AndreaBozzo/ceres-open-data-index huggingface dataset:
LGA-P39b Non-School Qualification: Field of Study by Age by Sex-Census 2016

LGA based data for Non-School Qualification: Field of Study by Age by Sex, in Place of Enumeration Profile (PEP), 2016 Census. Count of persons aged 15 years and over with a qualification (excludes overseas visitors). Excludes persons with a qualification out of the scope of the Australian Standard Classification of Education (ASCED). P39 is broken up into three sections (P39a - P39c), this section contains 'Females Management and Commerce Age 35-44 years' - 'Persons Total Age 45-54 years'. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. 
Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
For more information visit the data source: http://www.abs.gov.au/census. 

Tags: 2016, age, census, education, field of study, non-school, p39b, pep, place of enumeration profile, qualification, sex, study
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
LGA-G27 Family Blending-Census 2016

LGA based data for Family Blending, in General Community Profile (GCP), 2016 Census. Count of couple families with children. Classifies couple families based on the parent-child relationships within them. Temporarily absent children are taken into consideration when classifying families. Excludes 'Couple families with no children', 'One parent families' and 'Other families'. Excludes families in: 'Non-family/Non-classifiable households', 'Non-private dwellings' and 'Migratory, off-shore and shipping' SA1s.  Excludes overseas visitors. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. 
 Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
 For more information visit the data source: http://www.abs.gov.au/census.

Tags: 2016, census, child, family blending, g27, gcp, general community profile, lga, parent, relationship
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
PHIDU - Admissions - Principal Diagnosis: Females  (PHN) 2016-2017

This dataset, released November 2018, contains data relating to female hospital admissions during 2016-2017 by principal diagnosis of: Parasitic disease, cancer, Blood-organ disease, metabolic disease, mental health disease, nervous system disease, eye disease, ear disease, circulatory system disease, respiratory system disease, digestive system disease, skin disease, musculoskeletal disease, genitourinary system disease, perinatal condition, congenital deformations, pregnancies and external causes. The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).
There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.
For more information please see the data source notes on the data. 
Source: Compiled by PHIDU using data from the Australian Institute of Health and Welfare, supplied on behalf of Stateand Territory health departments for 2016/17; and the ABS Estimated Resident Population, 30 June 2016.
AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Tags: HEALTH SCIENCES, Public health
Organization: Torrens University Australia - Public Health Information Development Unit
TAS DSG - Tasmania Crash Statistics (Point) 2010-2020

This dataset contains all vehicular crashes on Tasmanian roads reported by Tasmanian police, or in the case of property damage only, crashes reported by the public. The data covers the crashes over the period of 2010/01/01 to 2020/12/07.
The original dataset was provided to AURIN by the Tasmanian Department of State Growth. 
AURIN has spatialised the data with PostGIS, from the geographic coordinates in the original dataset.

Tags: Traffic Accidents, Transport
Organization: Government of Tasmania - Department of State Growth
City of Melbourne CLUE Business Establishments by CLUE Industries (Block) 2006

This dataset was collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data shows the number of business establishments per city (CLUE) block, classified by their CLUE industry (from ANZSIC) and small area allocation. The data is aggregated to the 2016 Blocks for CLUE Boundaries and covers the year period of 2006.
A business establishment is defined as a 


Commercial occupant in a building


Separate land use


Any permanent presence of economic activity in accordance with standard Industry classification (ANZSIC).


Hence, if one organisation has its presence in several buildings in the CLUE area, each time it will be counted as a separate establishment. Consequently, the count of establishments presented in CLUE represents the number of locations, rather than 'enterprises'.
For more information please visit the City of Melbourne CLUE Portal and ABS ANZSIC Page.
Please note: 


AURIN has spatially enabled the data acquired through the City of Melbourne Open Data Portal.


The individual yearly tables have been extracted from the archived 2002-2017 tables.


The data in this table is a snapshot and not live.



