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

Sequeira, AMM; O'Toole, M; Keates, TR; McDonnell, LH; Braun, CD; Hoenner, X; Jaine, FRA; Jonsen, ID; Newman, P; Sims, DW et al. 2021 A standardisation framework for bio-logging data to advance ecological research and conservation. Methods in Ecology and Evolution, 12. 996-1007. https://doi.org/10.1111/2041-210X.13593

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Abstract/Summary

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 intergovernmental 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.

Item Type: Publication - Article
Subjects: Marine Sciences
Divisions: Marine Biological Association of the UK > Ecosystems and Environmental Change > Movement ecology, behaviour and population structure
Depositing User: Emily Smart
Date made live: 20 Aug 2021 11:05
Last Modified: 20 Aug 2021 11:05
URI: http://plymsea.ac.uk/id/eprint/9318

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