Please Note: As announced by the Minister for Immigration and Border Protection on 25 June 2017, the Department of Immigration and Border Protection (DIBP) retired the paper-based Outgoing Passenger Cards (OPC) from 1 July 2017. The information previously gathered via paper-based outgoing passenger cards is now be collated from existing government data and will continue to be provided to users. Further information can be accessed here: http://www.minister.border.gov.au/peterdutton/Pages/removal-of-the-outgoing-passenger-card-jun17.aspx.

Due to the retirement of the OPC, the Australian Bureau of Statistics (ABS) undertook a review of the OAD data based on a new methodology. Further information on this revised methodology is available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/3401.0Appendix2Jul%202017?opendocument&tabname=Notes&prodno=3401.0&issue=Jul%202017&num=&view=

A sampling methodology has been applied to this dataset. This method means that data will not replicate, exactly, data released by the ABS, but the differences should be negligible.

Due to ‘Return to Source’ limitations, data supplied to ABS from non-DIPB sources are also excluded.

Overseas Arrivals and Departures (OAD) data refers to the arrival and departure of Australian residents or overseas visitors, through Australian airports and sea ports, which have been recorded on incoming or outgoing passenger cards. OAD data describes the number of movements of travellers rather than the number of travellers. That is, multiple movements of individual persons during a given reference period are all counted. OAD data will differ from data derived from other sources, such as Migration Program Outcomes, Settlement Database or Visa Grant information. Travellers granted a visa in one year may not arrive until the following year, or may not travel to Australia at all. Some visas permit multiple entries to Australia, so travellers may enter Australia more than once on a visa. Settler Arrivals includes New Zealand citizens and other non-program settlers not included on the Settlement Database. The Settlement Database includes onshore processed grants not included in Settler Arrivals.

These de-identified statistics are periodically checked for privacy and other compliance requirements. The statistics were temporarily removed in March 2024 in response to a question about privacy within the emerging technological environment. Following a thorough review and risk assessment, the Department of Home Affairs has republished the dataset.

Geoscape G-NAF is the geocoded address database for Australian businesses and governments. It’s the trusted source of geocoded address data for Australia with over 50 million contributed addresses distilled into 15.4 million G-NAF addresses. It is built and maintained by Geoscape Australia using independently examined and validated government data. \r \r From 22 August 2022, Geoscape Australia is making G-NAF available in an additional simplified table format. G-NAF Core makes accessing geocoded addresses easier by utilising less technical effort.\r \r G-NAF Core will be updated on a quarterly basis along with G-NAF.\r \r Further information about contributors to G-NAF is available here.\r \r With more than 15 million Australian physical address record, G-NAF is one of the most ubiquitous and powerful spatial datasets. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.\r \r Updated versions of G-NAF are published on a quarterly basis. Previous versions are available here\r \r Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.\r \r Changes in the May 2025 release\r \r * Nationally, the May 2025 update of G-NAF shows an overall increase of 47,194 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,753,927 of which 14,909,770 or 94.64% are principal.\r \r * At some locations, there are unit-numbered addresses that appear to be duplicate addresses. Geoscape is working to identify these locations and include these addresses as separate addresses in G-NAF. To facilitate this process, some secondary addresses have had the word RETAIL added to their building names. In the first instance, this process is being progressively rolled out to identified locations, but it is expected that the requirement for this will become ongoing.\r \r * There is one new locality in G-NAF: Keswick Island, QLD.\r \r * The source data used for generating G-NAF STREET_LOCALITY_POINT data in New South Wales has an updated datum and changed from GDA94 to GDA2020. This has resulted in updates to the STREET_LOCALITY_POINT geometry for approximately 91,000 records, however, more than 95% of these have moved less than a metre.\r \r \r * Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.\r \r Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.\r \r Additional information: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.\r \r

License Information\r

\r Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)\r \r The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added. \r \r The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.\r \r End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).\r \r Users must also note the following attribution requirements:\r \r Preferred attribution for the Licensed Material:\r \r

_G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.\r \r Preferred attribution for Adapted Material:\r \r Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.\r \r

What to Expect When You Download G-NAF\r

\r G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.\r \r

AbstractTaxation Statistics 2021-22 is a continental dataset providing an overview of the income and tax status of Australian individuals, companies, partnerships, trusts and funds for the 2021-22 financial year.The dataset was compiled for the annual publication, Taxation Statistics, the ATO’s key statistical report. It provides a comprehensive statistical summary of information taxpayers report to the ATO. It includes information sourced from:The income tax returns of individuals, companies, super funds, partnerships and trusts.Annual returns for fringe benefits tax (FBT) and goods and services tax (GST).Business activity statements (BAS) and instalment activity statements (IAS).Schedules for rental properties, capital gains tax (CGT) and international dealings.Superannuation member contribution statements (MCS).Other information reported to the ATO in relation to excise, the pay as you go (PAYG) system, and charitable institutions.Previous versions of this dataset are available on the Australian Government open government data portal data.gov.auCurrencyDate Published: 25 September 2023Date Updated: 13 September 2024Modification Frequency: As neededData ExtentSpatial ExtentNorth: -9.1°South: -43.6°East: 159.1°West: 96.8°Source InformationData and Metadata are available from Taxation Statistics 2021-22 | Datasets | data.gov.au, Taxation Statistics 2021-22 - Dataset - data.gov.au.The data was obtained from the Australian Taxation Office.Catalog Entry: Taxation Statistics 2021-22 | Datasets | data.gov.auLineage statementThis layer was put together using two datasets. Australian taxation and income data provided by the Australian Taxation Office (ATO), was joined to the 2021 Postal Areas shapefile provided by the Australian Bureau of Statistics (ABS).Postal AreasPostal Areas are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries and should only be used for statistical purposes.Data and geography referencesSource data publication: Australian Statistical Geography Standard (ASGS) Edition 3Geographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3 - Postal AreasFurther information: Australian Statistical Geography Standard (ASGS) Edition 3 - Non ABS StructuresSource: Australian Bureau of Statistics (ABS)Data PreparationThe CSV was joined to the POA geographies using the 4 digit postcode. For the CSV, it was exported as a file geodatabase and a new field had to be generated where the postcodes were entered as text data to maintain the leading zeroes. The new text postcode field was then joined to the ABS POA_Name field.All data manipulations, joins, and spatial operations were performed using ArcGIS Pro 3.4.3.Data dictionaryAttribute nameDescriptionPostcodesThe postcode affiliated with that areaAREA_SQKMThe area in square kilometres of the postcodeAverage taxable income or lossThe average taxable income or loss of the postcodeNumber of individuals lodging an income tax returnThe number of individuals lodging a tax return in that postcodeCount taxable income or lossThe number of individuals reporting taxable income or loss in the postcodeMedian taxable income or lossThe median taxable income or loss of the postcodeProportion with salary or wagesThe proportion of individuals reporting salary or wages in the postcodeCount salary or wagesThe number of individuals reporting salary or wages in the postcodeAverage salary or wagesThe average salary or wages of the postcodeMedian salary or wagesThe median salary or wages of the postcodeProportion with net rentThe proportion of individuals reporting net rent in the postcodeCount net rentThe number of individuals reporting net rent in the postcodeAverage net rentThe average cost of net rent in the postcodeMedian net rentThe median net rent in the postcodeCount total income or lossThe number of individuals reporting total income or loss in the postcodeAverage total income or lossThe average total income or loss of the postcodeMedian total income or lossThe median total income or loss of the postcodeCount total deductionsCount of individuals reporting total deductions in the postcodeAverage total deductionsThe average total deductions of the postcodeMedian total deductionsThe median total deductions of the postcodeProportion with total business incomeThe proportion of individuals reporting business income in the postcodeCount total business incomeThe number of individuals reporting business income in the postcodeAverage total business incomeThe average total business income in the postcodeMedian total business incomeThe median total business income in the postcodeCount total business expensesThe number of individuals reporting business expenses in the postcodeAverage total business expensesThe average business expenses in the postcodeMedian total business expensesThe median business expenses in the postcodeProportion with net taxThe proportion of individuals with net tax in the postcodeCount net taxThe number of individuals with net tax in the postcodeAverage net taxThe average net tax in the postcodeMedian net taxThe median net tax in the postcodeCount super total accounts balanceThe total number of super accounts in the postcodeAverage super total accounts balanceThe average balance of super accounts in the postcodeMedian super total accounts balanceThe median balance of super accounts in the postcodeProportion with total business expensesThe proportion of individuals reporting business expenses in the postcodeSHAPE_LengthLength of polygon outlineSHAPE_AreaArea of the polygonContactAustralian Taxation Office, taxstats@ato.gov.au