Tags: 2006, business, census, clue, establishment, industry, land, melbourne, use
Organization: Local Government of Victoria - City of Melbourne
ABS - Jobs In Australia - Employee Jobs (SA4) 2011-2018

This dataset presents aggregated data regarding employee jobs within the relevant statistical regions, including the number of employee jobs and median employee income per job by sex, classified by Statistical Area Level 4 (SA4). The data spans from 2011-12 to 2017-18 financial year and is aggregated to the 2016 SA4 boundaries.
Jobs in Australia provide aggregate statistics and are sourced from the Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. An 'employee Job' refers to a job for which the occupant receives remuneration in wages, salary, payment in kind, or piece rates. This excludes self-employment jobs held by Owner-Managers of Unincorporated Enterprises (OMUE).
The job counts in this release differ from the filled job estimates from other sources such as the Australian Labour Account and the Labour Force Australia. The Jobs in Australia release provides insights into all jobs held throughout the year, while the Labour Account data provides the number of filled jobs at a point-in-time each quarter (and annually for the financial year reference period), and Labour Force Survey data measures the number of people employed each month. 
For more information on the release please visit the Australian Bureau of Statistics
This release provides statistics on the number and nature of jobs, the people who hold them, and their employers. These statistics can be used to understand regional labour markets or to identify the impact of major changes in local communities. The release also provides new insights into the number of jobs people hold, the duration of jobs, and the industries and employment income of concurrent jobs.
The scope of these data includes individuals who submitted an individual tax return to the Australian Taxation Office (ATO), individuals who had a Pay As You Go (PAYG) payment summary issued by an employer and their employers.
AURIN has spatially enabled the original data. The following additional changes were made:


Where data was not published for confidential reasons, "np" in the original data, the records have been set to null.


Total values may be higher than the sum of the published components due to this confidentialisation.



Tags: COMMERCE, Demography, Demography not elsewhere classified, ECONOMICS, HUMAN SOCIETY, Human resources, MANAGEMENT, Other economics, TOURISM AND SERVICES, industrial relations
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
VCGLR - Liquor Venues (Point) February 2019

This dataset includes liquor venues by street address, suburb or town, venue name, licence number or licence category. Liquor licence data is updated directly from the Victorian Commission for Gambling and Liquor Regulation's (VCGLR) licensing database daily.
For more information visit the VCGLR's website.
Please note:

AURIN has extracted venue lists from the VCGLR's interactive map of Victoria's liquor venues and spatially enabled them on the 8th of March 2019.


Tags: gaming, licence, population
Organization: Government of Victoria - Victorian Commission for Gambling and Liquor Regulation
Ookla - Network Performance - Mobile (Polygon) Q3 2020

This data set provides mobile (cellular) network performance, allocated to zoom level 16 web mercator tiles (approximately 610.8 meters by 610.8 meters at the equator). Download speed, upload speed, and latency are collected via the Speedtest by Ookla applications for Android and iOS and averaged for each tile. Measurements are filtered to results containing GPS-quality location accuracy.
For more information please see the Ookla Github repository or the Registry of Open Data on AWS.
Ookla licenses data to NGOs and educational institutions to fulfill its mission: to help make the internet better, faster and more accessible for everyone. Ookla hopes to further this mission by distributing the data to make it easier for individuals and organizations to use it for the purposes of bridging the social and economic gaps between those with and without modern Internet access.
AURIN has generated a subset corresponding to the intersection with the extent of the 2016 Greater Capital City Statistical Areas (GCCSA) boundaries from the ABS Australian Statistical Geography Standard (ASGS). It was then reprojected from EPSG 4326 (WGS84) to 4283 (GDA94).
Additional columns have been added corresponding to the matching boundaries of the 2016 ABS Statistical Area Levels 2, 3 and 4, and the 2020 Local Government Areas. These were spatially joined using the centroid of each polygon, and therefore, should only be used as an approximation. Furthermore, grid cells residing outside of these boundaries, such as offshore or over rivers, are assigned a null value in these columns.

