Most of our work has resulted in scholarly publications. On this page you can review our publications to get an idea about our work.
Liquor and gaming licences, South Australia, September 2018
September, 2018 • Dataset
Attorney-General's Department
Every liquor licence in South Australia in September 2018 with its premises, status and issue date, and the gaming machine licence and number of machines where the premises held one. Closed snapshot.T…
Every liquor licence in South Australia in September 2018 with its premises, status and issue date, and the gaming machine licence and number of machines where the premises held one. Closed snapshot.This is the 2018-09-04 version of this dataset on publicdata.au, with 6,736 rows and 17 fields. The same version is kept at https://publicdata.au/d/sa-liquor-gaming-licences-2018/v/2018-09-04/ in 9 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Attorney-General's Department under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Attorney-General's Department, Government of South Australia, Liquor & Gaming Licences, https://data.sa.gov.au/data/dataset/liquor-gaming-licences, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.auliquor licencesgaming machines
The name, address and location of each private hospital in South Australia, 50 at the first version.This is the 2026-06-28 version of this dataset on publicdata.au, with 50 rows and 7 fields. The same…
The name, address and location of each private hospital in South Australia, 50 at the first version.This is the 2026-06-28 version of this dataset on publicdata.au, with 50 rows and 7 fields. The same version is kept at https://publicdata.au/d/sa-private-hospitals/v/2026-06-28/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by SA Health under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:SA Health, Government of South Australia, SA Private Hospitals, https://data.sa.gov.au/data/dataset/sa-private-hospitals, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.auhospitalsprivate hospitals
The name, address and location of each public hospital in South Australia, 73 at the first version.This is the 2026-06-28 version of this dataset on publicdata.au, with 73 rows and 8 fields. The same …
The name, address and location of each public hospital in South Australia, 73 at the first version.This is the 2026-06-28 version of this dataset on publicdata.au, with 73 rows and 8 fields. The same version is kept at https://publicdata.au/d/sa-public-hospitals/v/2026-06-28/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by SA Health under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:SA Health, Government of South Australia, SA Public Hospitals, https://data.sa.gov.au/data/dataset/sa-public-hospitals, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.auhospitalspublic hospitals
The zones of South Australian government primary schools that take their core intake from a zone, one shape per school, for the newest enrolment year.This is the 2024-09-25 version of this dataset on …
The zones of South Australian government primary schools that take their core intake from a zone, one shape per school, for the newest enrolment year.This is the 2024-09-25 version of this dataset on publicdata.au, with 84 rows and 3 fields. The same version is kept at https://publicdata.au/d/sa-primary-school-zones/v/2024-09-25/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department for Education under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department for Education, Government of South Australia, School Zones for South Australian Government Primary Schools, https://data.sa.gov.au/data/dataset/school-zones-for-south-australian-govt-primary-schools, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.auschool zonesschool catchments
AUTHENTIC CONTENT AND ARTIFICIAL INTELLIGENCE IN DIGITAL TOURISM MARKETING: A THEORETICAL-ANALYTICAL STUDY
September, 2026 • Publication • МЕЖДУНАРОДНАЯ КОНФЕРЕНЦИЯ АКАДЕМИЧЕСКИХ НАУК
Haydarova, N.
This article examines the theoretical content of “authentic content” in digital tourism marketing, its operationalization through the concept of information granularity, and the relative e…
This article examines the theoretical content of “authentic content” in digital tourism marketing, its operationalization through the concept of information granularity, and the relative effectiveness of artificial-intelligence-generated content (AIGC) compared to traditional user-generated content (UGC). The study was conducted through a comparative-analytical synthesis of scholarly literature and industry reports published between 2010 and 2026. The findings indicate that a large share of travelers — approximately 85 percent — rate user-generated content as more trustworthy than official brand-produced material, while artificial intelligence, although it increases content-production speed, still lags behind human-authored narratives in emotional credibility and distinctiveness. The article proposes a “human-centered automation” model for tourism organizations, in which artificial intelligence functions as a supporting tool while genuine experience-holders remain the primary source of content.