This dataset contains project materials and interview transcripts from a qualitative study aiming to undertake a nuanced analysis of phenomena surrounding the acceptance of asylum seekers by interviewing a subset of the Our Lives cohort to better appreciate why some young Australians are accepting of asylum seekers. The broader Our Lives project (www.ourlives.org.au) is a longitudinal study following, among other things, the social and political orientations of a single age cohort of young people in Queensland, Australia as they move from adolescence into adulthood. For nearly a decade, the study has been collecting both quantitative and qualitative data from this group of young people on different domains of their lives. The goal of the qualitative investigation was to listen to participants speak on the topic of asylum seekers coming to Australia by boat, and to consider how they come to understand what they ‘know’ about the issue and how this relates to their attitudes and actions towards ‘boat people’. It was undertaken by applying a purposive intensity sampling strategy to identify potential participants, selecting respondents who had strongly agreed or strongly disagreed with the statement ‘All boats carrying asylum seekers should be turned back’ in the 2010 Our Lives survey. Ultimately interviews were conducted in 2012 with 20 young people who had indicated in their response to the question that they held firm views on the asylum issue.

Please note this dataset is an archived version of the Geocoded National Address File (G-NAF). For the latest version of the G-NAF please go to this url: https://data.gov.au/data/dataset/geocoded-national-address-file-g-naf

Geoscape G-NAF is Australia’s authoritative, geocoded address file. It is built and maintained by Geoscape Australia using authoritative government data. Further information about contributors to G-NAF is available here.

G-NAF is one of the most ubiquitous and powerful spatial datasets. It contains more than 15 million Australian physical address records. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.

Updated versions of G-NAF are published on a quarterly basis.

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Changes in the February 2025 release

• Nationally, the February 2025 update of G-NAF shows an overall increase of 47,284 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,706,733 of which 14,867,032 or 94.65% are principal.

• In the February 2025 release of G-NAF, over 300 addresses in Morra, Western Australia have been updated. About 150 addresses have changed locations and 160 properties now have street numbers instead of lot numbers. Some properties are still using lot-numbers, resulting in two addressees. This issue will be resolved in the May 2025 update of G-NAF.

• In the February release, Geoscape has re-classified geocode types of ‘Property Access Point Setback’ (PAPS) to be ‘Property Access Point’ (PAP) in South Australia where the geocode falls within a road casement as the geocode is not set back into a land parcel. This update has changed approximately 57,000 geocodes to PAP from their previous classification of PAPS, while there are some 14,000 PAPS geocodes that remain unchanged.

• Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.

Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.

Note: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

License Information

Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)

The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added.

The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.

End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

_G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

Preferred attribution for Adapted Material:

Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

What to Expect When You Download G-NAF

G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.

AbstractTaxation Statistics 2012-13 is a continental dataset providing an overview of the income and tax status of Australian individuals, companies, partnerships, trusts and funds for the 2012-13 financial year.The dataset was compiled for the annual publication, Taxation Statistics, the ATO’s key statistical report. It provides a comprehensive statistical summary of information taxpayers report to the ATO. It includes information sourced from:The income tax returns of individuals, companies, super funds, partnerships and trusts.Annual returns for fringe benefits tax (FBT) and goods and services tax (GST).Business activity statements (BAS) and instalment activity statements (IAS).Schedules for rental properties, capital gains tax (CGT) and international dealings.Superannuation member contribution statements (MCS).Other information reported to the ATO in relation to excise, the pay as you go (PAYG) system, and charitable institutions.Previous versions of this dataset are available on the Australian Government open government data portal data.gov.auCurrencyDate Published: 08 April 2015Date Updated: 11 August 2023Modification Frequency: As neededData ExtentSpatial ExtentNorth: -9.1°South: -44.2°East: 159.1°West: 96.8°Source informationData and Metadata are available from Taxation Statistics 2012-13 - Dataset - data.gov.auThe data was obtained from the Australian Taxation Office.Catalog Entry: Taxation Statistics 2012-13 - Dataset - Data.gov.auLineage statementThis layer was put together using two datasets. Australian taxation and income data provided by the Australian Taxation Office (ATO), was joined to the 2011 Postal Areas shapefile provided by the Australian Bureau of Statistics (ABS).Postal AreasPostal Areas (POA) are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries exactly and should only be used for statistical purposes.Data and geography referencesSource data publication:Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2011Further information: Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2011 – Explanatory NotesSource:Australian Bureau of Statistics (ABS)Data PreparationThe CSV was joined to the POA geographies using the 4 digit postcode. For the CSV, it was exported as a file geodatabase and a new field had to be generated where the postcodes were entered as text data to maintain the leading zeroes. The new text postcode field was then joined to the ABS POA_Name field.All data manipulations, joins, and spatial operations were performed using ArcGIS Pro 3.4.3.Data Loss:The taxation statistics CSV and corresponding ABS data have the following record counts:File NameNumber of Recordsaveragetaxableincome201213.csv2563POA_2011_AUST.shp2516The ATO dataset experienced a data loss of 47 records that did not align to an ABS POA code. Postcodes on the ATO datasets are self-reported on individuals’ tax returns documentation. The data loss is attributed to mis-reporting, reporting of old postcodes from the 2006 census, and PO Boxes and Large Volume Receivers.Data dictionaryAttribute nameDescriptionAREA_SQKMThe area in square kilometres of the postcodeAverage taxable incomeThe average taxable income of the postcodePostcodesThe postcode affiliated with that areaSHAPE_LengthLength of polygon outlineSHAPE_AreaArea of the polygonContactAustralian Taxation Office, taxstats@ato.gov.au

SAIVT-Campus Dataset

Overview

The SAIVT-Campus Database is an abnormal event detection database captured on a university campus, where the abnormal events are caused by the onset of a storm. Contact Dr Simon Denman or Dr Jingxin Xu for more information.

