AndreaBozzo/ceres-open-data-index huggingface dataset:
SA2 Estimated Aboriginal or Torres Strait Islander Australians 2016

This dataset presents the estimates of the Aboriginal and Torres Strait Islander, non-Indigenous and total populations of Australia for the year ending at 30 June 2016, based on results of the 2016 Census of Population and Housing. The data is by Statistical Area Level 2 (SA2) regions following the 2016 Australian Statistical Geography Standard (ASGS).
The Aboriginal and Torres Strait Islander population of Australia comprises people who are of Aboriginal origin, Torres Strait Islander origin or both Aboriginal and Torres Strait Islander origin. The Commonwealth definition of an Aboriginal and/or Torres Strait Islander person is:


a person of Aboriginal and/or Torres Strait Islander descent who;


identifies as being of Aboriginal and/or Torres Strait Islander origin and who is;


accepted as such by the community with which the person associates.


This data is Australian Bureau of Statistics (ABS) data (catalogue number: 3238.0.55.001) used with permission from the ABS.
For more information please visit the ABS Explanatory Notes.
Please note: 


AURIN has spatially enabled the original data.


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



Tags: Australia, aboriginal, aus, indigenous, population
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
QPS - Reported Offences Number by Division (Polygon) Jan 2001 - Aug 2018

This dataset presents the footprint of the number of reported offences in Queensland, by month. The data is aggregated to Queensland Police Service (QPS) Divisions and spans the years January 2001 to August 2018.
For further information about this dataset, please visit the QPS - Division Reported Offences Number.
Please note:


AURIN has spatially enabled this data, using the QPS Divisions.


Data is made available through a AURIN-QCIF-RIDL collaboration.


Care should be taken when comparing monthly statistics. For example, January 2014 compared with February 2014. A more accurate comparison would be obtained by comparing a longer time series, for example, one calendar year to the next, as this will account for seasonal variations.



Tags: authority
Organization: Queensland Police Service
CCD-B21 Method of Travel to Work by Sex-Census 1996

Census Collection District (CCD) based data for Method of Travel to work by Sex, in Basic Community Profile, 1996 Census. Count of employed persons. The data is by CCD 1996 boundaries. Periodicity: 5-Yearly. 
This data is ABS data (geographic boundary cat. no. 1261.0.30.001 &amp; census dictionary cat. no. 2901.0) used with permission from the Australian Bureau of Statistics. 
For more information visit  the ABS .

Tags: 1996, b21, basic community profile, bcp, census, transport, travel method, work
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
ABS - Socio-Economic Indexes for Areas (SEIFA) - The Index of Economic Resources (SA2) 2011

Socio-Economic Indexes for Areas (SEIFA) is a product developed by the ABS that ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes are based on information from the five-yearly Census. SEIFA 2011 is the latest version of this product and consists of four indexes. The Index of Economic Resources (IER) focuses on the financial aspects of relative socio-economic advantage and disadvantage, by summarising variables related to income and wealth. This index excludes education and occupation variables because they are not direct measures of economic resources. It also misses some assets such as savings or equities which, although relevant, could not be included because this information was not collected in the 2011 Census. Data last updated: 28th March 2013. Users of this data are advised to carefully read the accompanying information on the SEIFA web page and in the Technical Paper.
SEIFA Homepage
SEIFA Technical Paper
 For further information about these and related statistics, contact the National Information and Referral Services on 1300 135 070. Periodicity: 5-Yearly.