Organization: Ookla
PHIDU - Prevalence of Chronic Diseases (PHN) 2011-2012

This dataset, released October 2014, contains for the time period of 2011-2012 the Estimated population, aged 18 years and over with diabetes mellitus; Estimated population aged 18 years and over with high blood cholesterol; Estimated male population with mental and behavioural problems; Estimated female population with mental and behavioural problems; Estimated population with mental and behavioural problems; Estimated population aged 2 years and over with circulatory system diseases; Estimated population with respiratory system diseases; Estimated population with musculoskeletal system diseases. The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).
There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.
For more information please see the data source notes on the data. 
Source: Estimates for Population Health Areas (PHAs) are modelled estimates and were produced by the ABS;estimates at the LGA and PHN level were derived from the PHA estimates. 
AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Tags: HEALTH SCIENCES, Public health
Organization: Torrens University Australia - Public Health Information Development Unit
LGA-P42b Industry of Employment by Occupation-Census 2016

LGA based data for Industry of Employment by Occupation, in Place of Enumeration Profile (PEP), 2016 Census. Count of employed persons aged 15 years and over (excludes overseas visitors). P42 is broken up into two sections (P42a - P42b), this section contains 'Total Occupation Managers' - 'Total Total'. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. 
Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
For more information visit the data source: http://www.abs.gov.au/census. 

Tags: 2016, census, employment, industry, occupation, p42b, pep, place of enumeration profile, work
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
SA4-P35 Dwelling Internet Connection By Dwelling Structure-Census 2016

SA4 based data for Dwelling Internet Connection by Dwelling Structure, in Place of Enumeration Profile (PEP), 2016 Census. Count of occupied private dwellings. Excludes 'Visitors only' and 'Other non-classifiable' households. Records whether any member of the household accesses the internet from the dwelling. This includes accessing the internet through a desktop/laptop computer, mobile or smart phone, tablet, music or video player, gaming console, smart TV or any other devices.  It also includes accessing through any type of connection for example ADSL, fibre, cable, wireless, satellite and mobile broadband (3G/4G). The data is by SA4 2016 boundaries. Periodicity: 5-Yearly. 
 Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
 For more information visit the data source: http://www.abs.gov.au/census.

Tags: 2016, census, dwelling structure, internet, internet connection, p35, pep, place of enumeration profile
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
AIHW - Maternity Indicators - Non-instrumental Vaginal Birth for Selected Women Giving Birth for the First Time (%) (SA3) 2014-2016

This dataset presents the footprint of the percentage of selected women giving birth for the first time who gave birth by non-instrumental vaginal birth, by the mother's usual residence. This has been calculated with the number of selected females giving birth for the first time who gave birth by non-instrumental vaginal birth, divided by all selected females, and multiplied by 100. The data spans the years of 2014-2016 and is aggregated to Statistical Area Level 3 (SA3) geographic areas from the 2011 Australian Statistical Geography Standard (ASGS).
Women included are those who gave birth for the first time and met all of the following criteria:


Aged between 20 and 34.


Gestational age at birth between 37 and 41 completed weeks.


Pregnancy has one baby only (singleton).


The presentation of the baby is vertex (baby's head was at the cervix).


The data is sourced from the National Perinatal Data Collection (NPDC), which is a national population-based cross-sectional collection of data on pregnancy and childbirth. The data are based on births reported to the perinatal data collection in each state and territory in Australia. Midwives and other birth attendants, using information obtained from mothers and from hospital or other records, complete notification forms for each birth. A standard de-identified extract is provided to the Australian Institute of Health and Welfare (AIHW) on an annual basis to form the NPDC.
For further information about this dataset, please visit:


Australian Institute of Health and Welfare - National Core Maternity Indicators Data Tables.


Metadata Online Registry Entry.


Please note:


AURIN has spatially enabled the original data.


A birth is defined as an event in which a baby comes out of the uterus after a pregnancy of at least 20 weeks gestation or weighing 400 grams or more.


