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Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs): An R package and workflow for processing biodiversity

Natalie N Patten^1,2, Michelle L Gaynor^3,4, Douglas E Soltis^3,4

¹Department of Mathematics University of Florida Gainesville 32611 Florida USA.

Applications in Plant Sciences

|April 19, 2024

Summary

This summary is machine-generated.

The new R package gatoRs simplifies accessing and cleaning biodiversity data from sources like GBIF and iDigBio. This tool makes biodiversity data processing more efficient for researchers and educators.

Keywords:

GBIF basis cleaning biodiversity data download herbaria iDigBio locality cleaning spatial correction taxonomic harmonization

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Area of Science:

Biodiversity informatics
Computational biology
Data science

Background:

Digitized biodiversity data are abundant but challenging to access and clean.
Data cleaning complexities include identifying and removing problematic records.

Purpose of the Study:

To introduce the R package gatoRs for streamlining biodiversity data acquisition and cleaning.
To provide a user-friendly tool for processing specimen records from major biodiversity databases.

Main Methods:

Developed the R package gatoRs with functions to download data from Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio).
Implemented functions for cleaning downloaded specimen records, accounting for structural differences between GBIF and iDigBio.
Included interactive cleaning steps for user control.

Main Results:

gatoRs offers a unified workflow for downloading and cleaning biodiversity data.
The package handles structural variations between GBIF and iDigBio data downloads.
Interactive cleaning options provide enhanced user control over data processing.

Conclusions:

The gatoRs package facilitates efficient processing of biodiversity data for the scientific community.
It is accessible to R coding novices and beneficial for both new and experienced users.
gatoRs can aid in teaching biodiversity concepts using herbarium specimen data.