolo
Lucas Jardim
Steven Bachman
Rafael Loyola
Insights
Last 30 days
This package has been downloaded 512 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 15 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 5,219 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Dec 20, 2024 with 47 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports20 packages
- Suggests19 packages
- Reverse Suggests1 package