The zones of South Australian government high schools that take their core intake from a zone, one shape per school, for the newest enrolment year.This is the 2024-09-25 version of this dataset on pub…
The zones of South Australian government high schools that take their core intake from a zone, one shape per school, for the newest enrolment year.This is the 2024-09-25 version of this dataset on publicdata.au, with 46 rows and 4 fields. The same version is kept at https://publicdata.au/d/sa-high-school-zones/v/2024-09-25/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department for Education under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department for Education, Government of South Australia, School Zones for South Australian Government High Schools, https://data.sa.gov.au/data/dataset/school-zones-for-south-australian-govt-high-schools, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.auschool zonesschool catchments
Traffic volume estimates on state roads, South Australia
September, 2026 • Dataset
Department for Infrastructure and Transport
The estimated annual average daily traffic on each section of South Australia's sealed state roads, with commercial vehicle counts by class, from the newest yearly snapshot.This is the 2026-09-24…
The estimated annual average daily traffic on each section of South Australia's sealed state roads, with commercial vehicle counts by class, from the newest yearly snapshot.This is the 2026-09-24 version of this dataset on publicdata.au, with 2,721 rows and 15 fields. The same version is kept at https://publicdata.au/d/sa-traffic-volumes/v/2026-09-24/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department for Infrastructure and Transport under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department for Infrastructure and Transport, Government of South Australia, Traffic Volumes, https://data.sa.gov.au/data/dataset/traffic-volumes, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.autraffic volumesAADT
The footprints of every State Heritage Place on the South Australian Heritage Register and every Local Heritage Place in the Planning and Design Code, with address, class and listing details.This is t…
The footprints of every State Heritage Place on the South Australian Heritage Register and every Local Heritage Place in the Planning and Design Code, with address, class and listing details.This is the 2026-06-28 version of this dataset on publicdata.au, with 23,229 rows and 39 fields. The same version is kept at https://publicdata.au/d/sa-heritage-places/v/2026-06-28/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department for Housing and Urban Development under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department for Housing and Urban Development, Government of South Australia, SA Heritage Places, https://data.sa.gov.au/data/dataset/sa-heritage-places, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.auheritage registerheritage listed
The boundaries of every gazetted suburb and locality in South Australia, one shape each with its name, postcode and suburb number, from the state's own layer.This is the 2026-06-28 version of thi…
The boundaries of every gazetted suburb and locality in South Australia, one shape each with its name, postcode and suburb number, from the state's own layer.This is the 2026-06-28 version of this dataset on publicdata.au, with 1,895 rows and 4 fields. The same version is kept at https://publicdata.au/d/sa-suburb-boundaries/v/2026-06-28/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department for Housing and Urban Development under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department for Housing and Urban Development, Government of South Australia, Suburbs, https://data.sa.gov.au/data/dataset/suburb-boundaries, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.ausuburb boundarieslocalities
Driver's licences by postcode, age and sex, South Australia
July, 2026 • Dataset
Department for Infrastructure and Transport
The number of current driver's licences in South Australia at the end of the newest quarter, by holder's postcode, age and sex. Updated quarterly.This is the 2026-07-09 version of this datas…
The number of current driver's licences in South Australia at the end of the newest quarter, by holder's postcode, age and sex. Updated quarterly.This is the 2026-07-09 version of this dataset on publicdata.au, with 46,248 rows and 4 fields. The same version is kept at https://publicdata.au/d/sa-drivers-licences-by-postcode/v/2026-07-09/ in 9 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department for Infrastructure and Transport under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department for Infrastructure and Transport, Government of South Australia, Drivers' Licences by postcode, age and sex, https://data.sa.gov.au/data/dataset/drivers-licences-by-postcode-age-and-sex, accessed 3 October 2026, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.
Australiagovernment open datapublicdata.audriver's licenceslicensed drivers
There is an increasing interest in upgrading the EModel, a parametric tool for speech quality estimation, to the wideband and super-wideband contexts. The
Contemporary models of Unmanned Aerial Vehicles (UAVs) are largely developed using simulators. In a typical scheme, a flight simulator is dovetailed with a
Undertaking engineering research can be compounding for beginning graduate students and thwarting even for seasoned researchers. With a wealth of academic
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