GSA Connects 2023 Meeting in Pittsburgh, Pennsylvania

Paper No. 108-5
Presentation Time: 8:00 AM-5:30 PM

PALAEOVERSE: A COMMUNITY-DRIVEN R PACKAGE TO SUPPORT PALEOBIOLOGICAL ANALYSIS


JONES, Lewis Alan1, GEARTY, William2, ALLEN, Bethany J.3, EICHENSEER, Kilian4, DEAN, Christopher D.5, GALVAN, Sofía1, GODOY, Pedro L.6, NICHOLL, Cecily7, DILLON, Erin8 and CHIARENZA, Alfio Alessandro1, (1)Departamento de Ecoloxía e Bioloxía Animal, Universidade de Vigo, Vigo, 36310, Spain, (2)American Museum of Natural History, 200 Central Park West, New York, NY 10024, (3)Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland, (4)Department of Earth Sciences, Durham University, Durham, United Kingdom, (5)UCL Earth Sciences, University College London, 5 Gower Place, London, WC1E 6BS, United Kingdom, (6)Institute of Biosciences, University of São Paulo, São Paulo, Brazil, (7)Earth Sciences, University College London, London, United Kingdom, (8)Smithsonian Tropical Research Institute, Panama City, NA, Panama

The open-source programming language ‘R' has become a standard tool in the paleobiologist's toolkit. Its popularity within the paleobiological community continues to grow, with published articles increasingly citing the usage of R and R packages. However, there are currently a lack of agreed standards for data preparation and available frameworks to support the implementation of such standards. Consequently, data preparation workflows are often unclear and not reproducible, even when code is provided. Moreover, due to a lack of code accessibility and documentation, paleobiologists are often forced to ‘reinvent the wheel’ to find solutions to issues already solved by other members of the community. Here, we introduce palaeoverse, a community-driven R package to aid data preparation and exploration for quantitative paleobiological research. The package is freely available and has three core principles: (1) streamline data preparation and analyses; (2) enhance code readability; and (3) improve reproducibility of results. To develop these aims, we assessed the analytical needs of the broader paleobiological community using an online survey, in addition to incorporating our own experiences. Here, we describe the functionality available in palaeoverse that was developed to meet the community's needs. palaeoverse is a community-driven R package for paleobiology, developed with the intention of bringing paleobiologists together to establish agreed standards for high-quality quantitative research. The package provides a user-friendly platform for preparing data for analysis with well-documented open-source code to enhance transparency. The functionality available in palaeoverse improves code reproducibility and accessibility, which is beneficial for both the review process and future research.