Licensing

The SAIVT-Campus database is © 2012 QUT and is licensed under the Creative Commons Attribution-ShareAlike 3.0 Australia License.

Attribution

To attribute this database, please include the following citation: Xu, Jingxin, Denman, Simon, Fookes, Clinton B., & Sridharan, Sridha (2012) Activity analysis in complicated scenes using DFT coefficients of particle trajectories. In 9th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2012), 18-21 September 2012, Beijing, China. available at eprints.

Acknowledging the Database in your Publications

In addition to citing our paper, we kindly request that the following text be included in an acknowledgements section at the end of your publications: We would like to thank the SAIVT Research Labs at Queensland University of Technology (QUT) for freely supplying us with the SAIVT-Campus database for our research.

Installing the SAIVT-Campus database

After downloading and unpacking the archive, you should have the following structure:

SAIVT-Campus +-- LICENCE.txt +-- README.txt +-- test_dataset.avi +-- training_dataset.avi +-- Xu2012 - Activity analysis in complicated scenes using DFT coefficients of particle trajectories.pdf

Notes

The SAIVT-Campus dataset is captured at the Queensland University of Technology, Australia.

It contains two video files from real-world surveillance footage without any actors:

training_dataset.avi (the training dataset)
test_dataset.avi (the test dataset).

This dataset contains a mixture of crowd densities and it has been used in the following paper for abnormal event detection:

Xu, Jingxin, Denman, Simon, Fookes, Clinton B., & Sridharan, Sridha (2012) Activity analysis in complicated scenes using DFT coefficients of particle trajectories. In 9th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2012), 18-21 September 2012, Beijing, China. Available at eprints. 
This paper is also included with the database (Xu2012 - Activity analysis in complicated scenes using DFT coefficients of particle trajectories.pdf) Both video files are one hour in duration.

The normal activities include pedestrians entering or exiting the building, entering or exiting a lecture theatre (yellow door), and going to the counter at the bottom right. The abnormal events are caused by a heavy rain outside, and include people running in from the rain, people walking towards the door to exit and turning back, wearing raincoats, loitering and standing near the door and overcrowded scenes. The rain happens only in the later part of the test dataset.

As a result, we assume that the training dataset only contains the normal activities. We have manually made an annotation as below:

the training dataset does not have abnormal scenes
the test dataset separates into two parts: only normal activities occur from 00:00:00 to 00:47:16 abnormalities are present from 00:47:17 to 01:00:00. We annotate the time 00:47:17 as the start time for the abnormal events, as from this time on we have begun to observe people stop walking or turn back from walking towards the door to exit, which indicates that the rain outside the building has influenced the activities inside the building. Should you have any questions, please do not hesitate to contact Dr Jingxin Xu.

Unemployment Rate in Australia decreased to 4.20 percent in July from 4.30 percent in June of 2025. This dataset provides - Australia Unemployment Rate at 5.8% in December - actual values, historical data, forecast, chart, statistics, economic calendar and news.

AbstractTaxation Statistics 2020-21 is a continental dataset providing an overview of the income and tax status of Australian individuals, companies, partnerships, trusts and funds for the 2020-21 financial year.The dataset was compiled for the annual publication, Taxation Statistics, the ATO’s key statistical report. It provides a comprehensive statistical summary of information taxpayers report to the ATO. It includes information sourced from:The income tax returns of individuals, companies, super funds, partnerships and trusts.Annual returns for fringe benefits tax (FBT) and goods and services tax (GST).Business activity statements (BAS) and instalment activity statements (IAS).Schedules for rental properties, capital gains tax (CGT) and international dealings.Superannuation member contribution statements (MCS).Other information reported to the ATO in relation to excise, the pay as you go (PAYG) system, and charitable institutions.Previous versions of this dataset are available on the Australian Government open government data portal data.gov.auCurrencyDate Published: 07 March 2023Date Updated: 13 September 2024Modification Frequency: As neededData ExtentGeocentric Datum of Australia 1994 (GDA94)Spatial ExtentNorth: -9.1°South: -43.6°East: 159.1°West: 96.8°Source InformationData and Metadata are available from Taxation Statistics 2020-21 - Dataset - data.gov.auThe data was obtained from the Australian Taxation Office.Catalog Entry: Taxation Statistics 2020-21 | Datasets | data.gov.auLineage StatementThis layer was put together using two datasets. Australian taxation and income data provided by the Australian Taxation Office (ATO), was joined to the 2016 Postal Areas shapefile provided by the Australian Bureau of Statistics (ABS).Postal AreasPostal Areas (POA) are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries exactly and should only be used for statistical purposes.Data and geography referencesSource data publication: Australian Statistical Geography Standard (ASGS) Edition 2 - Postal AreasFurther information: Australian Statistical Geography Standard (ASGS) Edition 2 - Non ABS StructuresSource: Australian Bureau of Statistics (ABS)Data PreparationThe CSV was joined to the POA geographies using the 4 digit postcode. For the CSV, it was exported as a file geodatabase and a new field had to be generated where the postcodes were entered as text data to maintain the leading zeroes. The new text postcode field was then joined to the ABS POA_Name field.All data manipulations, joins, and spatial operations were performed using ArcGIS Pro 3.4.3.Data dictionaryAttribute nameDescriptionPostcodesThe postcode affiliated with that areaAREA_SQKMThe area in square kilometres of the postcodeAverage taxable income or lossThe average taxable income or loss of the postcodeNumber of individuals lodging an income tax returnThe number of individuals lodging a tax return in that postcodeCount taxable income or lossThe number of individuals reporting taxable income or loss in the postcodeMedian taxable income or lossThe median taxable income or loss of the postcodeProportion with salary or wagesThe proportion of individuals reporting salary or wages in the postcodeCount salary or wagesThe number of individuals reporting salary or wages in the postcodeAverage salary or wagesThe average salary or wages of the postcodeMedian salary or wagesThe median salary or wages of the postcodeProportion with net rentThe proportion of individuals reporting net rent in the postcodeCount net rentThe number of individuals reporting net rent in the postcodeAverage net rentThe average cost of net rent in the postcodeMedian net rentThe median net rent in the postcodeCount total income or lossThe number of individuals reporting total income or loss in the postcodeAverage total income or lossThe average total income or loss of the postcodeMedian total income or lossThe median total income or loss of the postcodeCount total deductionsCount of individuals reporting total deductions in the postcodeAverage total deductionsThe average total deductions of the postcodeMedian total deductionsThe median total deductions of the postcodeProportion with total business incomeThe proportion of individuals reporting business income in the postcodeCount total business incomeThe number of individuals reporting business income in the postcodeAverage total business incomeThe average total business income in the postcodeMedian total business incomeThe median total business income in the postcodeCount total business expensesThe number of individuals reporting business expenses in the postcodeAverage total business expensesThe average business expenses in the postcodeMedian total business expensesThe median business expenses in the postcodeProportion with net taxThe proportion of individuals with net tax in the postcodeCount net taxThe number of individuals with net tax in the postcodeAverage net taxThe average net tax in the postcodeMedian net taxThe median net tax in the postcodeCount super total accounts balanceThe total number of super accounts in the postcodeAverage super total accounts balanceThe average balance of super accounts in the postcodeMedian super total accounts balanceThe median balance of super accounts in the postcodeProportion with total business expensesThe proportion of individuals reporting business expenses in the postcodeSHAPE_LengthLength of polygon outlineSHAPE_AreaArea of the polygonContactAustralian Taxation Office, taxstats@ato.gov.au

Abstract

The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.

