AndreaBozzo/ceres-open-data-index huggingface dataset:
DSS - Quarterly Payment Recipients (LGA) June 2019

This dataset presents counts of payment recipients by payment type for the quarter ending June 2019. The data is based on the recipient's geocoded address aggregated by Local Government Area (LGA) from the Australian Statistical Geography Standard (ASGS) 2018.
The Department of Social Services (DSS) is the Australian Government's lead agency in the development and delivery of social policy, and is working to improve the lifetime wellbeing of people and families in Australia. DSS' policies and services respond to need across people's lives - looking after families, children and older people; providing a safety net for people who cannot fully support themselves; enhancing the wellbeing of people with high needs; assisting people who need help with care; and supporting a diverse and harmonious society. DSS supports people and families in Australia by encouraging independence and participation, and supporting a cohesive society.
For more information on this dataset please visit the Australian Government Open Data.
For further details on payments, see 'A guide to Australian Government payments'.
Please note:


In order to protect individuals' privacy, identified populations between 1 and 4 have been suppressed and replaced with '&lt;5' for confidentiality purposes. Additional data may be suppressed and replaced with 'n.p.' (not provided) to prevent the derivation of identified populations that have values of less than 5.


Individuals who live overseas, individuals who are without a valid home address and individuals who only have a postal address cannot be assigned to a locational boundary. State/territory totals derived from Local Government Area data will not match actual state and territory totals, due to different statistical geography methodologies.


Caveats specific to payments type can be found in the relevant payment description of the original data.


AURIN has spatialised this dataset and have made the following replacements to enforce data type consistency: 


'&lt;5' has been assigned a value of '-1' within the data


A boolean field has been created for each data field to flag left-censored data. 'True' is assigned to fields that have been censored.


'n.p.' (not provided) has been set to Null within the data.



Tags: Demographics, Services, Social Services, Socio-economics
Organization: Australian Government - Department of Social Services
ABS Census - B27 Annual Individual Income By Sex (SLA) 1991

The 1991 Census Basic Community profiles present 57 tables containing summary characteristics of persons and/or dwellings for Statistical Local Areas (SLA) in Australia. 
This table contains data relating to annual individual income by sex. Counts are of persons aged 15 years or more, based on place of enumeration on census night which; includes overseas visitors; excludes Australians overseas; and excludes adjustment for under-enumeration. The data is by SLA 1991 boundaries. Periodicity: 5-Yearly. 
This data is ABS data (cat. no. 2101.0 &amp; original geographic boundary cat. no. 1261.0.30.001) used with permission from the Australian Bureau of Statistics. The tabular data was processed and supplied to AURIN by the Australian Data Archives. The cleaned, high resolution 1991 geographic boundaries are available from data.gov.au.
For more information please refer to the 1991 Census Dictionary.

Tags: 1991, b27, basic community profile, bcp, census, earnings, income, place of enumeration, salary
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
ABS Census - E34 Labour Force Status (Part-Time/Full-Time) By Sex Of Sole Parents By Age Of Dependent Offspring (LGA) 1991

The 1991 Census Expanded Community Profiles present 44 tables comprising more detailed information than that of the basic community profiles which provide characteristics of persons and/or dwellings for Local Government Areas (LGA) in Australia. 
This table contains data relating to labour force status (part-time/full-time) by sex of sole parents by age of dependent offspring. Counts are of dependent offspring (a) in one parent families, based on place of enumeration on census night which; excludes Australians overseas; and excludes adjustment for under-enumeration. The data is by LGA 1991 boundaries. Periodicity: 5-Yearly. 
This data is ABS data (cat. no. 2101.0 &amp; original geographic boundary cat. no. 1261.0.30.001) used with permission from the Australian Bureau of Statistics. The tabular data was processed and supplied to AURIN by the Australian Data Archives. The cleaned, high resolution 1991 geographic boundaries are available from data.gov.au.
For more information please refer to the 1991 Census Dictionary.
Please note:


(a) Comprises dependent offspring counted at home on census night.


(b) Full-time is defined as having worked 35 hours or more in the main job held last week.


(c) Comprises dependent offspring whose employed sole parent did not state his/her hours worked.


(d) Comprises dependent offspring whose employed sole parent did not state his/her labour force status.



