Data

Synthetic data for reef modelling

Australian Institute of Marine Science
Australian Institute of Marine Science (AIMS)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://apps.aims.gov.au/metadata/view/b678c7e9-e419-4ec8-8b67-fcf0f15f6c09&rft.title=Synthetic data for reef modelling&rft.identifier=https://apps.aims.gov.au/metadata/view/b678c7e9-e419-4ec8-8b67-fcf0f15f6c09&rft.publisher=Australian Institute of Marine Science (AIMS)&rft.description=Synthetic data can be used to support model analyses that can be published without referring to specific sites, reefs, or study areas. Here a synthetic data pipeline has been developed for the reef decision-support system ADRIA (Adaptive Dynamic Reef Intervention Algorithms). This pipeline includes developing models for tabular (benthic/compositional reef data), spatial-temporal (wave and heat stress data) and spatial network data (coral larval connectivity). Conditional sampling methods which connect spatial relationships across datasets are used to develop synthetic reef data packages which mimic the statistical properties of the original dataset.See Crocker et al (2024) for full details.Maintenance and Update Frequency: notPlanned&rft.creator=Australian Institute of Marine Science (AIMS) &rft.date=2026&rft.coverage=westlimit=146.14185333251956; southlimit=-16.978323208308048; eastlimit=146.32930755615237; northlimit=-16.75030415272027&rft.coverage=westlimit=146.14185333251956; southlimit=-16.978323208308048; eastlimit=146.32930755615237; northlimit=-16.75030415272027&rft_rights=Creative Commons Attribution 3.0 Australia License http://creativecommons.org/licenses/by/3.0/au/&rft_rights=Use Limitation: All AIMS data, products and services are provided as is and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.&rft_rights=Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: Australian Institute of Marine Science (AIMS). (2024). Synthetic data for reef modelling. https://apps.aims.gov.au/metadata/view/b678c7e9-e419-4ec8-8b67-fcf0f15f6c09, accessed[date-of-access].&rft_subject=oceans&rft.type=dataset&rft.language=English Access the data
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Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 3.0 Australia License
http://creativecommons.org/licenses/by/3.0/au/

Use Limitation: All AIMS data, products and services are provided "as is" and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.

Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: "Australian Institute of Marine Science (AIMS). (2024). Synthetic data for reef modelling. https://apps.aims.gov.au/metadata/view/b678c7e9-e419-4ec8-8b67-fcf0f15f6c09, accessed[date-of-access]".

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Full description

Synthetic data can be used to support model analyses that can be published without referring to specific sites, reefs, or study areas. Here a synthetic data pipeline has been developed for the reef decision-support system ADRIA (Adaptive Dynamic Reef Intervention Algorithms). This pipeline includes developing models for tabular (benthic/compositional reef data), spatial-temporal (wave and heat stress data) and spatial network data (coral larval connectivity). Conditional sampling methods which connect spatial relationships across datasets are used to develop synthetic reef data packages which mimic the statistical properties of the original dataset.


See Crocker et al (2024) for full details.

Lineage

Maintenance and Update Frequency: notPlanned

Notes

Credit
Crocker, R. Australian Institute of Marine Science (AIMS)
Credit
Robson, B J. (AIMS)
Credit
Ani, C. (AIMS)
Credit
Anthony, K. (AIMS)
Credit
Iwanaga, T. (AIMS)

Modified: 06 11 2026

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146.14185,-16.97832 146.32931,-16.97832 146.32931,-16.7503 146.14185,-16.7503 146.14185,-16.97832

146.23558044433,-16.864313680514

text: westlimit=146.14185333251956; southlimit=-16.978323208308048; eastlimit=146.32930755615237; northlimit=-16.75030415272027

Subjects
oceans |

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Other Information
Crocker, R., Robson, B. J., Ani, C., Anthony, K., & Iwanaga, T. (2024). Synthetic data for reef modelling. Ecological Informatics, 82, 102698. https://doi.org/10.1016/j.ecoinf.2024.102698

doi : https://doi.org/10.1016/j.ecoinf.2024.102698

GitHub Code repository for the creation of synthetic input data layers for ADRIA.

url : https://github.com/open-AIMS/ADRIA-synthetic-data/tree/v0.1.0

open-AIMS/ADRIA-synthetic-data: v0.1.0 (v0.1.0). Zenodo. https://doi.org/10.5281/zenodo.10158324

doi : https://doi.org/10.5281/zenodo.10158324

Identifiers
  • global : b678c7e9-e419-4ec8-8b67-fcf0f15f6c09
ACN 633 798 857