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Full description
The IMOS Understanding of Marine Imagery Sub-Facility provides a national repository for marine imagery and annotations, facilitating the sharing of quantitative data on species and habitat distributions. Squidle+ serves as the foundational software platform for this sub-facility, providing an end-to-end environment for the delivery, management, and annotation of marine imagery.The platform integrates disparate data sources, including autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs), baited remote underwater videos (BRUVs), towed systems, and diver-based photo quadrats (e.g., Reef Life Survey (RLS)), by standardising formats and enabling cross-walks between different label vocabularies. This ensures unified datasets that can be synthesised at a national scale across diverse research projects.
This specific product aggregates kelp-related annotations from public Squidle+ surveys, translated into the Darwin Core standard for enhanced interoperability. Data are filtered via a curated allow-list, taxonomically aligned with the World Register of Marine Species (WoRMS, https://www.marinespecies.org/about.php#what_is_worms), and normalised temporally and spatially using a H3 index. Australian Marine Region Tags have also been added which allows spatial filtering of the data based on known marine regions (for example, commonwealth marine regions).The resulting analysis-ready resource supports the study of canopy-forming macroalgae and benthic habitat structure across Australian waters.
The allow-list targets canopy-forming and habitat-forming macroalgae from the phylum Ochrophyta, class Phaeophyceae, with particular emphasis on the orders Laminariales and Fucales. Key taxa represented include Ecklonia radiata, Phyllospora comosa, Macrocystis pyrifera, Durvillaea spp., Cystophora spp., Scytothalia dorycarpa, Lessonia corrugata and Perithalia caudata, among others. The geographic occurrence coverage spans the temperate and subtropical coastal waters of southern and eastern Australia, from approximately 113°E to 153°E and 44°S to 27°S, encompassing the major kelp forest ecosystems of the Great Southern Reef, the south-east Australian coast and the eastern seaboard.
Lineage
Maintenance and Update Frequency: monthly
Statement: Data Ingestion Workflow
The Kelp Squidle+ Annotations Data Product is produced using a standard Extract–Transform–Load (ETL) workflow designed to convert kelp‑related image annotations from the Squidle+ marine imagery platform into a harmonised, Darwin Core–compliant dataset. The workflow provides reproducible, consistent access to annotated kelp observations for scientific analysis.
Data Extraction
Source data consist of public annotation sets hosted on the Squidle+ platform. Because Squidle+ allows users to employ their own controlled vocabularies, kelp labels are not always consistent over time. To ensure specificity, an explicit Kelp Label Allow List is applied to identify and select only annotation sets containing kelp‑related labels.
For each selected annotation set, the pipeline retrieves:
• Raw annotation records
• Associated label scheme vocabularies
• Relevant WoRMS taxonomic information used during translation
These are accessed programmatically through the Squidle+ REST API.
Filtering and Cleaning
A multi‑step filtering process ensures only high‑quality, kelp‑specific data enter the transformation stage:
• Kelp pruning: Only annotations matching the allow‑listed kelp labels are retained.
• Media conflict resolution: Because Squidle+ supports multiple annotation layers on the same image, media containing conflicting label sets are excluded to preserve data integrity.
• Temporal and spatial filtering: Only records occurring on or after 28 September 2007 are retained, and observations are restricted to the Australian region.
This cleaning stage ensures that only valid, high‑confidence kelp occurrences proceed to standardisation.
Darwin Core Translation
The transformation step maps Squidle+ annotation fields to the global Darwin Core standard to ensure interoperability with marine biodiversity infrastructures such as OBIS. Key operations include:
• Taxonomic alignment: Local Squidle+ label IDs are joined with authoritative WoRMS taxonomic entries, providing standardised scientific names, LSIDs (scientificNameID), and full taxonomic hierarchy.
• Identifier generation: Each observation receives a unique occurrenceID derived from its annotation ID and deployment ID.
• Temporal normalisation: Annotation timestamps are parsed and converted to ISO‑compatible eventDate values (UTC).
