AuthorBledsoe, Ellen K
Burant, Joseph B
Higino, Gracielle T
Roche, Dominique G
Binning, Sandra A
Pollock, Laura S
Sunday, Jennifer M
Srivastava, Diane S
AffiliationSchool of Natural Resources and the Environment, University of Arizona
long-term ecological data
MetadataShow full item record
PublisherRoyal Society Publishing
CitationBledsoe, E. K., Burant, J. B., Higino, G. T., Roche, D. G., Binning, S. A., Finlay, K., Pither, J., Pollock, L. S., Sunday, J. M., & Srivastava, D. S. (2022). Data rescue: Saving environmental data from extinction. Proceedings of the Royal Society B: Biological Sciences, 289(1979), 20220938.
Rights© 2022 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractHistorical and long-term environmental datasets are imperative to understanding how natural systems respond to our changing world. Although immensely valuable, these data are at risk of being lost unless actively curated and archived in data repositories. The practice of data rescue, which we define as identifying, preserving, and sharing valuable data and associated metadata at risk of loss, is an important means of ensuring the long-term viability and accessibility of such datasets. Improvements in policies and best practices around data management will hopefully limit future need for data rescue; these changes, however, do not apply retroactively. While rescuing data is not new, the term lacks formal definition, is often conflated with other terms (i.e. data reuse), and lacks general recommendations. Here, we outline seven key guidelines for effective rescue of historically collected and unmanaged datasets. We discuss prioritization of datasets to rescue, forming effective data rescue teams, preparing the data and associated metadata, and archiving and sharing the rescued materials. In an era of rapid environmental change, the best policy solutions will require evidence from both contemporary and historical sources. It is, therefore, imperative that we identify and preserve valuable, at-risk environmental data before they are lost to science.
NoteOpen access article
VersionFinal published version
Except where otherwise noted, this item's license is described as © 2022 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/.
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