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. Duarte; Daniel 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

doi:10.1111/2041-210X.13593

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 journal › Article › peer-review

56 Citations (Scopus)

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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 language	English
Pages (from-to)	996-1007
Number of pages	12
Journal	Methods in Ecology and Evolution
Volume	12
Issue number	6
DOIs	https://doi.org/10.1111/2041-210X.13593
Publication status	Published - 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

Access to Document

10.1111/2041-210X.13593

Publisher version (open access)Final published version, 1.62 MBLicence: CC BY-NC

Cite this

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. M., Blight, C., Cagnacci, F., Davidson, S. C., Dettki, H., ... Weise, M. (2021). A standardisation framework for bio-logging data to advance ecological research and conservation. Methods in Ecology and Evolution, 12(6), 996-1007. https://doi.org/10.1111/2041-210X.13593

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title = "A standardisation framework for bio-logging data to advance ecological research and conservation",

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.",

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

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. ",

year = "2021",

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doi = "10.1111/2041-210X.13593",

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Sequeira, AMM, O'Toole, M, Keates, TR, McDonnell, LH, Braun, CD, Hoenner, X, Jaine, FRA, Jonsen, ID, Newman, P, Pye, J, Bograd, SJ, Hays, GC, Hazen, EL, Holland, M, Tsontos, VM, Blight, C, Cagnacci, F, Davidson, SC, Dettki, H, Duarte, CM, Dunn, DC, Eguíluz, VM, Fedak, M, Gleiss, AC, Hammerschlag, N, Hindell, MA, Holland, K, Janekovic, I, McKinzie, MK, Muelbert, MMC, Pattiaratchi, C, Rutz, C, Sims, DW, Simmons, SE, Townsend, B, Whoriskey, F, Woodward, B, Costa, DP, Heupel, MR, McMahon, CR, 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

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AU - O'Toole, Malcolm

AU - Keates, Theresa R.

AU - McDonnell, Laura H.

AU - Braun, Camrin D.

AU - Hoenner, Xavier

AU - Jaine, Fabrice R. A.

AU - Jonsen, Ian D.

AU - Newman, Peggy

AU - Pye, Jonathan

AU - Bograd, Steven J.

AU - Hays, Graeme C.

AU - Hazen, Elliott L.

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AU - Tsontos, Vardis M.

AU - Blight, Clint

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AU - Dunn, Daniel C.

AU - Eguíluz, Victor M.

AU - Fedak, Michael

AU - Gleiss, Adrian C.

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AU - Holland, Kim

AU - Janekovic, Ivica

AU - McKinzie, Megan K.

AU - Muelbert, Mônica M. C.

AU - Pattiaratchi, Chari

AU - Rutz, Christian

AU - Sims, David W.

AU - Simmons, Samantha E.

AU - Townsend, Brendal

AU - Whoriskey, Frederick

AU - Woodward, Bill

AU - Costa, Daniel P.

AU - Heupel, Michelle R.

AU - McMahon, Clive R.

AU - Harcourt, Rob

AU - Weise, Michael

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PY - 2021/6

Y1 - 2021/6

N2 - 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.

AB - 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.

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

Abstract

Bibliographical note

Keywords

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UWA led : Dynamically assess threats to marine megafauna in the face of global change

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

Abstract

Bibliographical note

Keywords

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UWA led : Dynamically assess threats to marine megafauna in the face of global change

Cite this