Tags: 1991, census, community, e34, ecp, expanded, labour force, profiles, sole parent
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
AIHW - Cancer Incidence and Mortality Across Regions (CIMAR) - Persons Mortality (PHN) 2009-2013

This dataset presents the footprint of cancer mortality statistics in Australia for all cancers combined and the 6 top cancer groupings (colorectal, leukaemia, lung, lymphoma, melanoma of the skin and pancreas) and their respective ICD-10 codes. The data spans the years 2006-2010 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).
Mortality data refer to the number of deaths due to cancer in a given time period. Cancer deaths data are sourced from the Australian Institute of Health and Welfare (AIHW) 2013 National Mortality Database (NMD).
For further information about this dataset, please visit:


Australian Institute of Health and Welfare - Cancer Incidence and Mortality Across Regions (CIMAR) books.


Australian Institute of Health and Welfare - 2013 National Mortality Database.


Please note:


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


Due to changes in geographic classifications over time, long-term trends are not available.


Values assigned to "n.p." in the original data have been removed from the data.


The Australian and jurisdictional totals include people who could not be assigned a PHN. The number of people who could not be assigned a PHN is less than 1% of the total.


The Australian total also includes residents of Other Territories (Cocos (Keeling) Islands, Christmas Island and Jervis Bay Territory).


Cause of Death Unit Record File data are provided to the AIHW by the Registries of Births, Deaths and Marriages and the National Coronial Information System (managed by the Victorian Department of Justice) and include cause of death coded by the Australian Bureau of Statistics (ABS). The data are maintained by the AIHW in the NMD.


Year refers to year of occurrence of death for years up to and including 2012, and year of registration of death for 2013. Deaths registered in 2011 and earlier are based on the final version of cause of death data; deaths registered in 2012 and 2013 are based on revised and preliminary versions, respectively and are subject to further revision by the ABS.


Cause of death information are based on underlying cause of death and are classified according to the International Classification of Diseases and Related Health Problems (ICD). Deaths registered in 1997 onwards are classified according to the 10th revision (ICD-10).


Colorectal deaths presented are underestimates. For further information, refer to "Complexities in the measurement of bowel cancer in Australia" in Causes of Death, Australia (ABS cat. no. 3303.0).



Tags: health, population
Organization: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare
CCD-B05 Birthplace (Countries) by Sex-Census 1996

Census Collection District (CCD) based data for Country of Birth by Sex, in Basic Community Profile, 1996 Census. Count of all 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, ancestry, b05, basic community profile, bcp, birthplace, census, country of birth
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
LGA-W05c Status in Employment by Country of Birth of Person by Sex-Census 2016

LGA based data for Status in Employment by Country of Birth of Person by Sex, in Working Population Profile (WPP), 2016 Census. Count of employed persons aged 15 years and over. W05 is broken up into 4 sections (W05a - W05d), this section contains 'Females Sri Lanka Employee' - 'Persons Pakistan 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, birthplace, census, country of birth, employment, employment status, w05c, work, working population profile, wpp
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
SA4-based B09 Country of Birth of Person by Sex  as at 2011-08-11

SA4 based data for Country of Birth, for 2011 Census. Count of all persons 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
CCD-B22B Family Type and Relationship in Household by Age-Census 1996

Census Collection District (CCD) based data for Family Type and Relationship in Household by Age, in Basic Community Profile, 1996 Census. Count of all persons present in the household on census night. B22 is broken up into 2 sections (B22A – B22B), this section contains ‘Total Aged 0-4 years’ – ‘Total Total’. 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, b22b, basic community profile, bcp, census, family, family type, household relationship
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
LGA11-based B10B Country of Birth of Person by Year of Arrival in Australia as at 2011-08-11

LGA11 based data for Year of Arrival in Australia, for 2011 Census. Count of all persons 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
Mobility Australia - New South Wales Yearly Trains Origin-Destination Flow (SA2) 2020

This dataset estimates human mobility through origin destination (OD) movement flow among the Statistical Area 2 (SA2) regions in New South Wales (NSW), connected by public transport (PT) networks. The SA2 regions of New South Wales connected by Sydney trains (T1-T9) and Metro services (Metro North West line) 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
PHIDU - Emergency Department Presentations - Semi-Urgent (PHN) 2017-2018

