Data

Australian Acoustic Observatory (A2O) data portal

Queensland University of Technology

Roe, Paul ; Truskinger, Anthony ; Vella, Kellie ; QUT Ecoacoustics

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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25912/RDF_1680244358806&rft.title=Australian Acoustic Observatory (A2O) data portal&rft.identifier=10.25912/RDF_1680244358806&rft.publisher=Queensland University of Technology&rft.description=The Australian Acoustic Observatory (A2O) provides data for hundreds of acoustic sensors across seven Australian ecoregions. The A2O data include acoustic recordings collected by site sensors as well as site information, such as vegetation cover, landform and disturbance. The A2O is a network to monitor biodiversity, which includes the collection and processing of large volumes of high-resolution data over time using a distributed sensor network. These data are stored on the cloud and made available to researchers, citizen scientists, and the general public. The data is freely available for use under a Creative Commons license, Attribution 4.0 International Licence. If you wish to use this data, you will need to follow the licence terms and the which specify how to provide the attribution required under the licence. &rft.creator=Roe, Paul &rft.creator=Truskinger, Anthony &rft.creator=Vella, Kellie &rft.creator=QUT Ecoacoustics &rft.date=2023&rft.edition=1&rft.coverage=109.799621,-10.403629 156.733215,-10.403629 156.733215,-45.523347 109.799621,-45.523347 109.799621,-10.403629&rft_rights=© Queensland University of Technology, 2023&rft_rights=Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/4.0/&rft_subject=Ecology&rft_subject=Information systems&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft_subject=Pattern recognition and data mining&rft_subject=Acoustics recordings&rft_subject=Bioacoustics&rft_subject=Biological sciences&rft_subject=Environmental monitoring&rft_subject=Ecological applications&rft_subject=Fauna vocalisation&rft_subject=Ecological acoustic monitoring systems&rft_subject=Other information and computing sciences&rft_subject=Biogeoscience&rft_subject=Computer science&rft_subject=Distributed computing and systems software&rft_subject=Ecoacoustics&rft.type=dataset&rft.language=English Access the data

https://www.qut.edu.au... http://researchdatafin... https://data.acoustico...

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Licence & Rights:

Open Licence view details

CC-BY

Creative Commons Attribution 3.0
http://creativecommons.org/licenses/by/4.0/

© Queensland University of Technology, 2023

Access:

Other view details

Access to the data is via the A20 data portal - See https://acousticobservatory.org/data/find-data/

Contact Information

Postal Address:
Professor Paul Roe

p.roe@qut.edu.au

Full description

The Australian Acoustic Observatory (A2O) provides data for hundreds of acoustic sensors across seven Australian ecoregions. The A2O data include acoustic recordings collected by site sensors as well as site information, such as vegetation cover, landform and disturbance.

The A2O is a network to monitor biodiversity, which includes the collection and processing of large volumes of high-resolution data over time using a distributed sensor network. These data are stored on the cloud and made available to researchers, citizen scientists, and the general public.

The data is freely available for use under a Creative Commons license, Attribution 4.0 International Licence. If you wish to use this data, you will need to follow the licence terms and the which specify how to provide the attribution required under the licence.

This dataset is part of a larger collection

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Subjects

Acoustics recordings | Bioacoustics | Biogeoscience | Biological sciences | Computer science | Distributed Computing and Systems Software | Ecoacoustics | Ecological acoustic monitoring systems | Ecological applications | Ecology | Environmental monitoring | Fauna vocalisation | Information and Computing Sciences | Information Systems | Other Information and Computing Sciences | Pattern recognition and data mining |

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Identifiers

DOI : 10.25912/RDF_1680244358806
Local : 10378.3/8085/1018.17521

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