A standardisation framework for bio-logging data to advance ecological research and conservation

Ana M. M. Sequeira*, Malcolm O'Toole, Theresa R. Keates, Laura H. McDonnell, Camrin D. Braun, Xavier Hoenner, Fabrice R. A. Jaine, Ian D. Jonsen, Peggy Newman, Jonathan Pye, Steven J. Bograd, Graeme C. Hays, Elliott L. Hazen, Melinda Holland, Vardis M. Tsontos, Clint Blight, Francesca Cagnacci, Sarah C. Davidson, Holger Dettki, Carlos M. DuarteDaniel C. Dunn, Victor M. Eguíluz, Michael Fedak, Adrian C. Gleiss, Neil Hammerschlag, Mark A. Hindell, Kim Holland, Ivica Janekovic, Megan K. McKinzie, Mônica M. C. Muelbert, Chari Pattiaratchi, Christian Rutz, David W. Sims, Samantha E. Simmons, Brendal Townsend, Frederick Whoriskey, Bill Woodward, Daniel P. Costa, Michelle R. Heupel, Clive R. McMahon, Rob Harcourt, Michael Weise

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
1 Downloads (Pure)

Abstract

1. Bio-logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio-logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio-logging data into research and management recommendations. 

2. We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy-of-use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security. 

3. We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. 

4. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter-governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio-logging data formats across all fields in animal ecology.

Original languageEnglish
Pages (from-to)996-1007
Number of pages12
JournalMethods in Ecology and Evolution
Volume12
Issue number6
DOIs
Publication statusPublished - Jun 2021

Bibliographical note

Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • bio-logging template
  • data accessibility and interoperability
  • data standards
  • metadata templates
  • movement ecology
  • sensors
  • telemetry
  • tracking

Fingerprint

Dive into the research topics of 'A standardisation framework for bio-logging data to advance ecological research and conservation'. Together they form a unique fingerprint.

Cite this