• Spatial normalisation: Latitude/longitude fields are standardised to Darwin Core decimalLatitude and decimalLongitude.
• Standardised occurrence metadata:
o basisOfRecord = MachineObservation (photograph‑based detection)
o occurrenceStatus = present (all annotations represent confirmed occurrences)
• Media linkage: Each record includes a resolvable Squidle+ media URL for visual verification through an API‑generated iframe link.
This translation stage produces fully standardised, taxonomically verified occurrence records.
Validation
The transformed observations are validated against the expected output schema. Nullability constraints, temporal formats, coordinate validity, and taxonomic mappings are checked to ensure consistency. The final validated dataset is exported as a PyArrow table prior to loading.
Load and Publication
The final harmonised dataset is written to cloud storage in Parquet format.
This provides substantial efficiency benefits: the processed dataset is reduced to approximately 2 MB, enabling fast access and low‑cost storage, and supporting scheduled automated updates.
Update Schedule
Squidle+ is a public marine media annotation platform. The ETL pipeline is executed once per month, to capture additional surveys as they are published in Squidle+.
Advantages of the Workflow
• Reproducible: Automates the otherwise complex extraction of Squidle+ annotations, which typically requires familiarity with REST APIs and the Squidle+ relational schema.
• Interoperable: Converts bespoke Squidle+ labels into Darwin Core standard, enabling integration with global biodiversity systems such as OBIS.
• Space‑ and time‑efficient: Highly compressed Parquet outputs and scheduled refreshes ensure up‑to‑date data availability with minimal overhead.
• Cloud‑ready: The workflow supports cloud‑native ETL operations and reduces I/O costs.
Statement: Source data Workflow
For information relating to
- image submission to Squidle+: https://squidle.org/wiki/general_information/datasources_and_ingesting_from_cloud_repositories
- annotations in Squidle+: https://squidle.org/wiki/instructions_and_tutorials/annotate_media
See Friedman A, Monk J, Pizarro O, Lindsay D, Oh E, Thornton B, Carroll A, Przeslawski R and Williams S (2026) Squidle+: a collaborative platform to manage, discover and annotate marine imagery. Front. Mar. Sci. 12:1677103. doi: 10.3389/fmars.2025.1677103
For provenance information for annotations see:
Media linkage: Each record includes a resolvable Squidle+ media URL for visual verification through an API‑generated iframe link.
Note - there is a planned improvement to provide an aggregated link (covering image and annotation details)
Notes
CreditAustralia’s Integrated Marine Observing System (IMOS) is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). It is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent.
Credit
The dataset collection described in this record was funded by the Australian Government Department of Climate Change, the Environment, Energy & Water (DCCEEW) through the NESP Marine and Coastal Hub. In addition to NESP (DCCEEW) funding, this project was supported by an equivalent amount of in-kind support and co-investment from project partners and collaborators.
The dataset collection described in this record was funded by the Australian Government Department of Climate Change, the Environment, Energy & Water (DCCEEW) through the NESP Marine and Coastal Hub. In addition to NESP (DCCEEW) funding, this project was supported by an equivalent amount of in-kind support and co-investment from project partners and collaborators.
