Sequeira, AMM and O'Toole, M and Keates, TR and McDonnell, LH and Braun, CD and Hoenner, X and Jaine, FRA and Jonsen, ID and Newman, P and Pye, J and Bograd, SJ and Hays, GC and Hazen, EL and Holland, M and Tsontos, VM and Blight, C and Cagnacci, F and Davidson, SC and Dettki, H and Duarte, CM and Dunn, DC and Eguiluz, VM and Fedak, M and Gleiss, AC and Hammerschlag, N and Hindell, MA and Holland, K and Janekovic, I and McKinzie, MK and Muelbert, MMC and Pattiaratchi, C and Rutz, C and Sims, DW and Simmons, SE and Townsend, B and Whoriskey, F and Woodward, B and Costa, DP and Heupel, MR and McMahon, CR and Harcourt, R and Weise, M, A standardisation framework for bio-logging data to advance ecological research and conservation, Methods in Ecology and Evolution, 12, (6) pp. 996-1007. ISSN 2041-210X (2021) [Refereed Article]
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Copyright 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. https://creativecommons.org/licenses/by-nc/4.0/
- 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.
- 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.
- 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.
- 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.
|Item Type:||Refereed Article|
|Keywords:||bio-logging template, data accessibility and interoperability, data standards, metadata templates, movement ecology, sensors, telemetry, tracking|
|Research Division:||Environmental Sciences|
|Research Group:||Environmental management|
|Research Field:||Wildlife and habitat management|
|Objective Division:||Expanding Knowledge|
|Objective Group:||Expanding knowledge|
|Objective Field:||Expanding knowledge in the biological sciences|
|UTAS Author:||Hindell, MA (Professor Mark Hindell)|
|UTAS Author:||Muelbert, MMC (Dr Monica Muelbert)|
|UTAS Author:||Heupel, MR (Dr Michelle Heupel)|
|UTAS Author:||McMahon, CR (Dr Clive McMahon)|
|Web of Science® Times Cited:||21|
|Deposited By:||Ecology and Biodiversity|
|Downloads:||1 View Download Statistics|
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