Raritas: a program for counting high diversity categorical data with highly unequal abundances

Area of Science:

• Biodiversity research
• Paleontology
• Data science

Background:

• Human observation is currently the primary method for collecting occurrence data in fields like biodiversity and paleontology.
• Existing computational tools for data recording are often inflexible and expensive, hindering research progress.

Purpose of the Study:

• To introduce Raritas, a novel, open-source software designed to overcome the limitations of current data acquisition methods.
• To enhance the collection of quantitative data, particularly for rare categories such as species, crucial for biodiversity surveys.
• To propose a standardized file format for storing geologic biodiversity data.

Main Methods:

• Development of Raritas as an open-source program written in Python.
• Compatibility as a standalone application for MacOS and Windows, and as customizable source code.
• Implementation of a dedicated rare category count mode within the software.
• Definition and proposal of the 'Stratigraphic occurrence data' file format.

Main Results:

• Raritas provides a flexible and cost-effective solution for data acquisition in biodiversity and paleontology.
• The rare category count mode facilitates more accurate and efficient data collection for rare species.
• The proposed 'Stratigraphic occurrence data' file format offers a standardized structure for geologic biodiversity data, including metadata.

Conclusions:

• Raritas offers a significant advancement in data collection tools for scientific research, particularly in biodiversity and paleontology.
• The software and proposed file format have the potential to improve data standardization and accessibility in these fields.