Credit
This dataset collection forms part of the NESP MaC Project 5.9 – Making marine environmental data more assessment ready, 2025 (UTAS, IMOS)
This dataset collection forms part of the NESP MaC Project 5.9 – Making marine environmental data more assessment ready, 2025 (UTAS, IMOS)
Credit
Source data provided to Squidle+ by numerous imagery contributors and individual annotators
Source data provided to Squidle+ by numerous imagery contributors and individual annotators
Credit
Reef Life Survey and Australian Temperate Reef Collaboration partners
Reef Life Survey and Australian Temperate Reef Collaboration partners
Issued: 26 02 2026
text: westlimit=113.39; southlimit=-43.72; eastlimit=153.48; northlimit=-27.13
Subjects
Abundance of biota |
Autonomous Underwater Vehicles Sub-Facility, Integrated Marine Observing System (IMOS) |
BATHYMETRY/SEAFLOOR TOPOGRAPHY |
BENTHIC |
BIOLOGICAL CLASSIFICATION |
BROWN ALGAE |
Baited remote underwater video (BRUV) |
Biotic taxonomic identification |
COASTAL |
COASTAL BATHYMETRY |
COASTAL PROCESSES |
CORAL REEF |
Carpoglossum |
Carpoglossum confluens |
Caulocystis |
Countries | Australia |
Cystophora |
Durvillaea potatorum |
ECOLOGICAL DYNAMICS |
Ecklonia radiata |
GRAZING DYNAMICS / PLANT ECOLOGY |
Global / Oceans | Indian Ocean |
Global / Oceans | Pacific Ocean |
Global / Oceans | Southern Ocean |
IMAGE PROCESSING |
KELP FOREST |
Laminariaceae |
Lessonia corrugata |
MACROALGAE (SEAWEEDS) |
MARINE |
MARINE ECOSYSTEMS |
Macrocystis pyrifera |
Marine Features (Australia) | Bass Strait, TAS/VIC |
Marine Features (Australia) | Great Australian Bight, SA/WA |
Marine Imagery Sub-Facility, Integrated Marine Observing System (IMOS) |
National Reef Monitoring Network Sub-Facility, Integrated Marine Observing System (IMOS) |
Offshore Islands (Australia) | Macquarie Island |
Perithalia caudata |
Phaeophyceae |
Phyllospora comosa |
Regional Seas | Coral Sea |
Regional Seas | Tasman Sea |
Sargassum |
Scaberia agardhii |
Scytothalia dorycarpa |
Seirococcus axillaris |
States, Territories (Australia) | New South Wales |
States, Territories (Australia) | Queensland |
States, Territories (Australia) | South Australia |
States, Territories (Australia) | Tasmania |
States, Territories (Australia) | Victoria |
States, Territories (Australia) | Western Australia |
Xiphophora |
Xiphophora gladiata |
biota |
diver |
environment |
geoscientificInformation |
oceans |
propelled unmanned submersible |
towed unmanned submersible |
unmanned autonomous underwater vehicle |
User Contributed Tags
Login to tag this record with meaningful keywords to make it easier to discover
Other Information
(Understanding of Marine Imagery page on IMOS website)
url :
https://imos.org.au/facilities/facilities/understanding-marine-imagery
(Explore, annotate and download data through Squidle+ website (source of annotations))
url :
https://squidle.org/
(Squidle+ paper in Frontiers in Marine Science)
doi :
https://doi.org/10.3389/fmars.2025.1677103
(View and download data though the AODN Portal)
url :
https://portal.aodn.org.au/search?uuid=20be281d-dfb2-4868-b690-c889a23b5714
(Access To AWS Open Data Program registry for the Cloud Optimised version of this dataset (link to be added))
url :
https://registry.opendata.aws/
(Data files via Amazon Web Services S3 storage - download link (full dataset))
url :
https://data-uplift-public.s3.ap-southeast-2.amazonaws.com/stored/datauplift/kelp/kelp.parquet
(Data files accessible via Amazon S3 (public access, S3 URI))
local : s3://data-uplift-public/stored/datauplift/kelp/kelp.parquet
(Access to Jupyter notebook to query Cloud Optimised converted dataset (link to be added))
url :
https://github.com/aodn/aodn_cloud_optimised/blob/main/notebooks/
(Technical description of product)
url :
https://content.aodn.org.au/Documents/IMOS/Data_product/Kelp_v1.0.pdf
global : af5d0ff9-bb9c-4b7c-a63c-854a630b6984
global : aeb0afce-7fc7-4d48-91fc-f7b8e730073c
local : 010x3gp67
local : 010x3gp67
local : 02czsnj07
local : 0000-0002-1874-0619
local : 0000-0003-3529-1031
NESP MaC Project 5.9 – Making marine environmental data more assessment ready, 2025 (UTAS, IMOS)
doi :
10.82210/a44c9c1d
Identifiers
- global : 20be281d-dfb2-4868-b690-c889a23b5714