This dataset shows the Australian Bureau of Statistics (ABS) Mesh Blocks across Victoria, with the 2011 census population and housing counts attached as attributes. It was derived by the Bioregional Assessment Programme from the ABS Mesh Block Population Counts Aus 2011 dataset, and the ABS Boundaries 2011 dataset. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

Dataset History

The ABS 2011 Mesh Block Population Count spreadsheet (https://data.bioregionalassessments.gov.au/datastore/dataset/ee39fa76-db4e-412a-af0a-115d965b5813) was joined to the Victorian ABS Mesh Block boundaries (https://data.bioregionalassessments.gov.au/datastore/dataset/8b65c3a4-7010-4a79-8eaa-5621b750347f) using the unique MB_CODE11 field within ESRI ArcMap 10.2.

Two additional fields were added to show Mesh Block Area (km2) and Population Density (people/km2). These field values were calculated within ESRI ArcMap 10.2 using the Field Calculator tool.

Dataset Citation

Bioregional Assessment Programme (2014) Victorian ABS Mesh Block Population 2011. Bioregional Assessment Derived Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/b27fdf82-dd1e-4841-a228-21f671a95368.

Dataset Ancestors

• Derived From ABS Mesh Block Population Counts Aus 2011

• Derived From ABS Boundaries 2011

The data and files in these directories underpin inland flyway analyses of Australia waterbird species. The goal is to understand the habitat use of a species across its life cycle is essential for effective management.

Many waterbirds are highly mobile at range of spatial and temporal scales, which when using traditional methods such as on-ground surveys or leg-banding can make monitoring, quantifying, and predicting habitat use difficult.

In this analysis, we used a 7-year GPS satellite telemetry dataset of 141 individuals to: a) quantify habitat selection post-dispersal from breeding sites, and b) predict habitat availability, for straw-necked ibis (SNI) and royal spoonbill (RSB).

This research is led by CSIRO as part of the CEWH Monitoring, Evaluation and Research Program (Flow- MER). It builds on and incorporates satellite tracking of straw-necked ibis, Australian white ibis and royal spoonbills conducted by CSIRO between 2016–19 as part of the Environmental Water Knowledge and Research (EWKR) Waterbird Theme. The EWKR research identified a need for additional satellite tracking of species dependent on water to feed (such as spoonbills and egrets), not just to breed (such as ibis), and for tracking of the movements of birds from additional important sites across the Basin.

The data and code in this directory were used in the analyses described in the manuscript "Extensive tracking of nomadic waterbird movements reveals an inland flyway". The manuscript presents analyses of GPS satellite telemetry data tracking the movements of 73 straw-necked ibis (SNI) (Threskiornis spinicollis) and 42 royal spoonbills (RSB) (Platalea regia) over seven years. We used these data to identify long-distance movements and to demarcate and characterise movement routes. We used Hidden Markov Modelling (HMM) to identify movement classes from the prepared tracking data with the goal of separating long-distance flight movements from foraging/roosting movements. We used the ‘kernelUD’ function from the R package adehabitatHR to estimate the utilisation distribution for all individuals of each species using the kernel density estimation method (KED). For each species, we sampled the intersection of the KED50 with known important aggregate-breeding waterbird nesting sites. We then assessed the KED50 for each species against environmental covariates to identify habitat preferences during long-distance movements.

The kernels are intersected with publicly available remote sensing derived products. The MRVBF and elevation .tif files are not included but can be found at MRVBF - https://data.csiro.au/collection/csiro:5681, Elevation - https://data.gov.au/data/dataset/mcas-s-data-pack-update-2022

The rainfall map was created from monthly rainfall averaged over 2011-2020 and binned into deciles over the whole of Australia (Australian Gridded Climate Data; Evans et al. (2020)). Data were downloaded from https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f6475_9317_5747_6204. The summary file is available with the data pack at data_env/rainfall_avg_2011_2020_decile.tif Lineage: Telemetry data were gathered from GPS transmitters deployed on straw-necked ibis (SNI) and royal spoonbill (RSB) at eight breeding sites between 2016 and 2023. Birds were captured either by hand, with leg-nooses, or by using a net launcher. We attached transmitters as a ‘backpack’ using harnesses made of Teflon ribbon or Spectra ribbon (Bally Ribbon MillsTM), fitted either as wing-loops with a join at the keel (SNI and some RSB), or as leg-loops (RSB). Harness design was based on designs used for other species modified and improved over time. Transmitters weighed 12–40 g, ranging from < 1% to 5% of bird bodyweight. We used solar-powered GPS transmitters with a fix resolution of 15–26 m and fix frequency ranging from one minute to 6 hours (depending on transmitter type and programmed duty cycle). Data were transmitted via either the Argos satellite network (for Geotrak units) or the 3G network (for Ornitela and Druid units). We considered duty cycle in analyses, with interpolation or down-scaling applied when appropriate.

To ensure that results reflected longer-term non-breeding movements, we limited our analysis to birds for which > 30 d of data were available after the date at which they dispersed from the breeding site where they were captured. Data for nesting adults and for adults and juveniles still within breeding sites after capture but before dispersal were removed from the dataset. Please see README and paper in Ecology and Evolution for extra details on the data processing.

Figure CaptionsVisitor Numbers + Temperature Peaks - Cleaned dataset containing Tour times for Cathedral Cave, Wellington NSW, Australia, as well as tour sizes, both by total and ticket type breakdown. The tours also contain the total change in temperature peaks found in Appendix D that was matched with a tour time.AbstractShow caves are caves that have been made accessible for guided public visits and are a large tourism industry globally, amassing $850 million per year. However, with the increase of people entering these caves, there is an increased concern of the impact that people may have on the condition of the caves. This has brought attention within the caves, as the attraction of tourists can build up and raise the temperature, in comparison to their natural range. To assist in the understanding of human impacts on cave temperature levels, the study compiled temperature data from a probe within Cathedral Cave, Wellington NSW, Australia and compiled into a database, which was used to create a time series for analysis of significant temperature peaks, which was then compared with visitor numbers within the cave system. These comparisons were analysed using several linear regressions and scatter plots, to determine what the major temperature peak trends. The research found that there were three key factors on the change in temperature: the size of a tour, the time of day that a tour takes place in and the tour composition (i.e. the number of adults vs children). These factors were found to display a range of impacts upon how the temperature would change, in comparison to the baseline data that was collected by the same logger which showed no temperature changes in the absence of visitors. Potential new avenues for research includes restrictions of tour sizes, detailed studies into the impacts of children, seasonal variabilities, the value in multiple, more accurate climate loggers and looking at other caves. This can be used to help cave management in the future, balancing displaying the cave’s natural beauty with the health of the cave ecosystem.

