A standardisation framework for bio-logging data to advance ecological research and conservation
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Bio-logging data obtained by tagging animals is 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. This slows 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. 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: (i) decoded raw data, (ii) curated data, (iii) interpolated data, and (iv) 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. 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, providing data examples, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. 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.
Sequeira , A M M , O’Toole , M , Keates , T R , McDonnell , L H , Braun , C D , Hoenner , X , Jaine , F R A , Jonsen , I D , Newman , P , Pye , J , Bograd , S J , Hays , G C , Hazen , E L , Holland , M , Tsontos , V , Blight , C , Cagnacci , F , Davidson , S C , Dettki , H , Duarte , C M , Dunn , D C , Eguíluz , V M , Fedak , M , Gleiss , A C , Hammerschlag , N , Hindell , M A , Holland , K , Janekovic , I , McKinzie , M K , Muelbert , M M C , Pattiaratchi , C , Rutz , C , Sims , D W , Simmons , S E , Townsend , B , Whoriskey , F , Woodward , B , Costa , D P , Heupel , M R , McMahon , C R , Harcourt , R & Weise , M 2021 , ' A standardisation framework for bio-logging data to advance ecological research and conservation ' , Methods in Ecology and Evolution , vol. 12 , no. 6 , pp. 996-1007 . https://doi.org/10.1111/2041-210X.13593
Methods in Ecology and Evolution
Copyright © 2021 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.