Tags: advantage, disadvantage, ier, seifa, socio-economic
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
PHIDU - Admissions - Principal Diagnosis: Persons  (PHN) 2017-2018

This dataset, released June 2020, contains data relating to hospital admissions during 2017-2018 by a 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 2017/18; and the average of the ABS Estimated Resident Population, 30 June 2017 and 30 June 2018.
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
GCCSA-G44a Labour Force Status by Sex of Parents by Age of Dependent Children for Couple Families-Census 2016

GCCSA based data for Labour Force Status by Sex of Parents by Age of Dependent Children for Couple Families, in General Community Profile (GCP), 2016 Census. Count of dependent children in couple families. Comprises children aged under 15 years and dependent students aged 15-24 years who were present at their usual residence on Census Night. Comprises couple families with both parents present at their usual residence on Census Night. Excludes same-sex couples. G44 is broken up into 6 sections (G44a - G44f), this section contains 'Dependent children Aged 0-4 years Female parent Employed worked Full-time Male parent Employed Worked Full-time' - 'Dependent children Aged 5-9 years Female parent Total Employed Male Parent Unemployed Looking For Total'. The data is by GCCSA 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, couple family, dependent children, g44a, gcp, general community profile, labour force, parent, sex, work status
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
PHIDU - Age Distribution - Broad Age Groups: Persons (PHA) 2019

This dataset, released September 2020, contains usual resident population by broad age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years, 2019. The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).
Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.
For more information please see the data source notes on the data. 
Source: Compiled by PHIDU based on ABS 3235.0 Population by Age and Sex, Regions of Australia, 30 June 2019. 
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: Demography, HEALTH SCIENCES, HUMAN SOCIETY, Public health
Organization: Torrens University Australia - Public Health Information Development Unit
SA1-P43a Occupation by Age by Sex-Census 2016

SA1 based data for Occupation by Age by Sex, in Place of Enumeration Profile (PEP), 2016 Census. Count of employed persons aged 15 years and over (excludes overseas visitors). P43 is broken up into two sections (P43a and P43b), this section contains 'Males 15-19 years Occupation Managers' - 'Females Total Total'. The data is by SA1 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, employment, occupation, p43a, pep, place of enumeration profile, sex
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
Main Roads WA - Bike Count Sites 2017/18

This dataset presents the location of bike count sites in the Perth, Metropolitan Area. This dataset provides the volumes for the latest count year. Bike volumes are collected on a continuous basis at permanent sites on principal shared paths. The Integrated Road Information System (IRIS) Reporting Centre provides a number of other reports. The Bike Count Sites are owned and managed by Main Roads Western Australia (MRWA).
This data was extracted on August 2018.
For more information please visit the MRWA Open Data Portal.

Tags: WA, Western Australia, bicycle, count, points, road assets, sites, traffic, transportation, volume
Organization: Government of Western Australia - Main Roads Western Australia
GCCSA-G46a Non-School Qualification-Level of Education by Age by Sex-Census 2016

GCCSA based data for Non-School Qualification: Level of Education by Age by Sex, in General Community Profile (GCP), 2016 Census. Count of persons aged 15 years and over with a qualification. Excludes persons with a qualification out of the scope of the Australian Standard Classification of Education (ASCED). Excludes schooling up to year 12. G46 is broken up into two sections (G46a-G46b), this section contains 'Males Postgraduate Degree Level Age 15 24 years' - 'Persons Postgraduate Degree Level Age 25-34 years'. The data is by GCCSA 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, g46a, gcp, general community profile, non-school, qualification, sex
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
Mobility Australia - Queensland Monthly Ferry Origin-Destination Flow (SA2) 2021

This dataset estimates human mobility through origin destination (OD) movement flow among the Statistical Area 2 (SA2) regions in Queensland (QLD), connected by public transport (PT) networks. The SA2 regions of Queensland connected by buses, trains, trams and ferries have been used to evaluate OD movement flows. The passenger OD movement data among different stations (or the station-based OD flow) are first estimated using a statistical estimation methodology. The stations-based OD flow data are then translated into region-based OD matrices using the state-of-art method. For more information please see the original metadata file here.
Human mobility data is a key ingredient in various areas and domains of research including epidemiology, policy and administration, criminology, transportation, logistics and supply chains, environmental management and, pollution and contamination. High quality human mobility data provided by telecommunication companies collected from call data records (CDRs) is available at prohibitive cost with restrictive licensing, keeping it out of reach for the majority of research community. On the other hand, there is an abundance of high-quality public data, reporting different aspects of mobility. Examples are the public transport patronage and information about the usage of the Australian road network. These datasets are collected by different organisations and government departments and are presented in various formats. For instance, data may be collected at different spatial (e.g. at state or postcode levels) and temporal scales and be presented in the form of passenger counts or aggregated movement flows. This dataset addresses the general lack of national scale comprehensive human mobility dataset in Australia by transforming available mobility data into a consistent format that is suitable for analysis in a broad range of research areas. Merging the various individual datasets into Australia's first comprehensive, national-scale human mobility data asset drastically improves the quality and coverage of existing datasets.
The Mobility Australia project received investment (https://doi.org/10.47486/DP702) from the Australian Research Data Commons (ARDC). The ARDC is funded by the National Collaborative Research Infrastructure Strategy (NCRIS).
The original data tables were structured in a matrix-like format. AURIN employed a methodology to merge diverse datasets into a comprehensive one, categorising based on transportation types (e.g., trains, buses, rails, ferries), years (e.g., 2019, 2020, 2021, etc.), and temporal scales (e.g., weekly, monthly, yearly). Subsequently, AURIN spatially enabled the original data by employing the 2021 edition of the Australian Statistical Geography Standard (ASGS). The flow between origin and destination pairs is visually represented using line geometry.

Tags: human mobility, network analyses, transit networks, transport, urban
Organization: CSIRO
City of Melbourne CLUE Business Establishments by ANZSIC Industries (Block) 2008

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 ANZSIC1 industry and small area allocation. The data is aggregated to the 2016 Blocks for CLUE Boundaries and covers the year period of 2008.
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: 2008, business, census, clue, establishment, industry, land, melbourne, use
Organization: Local Government of Victoria - City of Melbourne
LGA15 Age Distribution-Broad Age Groups - 2015

The number of People in broad age groups (0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years) and their proportion of the total population, 2015 (all entries that were classified as not shown, not published or not applicable were assigned a null value; no data was provided for Maralinga Tjarutja LGA, in South Australia). The data is by LGA 2015 profile (based on the LGA 2011 geographic boundaries).
Source: Compiled by PHIDU based on the (Australian Bureau of Statistics (ABS) Estimated Resident Population, 30 June 2015. 

Tags: age distribution, broad age distributions, lga profile 2015, phidu, public health information development unit, torrens university australia, total population, tua
Organization: Torrens University Australia - Public Health Information Development Unit
SA3-based B44B Industry of Employment by Occupation as at 2011-08-11

SA3 based data for Industry of Employment by Occupation, for 2011 Census. Count of employed persons aged 15 years and over on Census night based on place of usual residence. Data sourced from: http://www.abs.gov.au/census. For further information about these and related statistics, contact the National Information and Referral Services on 1300 135 070. Periodicity: 5-Yearly.

Tags: census
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
SA1-P28 Total Household Income (Weekly) by Household Composition-Census 2016

SA1 based data for Total Household Income (Weekly) by Household Composition, in Place of Enumeration Profile (PEP), 2016 Census. Count of occupied private dwellings. Total Household Income (Weekly) is calculated by summing the personal incomes reported by all household members aged 15 years and over. Excludes 'Other non-classifiable' households. Comprises 'Visitors only', 'Lone person' and 'Group households'. The data is by SA1 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, household composition, household income, p28, pep, place of enumeration profile, sa1, weekly income
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
CER - Small-scale Installations - Solar Water Heater - Heat Pump (POA) 2001-Jun 2021

This dataset presents the footprint of the number of installations of solar water heater (SWH) air source heat pump systems. The data spans the months from January 2020 to June 2021 and includes the total over the months from 2001 to 2019. The data is aggregated to Postal Areas (POAs) from the 2016 Australian Statistical Geography Standard (ASGS).
Every month the Clean Energy Regulator (CER) publishes small-scale renewable energy installation data files. These data files provide a list of small generation units (SGU) (small-scale solar panel, wind and hydro systems) and kW capacity by installed postcode, and SWH and air source heat pumps by installed postcode. The data represents all systems that have had certificates validly created against them. The data includes new installations, upgrades to existing systems and stand-alone (off-grid) systems. This data is not publicly available via the Renewable Energy Certificate (REC) Registry and does not include systems that are pending registration or have been failed by the CER.
For further information about this dataset, visit the data source:Clean Energy Regulator - Postcode Data for Small-scale Installations.
Please note:


A 12 month creation period for registered persons to create small-scale technology certificates applies under the Renewable Energy (Electricity) Act 2000. Therefore the 2019 and 2020 figures will continue to rise due to the 12 month creation period.


Small-scale technology certificates are calculated based on the life of the system. This differs for solar hot water heaters and small generation units (solar panels, wind and hydro). 


This data is current as at 30-06-2021.


Further information can be found at theRenewable Energy Target FAQ.


Air source heat pumps were introduced into the Small-scale Renewable Energy Scheme in 2005 as such there is no installation data available pre-2005 for this fuel source.
 AURIN has made the following change to the original data:


Spatially enabled the original data by joining the data with the 2016 ASGS POAs



Tags: BUILT ENVIRONMENT AND DESIGN, Climate change science, Climate change science not elsewhere classified, Design, EARTH SCIENCES, ENVIRONMENTAL SCIENCES, Environmental management, Sustainable design
Organization: Government of the Commonwealth of Australia - Clean Energy Regulator
AIHW - Mothers and Babies - Teenage Mothers who Gave Birth (PHN) 2016

This dataset presents the footprint of the number and per cent of teenage mothers who gave birth (aged between 15 and 19), by the mother's usual place of residence. The data spans the year of 2016 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 Institute of Health and Welfare (AIHW) National Perinatal Data Collection (NPDC). The NPDC began in 1991 and is a collaborative effort by the AIHW and state and territory health departments. Perinatal data are collected for each birth in each state and territory, usually by midwives and other birth attendants. The data are collated by the relevant state or territory health department and a standard de-identified extract is provided to the AIHW on an annual basis to form the NPDC. The NPDC covers both live births and stillbirths, where gestational age is at least 20 weeks or birth weight is at least 400 grams, except in Victoria and Western Australia, where births are included if gestational age is at least 20 weeks or, if gestation is unknown, birthweight is at least 400 grams.
The Mothers and Babies data accompanies the Australia's Mothers and Babies 2016 - In Brief Report.
For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - Australia's Mothers and Babies 2016 Data Tables.
Please note:


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


PHN is derived from Statistical Area Level 2 (SA2) of the ABS Australian Statistical Geography Standard Edition 2011. Numbers may not sum to totals due to rounding error.


The data only includes a small number of mothers aged less than 15.


Denominators are based on the estimated resident population of females aged 15-19 by state and territory and PHN.


Excludes mothers not usually resident in Australia or whose SA2 of usual residence was 'Not stated'.



Tags: health, population
Organization: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare
QED - Home Education Register (POA) 2016-2017

This dataset presents the footprint of home education registrations in Queensland. The data is aggregated to Postal Areas (POAs) from the 2016 Australian Statistical Geography Standard (ASGS). The data spans the years of 2016-2017.
In Queensland, registration for home education is a legal option for the provision of your child's education. Home education means the education of the child provided by one or both of the child's parents, or a registered teacher, primarily at the child's usual place of residence.
For further information about this dataset, please visit the Queensland Department of Education - Home Education Registrations.
Please note:


AURIN has spatially enabled this data using the 2016 ASGS POAs.


Data is made available through a AURIN-QCIF-RIDL collaboration.


Some data has no geometry as the postcode either did not exists in the 2011/2016 datasets (is either too new or too old and has been superseded), or was either a PO Box, LVR or similar type postcode and does not have a spatial area.


Postcode information is based on a student's postal address. Some postal addresses are external to Queensland which may be due to travel and other reasons.


Age is at 1st July each year.


Active registrations as at August collection date each year.



Tags: education
Organization: Government of Queensland - Department of Education