The file set is a freely downloadable aggregation of information about Australian schools. The individual files represent a series of tables which, when considered together, form a relational database. The records cover the years 2008-2014 and include information on approximately 9500 primary and secondary school main-campuses and around 500 subcampuses. The records all relate to school-level data; no data about individuals is included. All the information has previously been published and is publicly available but it has not previously been released as a documented, useful aggregation. The information includes:
(a) the names of schools
(b) staffing levels, including full-time and part-time teaching and non-teaching staff
(c) student enrolments, including the number of boys and girls
(d) school financial information, including Commonwealth government, state government, and private funding
(e) test data, potentially for school years 3, 5, 7 and 9, relating to an Australian national testing programme know by the trademark 'NAPLAN'

Documentation of this Edition 2016.1 is incomplete but the organization of the data should be readily understandable to most people. If you are a researcher, the simplest way to study the data is to make use of the SQLite3 database called 'school-data-2016-1.db'. If you are unsure how to use an SQLite database, ask a guru.

The database was constructed directly from the other included files by running the following command at a command-line prompt:
sqlite3 school-data-2016-1.db < school-data-2016-1.sql
Note that a few, non-consequential, errors will be reported if you run this command yourself. The reason for the errors is that the SQLite database is created by importing a series of '.csv' files. Each of the .csv files contains a header line with the names of the variable relevant to each column. The information is useful for many statistical packages but it is not what SQLite expects, so it complains about the header. Despite the complaint, the database will be created correctly.

Briefly, the data are organized as follows.
(a) The .csv files ('comma separated values') do not actually use a comma as the field delimiter. Instead, the vertical bar character '|' (ASCII Octal 174 Decimal 124 Hex 7C) is used. If you read the .csv files using Microsoft Excel, Open Office, or Libre Office, you will need to set the field-separator to be '|'. Check your software documentation to understand how to do this.
(b) Each school-related record is indexed by an identifer called 'ageid'. The ageid uniquely identifies each school and consequently serves as the appropriate variable for JOIN-ing records in different data files. For example, the first school-related record after the header line in file 'students-headed-bar.csv' shows the ageid of the school as 40000. The relevant school name can be found by looking in the file 'ageidtoname-headed-bar.csv' to discover that the the ageid of 40000 corresponds to a school called 'Corpus Christi Catholic School'.
(3) In addition to the variable 'ageid' each record is also identified by one or two 'year' variables. The most important purpose of a year identifier will be to indicate the year that is relevant to the record. For example, if one turn again to file 'students-headed-bar.csv', one sees that the first seven school-related records after the header line all relate to the school Corpus Christi Catholic School with ageid of 40000. The variable that identifies the important differences between these seven records is the variable 'studentyear'. 'studentyear' shows the year to which the student data refer. One can see, for example, that in 2008, there were a total of 410 students enrolled, of whom 185 were girls and 225 were boys (look at the variable names in the header line).
(4) The variables relating to years are given different names in each of the different files ('studentsyear' in the file 'students-headed-bar.csv', 'financesummaryyear' in the file 'financesummary-headed-bar.csv'). Despite the different names, the year variables provide the second-level means for joining information acrosss files. For example, if you wanted to relate the enrolments at a school in each year to its financial state, you might wish to JOIN records using 'ageid' in the two files and, secondarily, matching 'studentsyear' with 'financialsummaryyear'.
(5) The manipulation of the data is most readily done using the SQL language with the SQLite database but it can also be done in a variety of statistical packages.
(6) It is our intention for Edition 2016-2 to create large 'flat' files suitable for use by non-researchers who want to view the data with spreadsheet software. The disadvantage of such 'flat' files is that they contain vast amounts of redundant information and might not display the data in the form that the user most wants it.
(7) Geocoding of the schools is not available in this edition.
(8) Some files, such as 'sector-headed-bar.csv' are not used in the creation of the database but are provided as a convenience for researchers who might wish to recode some of the data to remove redundancy.
(9) A detailed example of a suitable SQLite query can be found in the file 'school-data-sqlite-example.sql'. The same query, used in the context of analyses done with the excellent, freely available R statistical package (http://www.r-project.org) can be seen in the file 'school-data-with-sqlite.R'.

AbstractTaxation Statistics 2011-12 is a continental dataset providing an overview of the income and tax status of Australian individuals, companies, partnerships, trusts and funds for the 2011-2012 financial year.The dataset was compiled for the annual publication, Taxation Statistics, the ATO’s key statistical report. It provides a comprehensive statistical summary of information taxpayers report to the ATO. It includes information sourced from:The income tax returns of individuals, companies, super funds, partnerships and trusts.Annual returns for fringe benefits tax (FBT) and goods and services tax (GST).Business activity statements (BAS) and instalment activity statements (IAS).Schedules for rental properties, capital gains tax (CGT) and international dealings.Superannuation member contribution statements (MCS).Other information reported to the ATO in relation to excise, the pay as you go (PAYG) system, and charitable institutions.Previous versions of this dataset are available on the Australian Government open government data portal data.gov.auCurrencyDate Published: 24 April 2014Date Modified: 11 August 2023Modification Frequency: As neededData ExtentCoordinate Reference Geocentric Datum of Australia 1994 (GDA1994)Spatial ExtentNorth: -9.1°South: -43.6°East: 159.1°West: 96.8°Source informationData and Metadata are available from Taxation Statistics 2011-12 - Dataset - data.gov.auThe data was obtained from Australian Taxation OfficeCatalog Entry: Taxation Statistics 2011-12 - Dataset - Data.gov.auLineage statementThis layer was put together using two datasets. Australian taxation and income data provided by the Australian Taxation Office (ATO), was joined to the 2011 Postal Areas shapefile provided by the Australian Bureau of Statistics (ABS).Postal AreasPostal Areas (POA) are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries exactly and should only be used for statistical purposes.Data and geography referencesSource data publication: Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2011Further information: Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2011 – Explanatory NotesSource: Australian Bureau of Statistics (ABS)Data Preparation:The CSV was joined to the POA geographies using the 4 digit postcode. For the CSV, it was exported as a file geodatabase and a new field had to be generated where the postcodes were entered as text data to maintain the leading zeroes. The new text postcode field was then joined to the ABS POA_Name field.All data manipulations, joins, and spatial operations were performed using ArcGIS Pro 3.4.3.Data Loss:The taxation statistics CSV and corresponding ABS data have the following record counts:File NameNumber of Recordspc-update-all-individuals.csv2876POA_2011_AUST.shp2516The ATO dataset experienced a data loss of 360 records that did not align to an ABS POA code. 158 of these records are PO Boxes and Large Volume Receivers (LVRs) that are not included in the ABS POA Data, the remaining missing datapoints did not have an ABS equivalent, and are not represented. In 2012, increased use of eTax software reduced this discrepancy.Data dictionaryAttribute nameDescriptionAREA_SQKMThe area in square kilometres of the postcodeAverage taxable incomeThe average taxable income of the postcodePostcodesThe postcode affiliated with that areaSHAPE_LengthLength of polygon outlineSHAPE_AreaArea of the polygonContactAustralian Taxation Office, taxstats@ato.gov.au

The Collaborative Australian Protected Areas Database (CAPAD) 2016 provides both spatial and textual information about government, Indigenous and privately protected areas for Australia, in both the marine and terrestrial environments. This dataset is the marine component of the CAPAD only. Marine CAPAD provides information about off-shore protected areas in both state and Commonwealth waters. State and Territory conservation agencies supplied data current to 30 June 2016. This is the eighth version of the marine database, with previous versions released in 1997, 2002, 2004, 2008, 2010, 2012 and 2014.The Department also publishes protected areas data for the terrestrial environment. The terrestrial component of the database has been previously released in 1997, 2000, 2002, 2004, 2006, 2008 2010, 2012 and 2014.CAPAD provides a snapshot of protected areas that meet the IUCN definition of a protected area: "A protected area is an area of land and/or sea especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means" (IUCN 1994).The department publishes a summary of the CAPAD data biennially on its website at https://www.dcceew.gov.au/environment/land/nrs/science/capad.This version of CAPAD is a public and downloadable version of CAPAD 2016 data, available for use through the CC-BY licencing model.Commercial users: Commercial users should note the availability of a more descriptive dataset for Commonwealth Marine Reserves. It is recommended for use in commercial applications as it includes additional information about management arrangements for Commonwealth Marine Reserves. This dataset is available under Creative Commons Attribution Non-Commercial license from:https://www.environment.gov.au/fed/catalog/search/resource/details.page?uuid=%7B2E8DD19C-1B93-4D90-BD1C-128DDC4A2998%7D------------------------------------------------------------------------------------------------------IMPORTANT INFORMATION FOR MARINE USERS – TRANSITIONAL ARRANGEMENTSThe process for developing management plans has been completed for the five Commonwealth marine reserve networks declared around Australia and the Coral Sea Commonwealth Marine Reserve. Until the new management plans come into effect transitional management arrangements are in place. Under these transitional arrangements, there are no changes "on the water" for users in the new areas added to the Commonwealth marine reserve estate. If people hold an existing approval to undertake activities within Commonwealth marine reserves or the now-revoked Coral Sea Conservation Zone, they are able to continue to operate under the terms of the existing approval. No additional administrative requirements apply.The management plan for the South-east Network came into effect on 1 July 2013, while the management plans for the South-west, North-west, North and Temperate East Networks and the Coral Sea Commonwealth Marine Reserve are under review. More information is available at https://parksaustralia.gov.au/marine/parks/.------------------------------------------------------------------------------------------------------Main attributes in Marine CAPAD 2016 include:PA_ID: The protected area ID code. The first three digits of the PA_ID code are common to all component polygons of a single protected area. It is a DoEE generated number.NAME: the name of the protected area.TYPE: the type of protected area according to the protected area establishment mechanism.TYPE_ABBR: the abbreviation of the TYPE.TYPE abbreviations:AQR = Aquatic ReserveCA = Conservation AreaCMR = Commonwealth Marine ReserveCP = Conservation ParkDPAA = Dugong Protection Area (A)DPAB = Dugong Protection Area (B)DS = Dolphin SanctuaryFHAA = Fish Habitat Area (A)FHAB = Fish Habitat Area (B)FHPA = Fish Habitat Protection AreaGR = Game ReserveIPA = Indigenous Protected AreaLS = Rock Lobster SanctuaryMCA = Marine Conservation AreaMMA = Marine Management AreaMNP = Marine National ParkMNR = Marine Nature ReserveMP = Marine ParkMS = Marine SanctuaryNP = National ParkNPC = National Park (Commonwealth)NPS4 = National Parks Act - Schedule 4 park or reserveNR = Nature ReserveSH = Shipwreck ReserveS5G = 5(1)(g) ReserveS5H = 5(1)(h) ReserveIUCN: the IUCN protected area management category ascribed by the Managing authority, as outlined in the publication: CNPPA/WCMC "Guidelines for Protected Area management categories". Gland: IUCN, 1994. (ISBN: 2-8317-0201-1).IUCN definitions:IA = Strict Nature Reserve: managed mainly for science;IB = Wilderness Area: managed mainly for wilderness protection;II = National Park: managed mainly for ecosystem protection;III = Natural Monument: managed mainly for conservation of specific natural features;IV = Habitat / Species Management Area: managed mainly for conservation through management intervention;V = Protected Landscape / Seascape: managed mainly for landscape/seascape conservation and recreation;VI = Managed Resource Protected Area: managed mainly for the sustainable use of natural ecosystems.NA = (Not applicable) - Denotes an area that does not meet the NRS criteria or the IUCN definition of a protected area but has management complimentary to the NRS.NRS_MPA: This attribute indicates whether the protected area meets the standard for inclusion in the NRSMPA or is managed for nature conservation without meeting the NRSMPA standard. For marine reserves refer to the “Guidelines for Establishing the National Representative System of Marine Protected Areas (NRSMPA)NRS_MPA code definitions:"Y" = Yes. The sea has been assessed as a protected area that meets the standard for inclusion in the NRSMPA."N" = No. The sea has been assessed as not meeting the standard for inclusion in the NRSMPA. It is managed for nature conservation without meeting the NRSMPA standard."ND" = Not Determined. The sea is managed for nature conservation although it has not been assessed to determine if it meets the standard for inclusion in the NRSMPA.GAZ_AREA: area in hectares as described in the nomination document (e.g. parliamentary gazettal), to the nearest hectare. Some protected areas do not have a specific area in the designation.GIS_AREA: area in hectares based on current spatial data and an Albers equal area projection for Australia. It is this field that is used to calculate the statistics provided in spreadsheets at: www.environment.gov.au/capad/REPT_AREA: is the same as GIS_AREA. (Previously REPT_AREA was based on the GAZ_AREA attribute and if this was a null value then the GIS_AREA was used. Due to the fact that not all received data had REPT_AREA, it was incomplete and inconsistent, so REPT_AREA is no longer used for analysis).GAZ_DATE: the first gazettal or proclamation date that established any protected area at this site. A default date of 01/01/1900 is applied for undated and unlabelled polygons supplied to the department.LATEST_GAZ: the date of the most recent gazettal or proclamation to amend the protected area. It can be the same date as the GAZ_DATE.STATE: The state is the state or territory that the protected area is located in. COM = protected areas located in Commonwealth Waters. EXT= protected areas located in Australian external territories.AUTHORITY: The Authority responsible for the management of the protected area mechanism.AUTHORITY abbreviations:DOEE = Australian Government, Department of Climate Change, Energy, the Environment and WaterGBRMPA = Great Barrier Reef Marine Park AuthorityIMG = Indigenous Management GroupNSW_DPI = NSW Department of Primary IndustriesNT_PWCNT= Parks and Wildlife Commission of the NTPIRSA = Primary Industries and Regions South AustraliaQLD_DEEDI = QLD Department of Employment, Economic Development and InnovationQLD_NPSR = Queensland Department of National Parks, Sport and RacingSA_DEWNR = South Australian Department of Environment, Water and Natural ResourcesTAS_DPIPWE = Tasmanian Department of Primary Industries, Parks, Water and EnvironmentTSRA = Torres Strait Regional AuthorityVIC_DELWP = Victorian Department of Environment, Land, Water and PlanningWA_DOF = Western Australian Department of FisheriesWA_DPAW = Western Australian Department of Parks and WildlifeDATASOURCE: Describes the source of the data for the protected area.DATASOURCE abbreviations:DOEE = Australian Government, Department of Climate Change, Energy, the Environment and WaterGBRMPA = Great Barrier Reef Marine Park AuthorityNSW_DPI = NSW Department of Primary IndustriesNT_PWCNT= Parks and Wildlife Commission of the NTPIRSA = Primary Industries and Regions South AustraliaQLD_DEEDI = QLD Department of Employment, Economic Development and InnovationQLD_NPSR = Queensland Department of National Parks, Sport and RacingSA_DEWNR = South Australian Department of Environment, Water and Natural ResourcesTAS_DPIPWE = Tasmanian Department of Primary Industries, Parks, Water and EnvironmentTSRA = Torres Strait Regional AuthorityVIC_DELWP = Victorian Department of Environment, Land, Water and PlanningWA_DOF = Western Australian Department of FisheriesWA_DPAW = Western Australian Department of Parks and WildlifeGOVERNANCE: Records the type of governance that has management and decision making responsibility.Governance code definitions: G = Government, C = Community (conserved areas including indigenous peoples or local communities) or J = Joint.COMMENTS: Extra information jurisdictions elect to supply. Due to the change in ENVIRON based categorisation rules in the 2016 version of CAPAD, it has been noted in the COMMENTS field of marine CAPAD if a record was previously included in terrestrial CAPAD.ENVIRON: A protected area gazetted as terrestrial may have a marine component and vice versa. A protected area can be 'T' terrestrial, marine 'M' or both 'B'. Terrestrial CAPAD 2016 contains 'T' and 'B' records. Marine CAPAD 2016 contains 'M' and ‘B’ records. If a record is coded as ‘B’ by the data

