A minimum data standard for wildlife disease research and surveillance

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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Publication Details

Journal
Scientific Data
Published
2025-06-21
DOI
https://doi.org/10.1038/s41597-025-05332-x
Citations
7
Primary Topic
Zoonotic diseases and public health
Type
article
Field-Weighted Citation Impact
11.27

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article

A minimum data standard for wildlife disease research and surveillance

Daniel J. Becker, Clifton McKee, Rebekah C. Kading, Cole B. Brookson et al.
7 citations
Scientific Data
Zoonotic diseases and public health
11.27
article

A minimum data standard for wildlife disease research and surveillance

Daniel J. Becker, Clifton McKee, Rebekah C. Kading, Cole B. Brookson, Colin J. Carlson, Collin Schwantes, Gregory F. Albery, M O'Shea, Stephanie N. Seifert, Ellie Graeden, Zoe O’Donoghue, Ryan D. Zimmerman, Sadie J. Ryan, Tess Stevens, Chelsea L. Wood, Timothée Poisot, Sarah H. Olson, Hailey Robertson, Carl N. Keiser, Amanda Vicente‐Santos, Stephanie Kramer‐Schadt, Cecilia A. Sánchez, Diego Montecino‐Latorre, Raphael Krut-Landau, Shashank Khandelwal, Dávid Simons
article en
7 citations

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.

Scientific DataVol. 12(1)
Tulane University (US), Pennsylvania State University (US), Wildlife Conservation Society (US), Johns Hopkins University (US), Georgetown University (US), University of Washington (US), Yale University (US), University of Florida (US), Center for Global Health (US), Leibniz Institute for Zoo and Wildlife Research (DE), Université de Montréal (CA), Washington State University (US), University of Oklahoma (US), Titanium Metals Corporation (United Kingdom) (GB), Colorado State University (US)
National Science Foundation
Openalex Percentile: Top 1%
Zoonotic diseases and public health
11.27
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