Rapid and comprehensive data sharing is vital to the transparency and actionability of wildlife infectious disease research and surveillance. Unfortunately, most best practices for publicly sharing these data are focused on pathogen determination and genetic sequence data. Other facets of wildlife disease data – particularly negative results – are often withheld or, at best, summarized in a descriptive table with limited metadata. Here, we propose a minimum data and metadata reporting standard for wildlife disease studies. Our data standard identifies a set of 40 data fields (9 required) and 24 metadata fields (7 required) sufficient to standardize and document a dataset consisting of records disaggregated to the finest possible spatial, temporal, and taxonomic scale. We illustrate how this standard is applied to an example study, which documented a novel alphacoronavirus found in bats in Belize. Finally, we outline best practices for how data should be formatted for optimal re-use, and how researchers can navigate potential safety concerns around data sharing.

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A minimum data standard for wildlife disease research and surveillance

A minimum data standard for wildlife disease research and surveillance

This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.

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Authors

Tess Stevens, Ryan Zimmerman, Greg Albery, Daniel J Becker , Rebekah Kading, Carl N. Keiser, Shashank Khandelwal, Stephanie Kramer-Schadt, Raphael Krut-Landau, Clifton McKee, Diego Montecino-Latorre, Zoe O'Donoghue, Sarah H Olson, Timothée Poisot , Hailey Robertson, Sadie Jane Ryan, Stephanie Seifert, David Simons, Amanda Vicente-Santos, Chelsea Wood, Ellie Graeden, Colin J Carlson 

Abstract

Rapid and comprehensive data sharing is vital to the transparency and actionability of wildlife infectious disease research and surveillance. Unfortunately, most best practices for publicly sharing these data are focused on pathogen determination and genetic sequence data. Other facets of wildlife disease data – particularly negative results – are often withheld or, at best, summarized in a descriptive table with limited metadata. Here, we propose a minimum data and metadata reporting standard for wildlife disease studies. Our data standard identifies a set of 40 data fields (9 required) and 24 metadata fields (7 required) sufficient to standardize and document a dataset consisting of records disaggregated to the finest possible spatial, temporal, and taxonomic scale. We illustrate how this standard is applied to an example study, which documented a novel alphacoronavirus found in bats in Belize. Finally, we outline best practices for how data should be formatted for optimal re-use, and how researchers can navigate potential safety concerns around data sharing.

DOI

https://doi.org/10.32942/X2TW4J

Subjects

Animal Diseases, Biodiversity, Bioinformatics, Diseases, Ecology and Evolutionary Biology, Environmental Microbiology and Microbial Ecology Life Sciences, Life Sciences, Microbiology, Parasitic Diseases, Veterinary Infectious Diseases, Veterinary Medicine, Virology, Virus Diseases

Keywords

wildlife, One Health, surveillance, data science, open science

Dates

Published: 2024-05-19 13:43

Last Updated: 2025-04-23 11:59

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data and Code Availability Statement:
The example dataset and blank templates are available from Github. No code is used in this manuscript.

Language:
English