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally suppied.

The dataset provides a comprehensive catalogue of permanently saturated springs that have fixed locations and any associated surface expression groundwater dependent ecosystems. This precludes soaks that are not permanent, bores (because they are not natural), wells that do not have a surface expression of groundwater, and groundwater discharge along a stream-bed that is not in a fixed location. The springs dataset also includes other types of springs (e.g. springs with a non-permanent or unsaturated saturation regime), however, information on these types of springs may be limited.

The springs dataset includes comprehensive information on spring location, status (active/inactive), and grouping (complex) for all springs included in the dataset. Where available, information is also provided on physical properties, general morphology, water chemistry, floristic composition, disturbance, faunal composition, survey effort, photographic documentation, and historical descriptions. Where sufficient information was available, springs have also been given a conservation ranking at both the individual spring and complex levels.

Original field data collected from 1995 to present checked, tested and compiled by the Queensland Herbarium. The water chemistry tests were performed by the Water Laboratory, Chemistry Centre, EcoScience Precinct,QLD. Springs added to the database come from a range of people and/or agencies. Springs are added to the database when a precise location is provided as well as a description accurate enough to inform permanency of the spring. Doubtful records are kept for further assessment. Springs can be removed from the database in some occasions after field survey confirming absence. A record of deleted springs is maintained by the Queensland Herbarium.

Dataset History

This dataset was extracted on the 13th October 2016 from the Queensland government website.

Dataset Citation

Queensland Herbarium, Department of Science, Information Technology, Innovation and the Arts (2016) QLD Springs Dataset 2016. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/26030523-4eb6-4abb-8932-bee72f954303.

AbstractTaxation Statistics 2014-15 is a continental dataset providing an overview of the income and tax status of Australian individuals, companies, partnerships, trusts and funds for the 2014-15 financial year.The dataset was compiled for the annual publication, Taxation Statistics, the ATO’s key statistical report. It provides a comprehensive statistical summary of information taxpayers report to the ATO.The income tax returns of individuals, companies, super funds, partnerships and trusts.Annual returns for fringe benefits tax (FBT) and goods and services tax (GST).Business activity statements (BAS) and instalment activity statements (IAS).Schedules for rental properties, capital gains tax (CGT) and international dealings.Superannuation member contribution statements (MCS).Other information reported to the ATO in relation to excise, the pay as you go (PAYG) system, and charitable institutions.Previous versions of this dataset are available on the Australian Government open government data portal data.gov.auCurrencyDate Published: 28 March 2017Date Updated: 12 June 2024Modification Frequency: As neededData ExtentGeocentric Datum of Australia 1994 (GDA94)Spatial ExtentNorth: -9.1°South: -43.6°East: 159.1°West: 96.8°Source InformationData and Metadata are available from Taxation Statistics 2014-15 - Dataset - data.gov.auThe data was obtained from the Australian Taxation Office.Catalog Entry: Taxation Statistics 2014-15 - Dataset - Data.gov.auLineage StatementThis layer was put together using two datasets. Australian taxation and income data provided by the Australian Taxation Office (ATO), was joined to the 2011 Postal Areas shapefile provided by the Australian Bureau of Statistics (ABS).Postal AreasPostal Areas (POA) are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries exactly and should only be used for statistical purposes.Data and geography referencesSource data publication:Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2011Further information: Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2011 – Explanatory NotesSource: Australian Bureau of Statistics (ABS)Data PreparationThe CSV was joined to the POA geographies using the 4 digit postcode. For the CSV, it was exported as a file geodatabase and a new field assigned where postcodes were entered as text data to maintain the leading zeroes. The new text postcode field was then joined to the ABS POA_Name field.All data manipulations, joins, and spatial operations were performed using ArcGIS Pro 3.4.3.Data dictionaryAttribute nameDescriptionAREA_SQKMThe area in square kilometres of the postcodeCount taxable income or lossThe number of individuals reporting taxable income or loss in the postcodeAverage taxable income or lossThe average taxable income or loss of the postcodeMedian taxable income or lossThe median taxable income or loss of the postcodeCount of salary or wagesThe number of individuals reporting salary or wages in the postcodeAverage salary and wagesThe average salary or wages of the postcodeMedian salary and wagesThe median salary or wages of the postcodeCount net rentThe number of individuals reporting net rent in the postcodeAverage net rentThe average net rent in the postcodeMedian net rentThe median net rent in the postcodeCount total income or lossThe number of individuals reporting total income or loss in the postcodeAverage total income or lossThe average total income or loss of the postcodeMedian total income or lossThe median total income or loss of the postcodeCount total deductionsCount of individuals reporting total deductions in the postcodeAverage total deductionsThe average total deductions of the postcodeMedian total deductionsThe median total deductions of the postcodeCount total business incomeThe number of individuals reporting business income in the postcodeAverage total business incomeThe average total business income in the postcodeMedian total business incomeThe median total business income in the postcodeCount total business expensesThe number of individuals reporting business expenses in the postcodeAverage total business expensesThe average business expenses in the postcodeMedian total business expensesThe median business expenses in the postcodeCount net taxThe number of individuals with net tax in the postcodeAverage net taxThe average net tax in the postcodeMedian net taxThe median net tax in the postcodeCount super total accounts balanceThe total number of super accounts in the postcodeAverage super total accounts balanceThe average balance of super accounts in the postcodeMedian super total accounts balanceThe median balance of super accounts in the postcodePostcodesThe postcode affiliated with that areaSHAPE_LengthLength of polygon outlineSHAPE_AreaArea of the polygon.ContactAustralian Taxation Office, taxstats@ato.gov.au