A non-instrumental vaginal birth is one in which the baby is born through the vagina without the assistance of instruments (vacuum or forceps).


Non-instrumental vaginal births include spontaneous vaginal and vaginal breech.


Data for selected women criteria, parity, were not available from Victoria for 2009.


Data for Tasmania from 2004 to 2012 were not available. For Tasmania from 2005 to 2012, presentations via caesarean births were not reported by hospitals still using paper-based form. Where a caesarean section occurred the presentation was recorded as ‘Not stated’. Presentations via caesarean births were included in the paper-based form from 1 January 2013. The year 2004 was not included in this analysis.


Data for Statistical Local Area Level 3 (SA3) of mother's usual residence reported using a 3-year aggregate, 2014-2016.


The sum of the reported 'Grouped by' values may not equal the Australia total.



Tags: health, population
Organization: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare
PHIDU - Potentially Preventable Admissions - All Conditions  (PHN) 2016-2017

This dataset, released November 2018, contains data on the number of All potentially preventable hospitalisations - Vaccine-preventable, Acute and Chronic conditions, 2016/17. The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).
There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.
For more information please see the data source notes on the data. 
Source: Compiled by PHIDU using data from the Australian Institute of Health and Welfare, supplied on behalf of Stateand Territory health departments for 2016/17; and the ABS Estimated Resident Population, 30 June 2016.
AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Tags: HEALTH SCIENCES, Public health
Organization: Torrens University Australia - Public Health Information Development Unit
AIHW - Patient Experiences - Adults who Did Not See or Delayed Seeing a Dentist, Hygienist or Dental Specialist due to Cost (%) (PHN) 2014-2017

This dataset presents the footprint of the percentage of adults who did not see or delayed seeing a dentist, hygienist or dental specialist due to cost in the preceding 12 months. The data spans the years of 2014-2017 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).
The data is sourced from the Australian Bureau of Statistics (ABS) 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. It also includes data from previous Patient Experience Surveys conducted in 2013-14, 2014-15 and 2015-16. The Patient Experience Survey is conducted annually by the ABS and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patient Experience Survey collects data on persons aged 15 years and over, who are referred to as adults for this data collection.
For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Patient experiences in Australia Data Tables.
Please note:


AURIN has spatially enabled the original data using the Department of Health - PHN Areas.


Percentages are calculated based on counts that have been randomly adjusted by the ABS to avoid the release of confidential data.


As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the ABS using standard error estimates of the proportion.


Some of the patient experience measures for 2016-17 have age-standardised rates presented. Age-standardised rates are hypothetical rates that would have been observed if the populations studied had the same age distribution as the standard population.


Crude rates are provided for all years. They should be used for understanding the patterns of actual service use or level of experience in a particular PHN.


The Patient Experience Survey excludes persons aged less than 15 years, persons living in non-private dwellings and the Indigenous Community Strata (encompassing discrete Aboriginal and Torres Strait Islander communities).


Data for Northern Territory should be interpreted with caution as the Patient Experience Survey excluded the Indigenous Community Strata, which comprises around 25% of the estimated resident population of the Northern Territory living in private dwellings.


NP - Not available for publication. The estimate is considered to be unreliable. Values assigned to NP in the original data have been set to null.



Tags: health, population
Organization: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare
SA4-G27 Family Blending-Census 2016

SA4 based data for Family Blending, in General Community Profile (GCP), 2016 Census. Count of couple families with children. Classifies couple families based on the parent-child relationships within them. Temporarily absent children are taken into consideration when classifying families. Excludes 'Couple families with no children', 'One parent families' and 'Other families'. Excludes families in: 'Non-family/Non-classifiable households', 'Non-private dwellings' and 'Migratory, off-shore and shipping' SA1s.  Excludes overseas visitors. The data is by SA4 2016 boundaries. Periodicity: 5-Yearly. 
 Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.
 For more information visit the data source: http://www.abs.gov.au/census.

Tags: 2016, census, child, family blending, g27, gcp, general community profile, parent, relationship, sa4
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics