WildObs (WO)

IPT integration

If your data provider is an IPT instance, set the website URL to be the URL of the IPT endpoint.
e.g. http://data.canadensys.net/ipt

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Description

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The Wildlife Observatory of Australia (WildObs) is a national initiative transforming how Australia collects, processes, and shares data from wildlife camera traps. It brings together artificial intelligence, field monitoring standards, and open data infrastructure to create an end-to-end platform that supports large-scale biodiversity monitoring and ecological research. By streamlining the management of camera trap data?from image collection to analysis?WildObs aims to improve the consistency, accessibility, and scientific value of this rapidly growing data source.

A core part of this system is the tagged image repository hosted here by the Atlas of Living Australia (ALA). This curated dataset contains camera trap images that have been labelled with species identification and supporting metadata, such as location, date and time. The repository serves as a high-quality training and testing resource for researchers developing automated species recognition models using computer vision and machine learning. It also supports ecological studies that rely on verified image data, such as species occupancy modeling, behaviour analysis, and environmental reporting.

For example, a researcher investigating the spread of invasive predators can download a subset of validated fox and cat images to train a custom AI model tailored to local regions. Alternatively, conservation groups can use these tagged images to validate community-sourced identifications or build awareness of native species.

WildObs is made possible through a national collaboration of NCRIS-enabled infrastructure. TERN provides standardised field protocols and hosts the systematic survey data across Australian ecosystems. ALA hosts the tagged image dataset and occurrence records for public access and reuse. Australian Research Data Commons (ARDC) through QCIF is building the user-facing platform to support image upload, tagging, model training, and data sharing using advanced AI tools.

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Logo

Representative image

Location

Record consumers

These institutions and collections hold specimens related to the records sourced from this data provider.
Adding relationships here allows data processing to correctly attribute records down to the collection using collection codes and institution codes associated with the institution.

Attributions

External Identifiers