This dataset presents the footprint of female cancer incidence statistics in Australia for all cancers combined and the 11 top cancer groupings (breast, cervical, colorectal, leukaemia, lung, lymphoma, melanoma of the skin, ovary, pancreas, thyroid and uterus) and their respective ICD-10 codes. The data spans the years 2006-2010 and is aggregated to Statistical Area Level 4 (SA4) from the 2011 Australian Statistical Geography Standard (ASGS). Incidence data refer to the number of new cases of cancer diagnosed in a given time period. It does not refer to the number of people newly diagnosed (because one person can be diagnosed with more than one cancer in a year). Cancer incidence data come from the Australian Institute of Health and Welfare (AIHW) 2012 Australian Cancer Database (ACD).

AbstractTaxation Statistics 2019-20 is a continental dataset providing an overview of the income and tax status of Australian individuals, companies, partnerships, trusts and funds for the 2019-20 financial year.The dataset was compiled for the annual publication, Taxation Statistics, the ATO’s key statistical report. It provides a comprehensive statistical summary of information taxpayers report to the ATO. It includes information sourced from:The income tax returns of individuals, companies, super funds, partnerships and trusts.Annual returns for fringe benefits tax (FBT) and goods and services tax (GST).Business activity statements (BAS) and instalment activity statements (IAS).Schedules for rental properties, capital gains tax (CGT) and international dealings.Superannuation member contribution statements (MCS).Other information reported to the ATO in relation to excise, the pay as you go (PAYG) system, and charitable institutions.Previous versions of this dataset are available on the Australian Government open government data portal data.gov.auCurrencyDate Published: 01 August 2022Date Updated: 13 September 2024Modification Frequency: As neededData ExtentGeocentric Datum of Australia 1994 (GDA94)Spatial ExtentNorth: -9.1°South: -43.6°East: 159.1°West: 96.8°Source InformationData and Metadata are available from Taxation Statistics 2019-20 - Dataset - data.gov.auThe data was obtained from the Australian Taxation Office.Catalog Entry: Taxation Statistics 2019-20 - Dataset - Data.gov.auLineage StatementThis layer was put together using two datasets. Australian taxation and income data provided by the Australian Taxation Office (ATO), was joined to the 2016 Postal Areas shapefile provided by the Australian Bureau of Statistics (ABS).Postal AreasPostal Areas (POA) are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries exactly and should only be used for statistical purposesData and geography referencesSource data publication: Australian Statistical Geography Standard (ASGS) Edition 2 - Postal AreasFurther information: Australian Statistical Geography Standard (ASGS) Edition 2 - Non ABS StructuresSource: Australian Bureau of Statistics (ABS)Data PreparationThe CSV was joined to the POA geographies using the 4 digit postcode. For the CSV, it was exported as a file geodatabase and a new field had to be generated where the postcodes were entered as text data to maintain the leading zeroes. The new text postcode field was then joined to the ABS attribute field POA_Name.All data manipulations, joins, and spatial operations were performed using ArcGIS Pro 3.4.3.Data dictionaryAttribute nameDescriptionPostcodesThe postcode affiliated with that areaAREA_SQKMThe area in square kilometres of the postcodeNumber of individuals lodging an income tax returnThe number of individuals lodging a tax return in that postcodeCount taxable income or lossThe number of individual reports of taxable income or loss in the postcodeAverage taxable income or lossThe average taxable income or loss of the postcodeMedian taxable income or lossThe median taxable income or loss of the postcodeProportion with salary or wagesThe proportion of individuals reporting salary or wage in the postcodeCount salary or wagesThe number of individuals reporting salary or wages in the postcodeAverage salary or wagesThe average salary or wages of the postcodeMedian salary or wagesThe median salary or wages of the postcodeProportion with net rentThe proportion of individuals reporting net rent in the postcodeCount net rentThe number of individuals reporting net rent in the postcodeAverage net rentThe average cost of net rent in the postcodeMedian net rentThe median net rent in the postcodeCount total income or lossThe number of individuals reporting total income or loss in the postcodeAverage total income or lossThe average total income or loss of the postcodeMedian total income or lossThe median total income or loss of the postcodeCount total deductionsCount of individuals reporting total deductions in the postcodeAverage total deductionsThe average total deductions of the postcodeMedian total deductionsThe median total deductions of the postcodeProportion with total business incomeThe proportion of individuals reporting business income in the postcodeCount total business incomeThe number of individuals reporting business income in the postcodeAverage total business incomeThe average total business income in the postcodeMedian total business incomeThe median total business income in the postcodeCount total business expensesThe number of individuals reporting business expenses in the postcodeAverage total business expensesThe average business expenses in the postcodeMedian total business expensesThe median business expenses in the postcodeProportion with net taxThe proportion of individuals with net tax in the postcodeCount net taxThe number of individuals with net tax in the postcodeAverage net taxThe average net tax in the postcodeMedian net taxThe median net tax in the postcodeCount super total accounts balanceThe total number of super accounts in the postcodeAverage super total accounts balanceThe average balance of super accounts in the postcodeMedian super total accounts balanceThe median balance of super accounts in the postcodeProportion with total business expensesThe proportion of individuals reporting business expenses in the postcodeSHAPE_LengthLength of polygon outlineSHAPE_AreaArea of the polygon.ContactAustralian Taxation Office, taxstats@ato.gov.au

This dataset presents the footprint of cancer incidence statistics in Australia for all cancers combined and the 5 top cancer groupings (breast - female only, colorectal, lung, melanoma of the skin and prostate) and their respective ICD-10 codes. The data spans the years 2006-2010 and is aggregated to Statistical Area Level 3 (SA3) from the 2011 Australian Statistical Geography Standard (ASGS). Incidence data refer to the number of new cases of cancer diagnosed in a given time period. It does not refer to the number of people newly diagnosed (because one person can be diagnosed with more than one cancer in a year). Cancer incidence data come from the Australian Institute of Health and Welfare (AIHW) 2012 Australian Cancer Database (ACD).