This dataset, released June 2020, contains Emergency department presentations for semi-urgent by principal diagnosis, 2017/18. Presentations include Semi-urgent presentations - Total; Semi-urgent presentations for certain infectious and parasitic diseases; Semi-urgent presentations for mental and behavioural disorders; Semi-urgent presentations for diseases of the circulatory system; Semi-urgent presentations for diseases of the respiratory system; Semi-urgent presentations for diseases of the digestive system; Semi-urgent presentations for diseases of the musculoskeletal system and connective tissue; Semi-urgent presentations for diseases of the genitourinary system; Semi-urgent presentations for injury, poisoning and certain other consequences of external causes; Semi-urgent presentations for factors influencing health status and contact with health services; Semi-urgent presentations for other diseases/ conditions, 2017/18.
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 State and Territory health departments for 2017/18; and the average of the ABS Estimated Resident Population, 30 June 2017 and 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
NSW DE - Government School Locations and Enrollments Master Dataset 2017

The master dataset contains comprehensive information for all government schools in NSW. Data items include school locations, latitude and longitude coordinates, school type, student enrolment numbers, electorate information, contact details and more. Please note the following: Student enrolment numbers are based on the census of government school students undertaken on the first Friday of August 2017. 
For more information visit the NSW Education Data Hub.
Please Note: 


AURIN has spatially enabled the original data.


School information, such as addresses and contact details, are updated regularly as required, and are the most current source of information.


Data is suppressed for indigenous and language backgrounds other than English (LBOTE) percentages where student numbers are equal to, or less than five.


National Schools Collection (NSSC) out of scope schools will not have an enrolment figure.


NSSC and LBOTE figures are updated annually in March.


Index of Community Socio-Educational Advantage (ICSEA) values are updated every April with the previous year's ICSEA values. The master dataset is currently displaying 2016 figures. Small schools, Schools for Specific Purposes (SSPs) and Senior Secondary schools do not have their ICSEA values published by The Australian Curriculum, Assessment and Reporting Authority (ACARA).


Following the introduction of part-time study in secondary schools in 1993, student enrolments are generally reported in full-time equivalent units (FTE). The FTE for students studying less than 10 units, the minimum workload, is determined by the formula: 0.1 x the number of units studied and represented as a proportion of the full-time enrolment of 1.0 FTE.


Norfolk Island Central School (NICS) is not a NSW government school. NICS is operated by the Australian government. The NSW Department of Education provides school education services under an agreement with the Australian government.


For more information visit NSW Education Data Hub

Tags: school
Organization: Government of New South Wales - Department of Education
OpenStreetMap - Places of Interest - Points (Australia) 2021

This dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 02 December 2021. Its purpose is to display Places of Interest as points within Australia. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk.
For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki.
Please note:


The original data for this dataset has been downloaded from Geofabrik on 02 December 2021.


Due to changes in tagging, previous versions of OSM may not be comparable with this release.



Tags: BUILT ENVIRONMENT AND DESIGN, Urban, regional planning
Organization: OpenStreetMap
City of Melbourne CLUE Employment by CLUE Industries (Block) 2010

This dataset was collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data shows the employment (number of jobs) per city (CLUE) block, classified by their CLUE industry (from ANZSIC1) and small area allocation. The data is aggregated to the 2016 Blocks for CLUE Boundaries and covers the year period of 2010.
This dataset has been confidentialised to protect the commercially sensitive information of individual businesses. Data in cells which pertain to two or fewer businesses have been suppressed.
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.


Suppressed values have been set to NULL on the table. The total columns refer to the true total and include these suppressed values.



Tags: 2010, census, clue, employment, industry, land, melbourne, use
Organization: Local Government of Victoria - City of Melbourne
LGA-G09a Country of Birth by Age by Sex-Census 2016

LGA based data for Country of Birth of Person by Age by Sex, in General Community Profile (GCP), 2016 Census. Count of persons. G09 is broken up into 8 sections (G09a - G09h), this section contains 'Males Afghanistan Age 0-4 years' - 'Males Iraq Total'. The list of countries consists of the 50 most common Country of Birth responses reported in the 2011 Census. 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, birthplace, census, country of birth, g09a, gcp, general community profile, lga, sex
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
LGA Composite Indicators - Synthetic Prediction 2007-2008

People aged 18 years and over with composite health risk factors: asthma and smoking, or type 2 diabetes and overweight or obese by LGA, for 2007 to 2008.

Tags: asthma, estimates, health, obese, overweight, smoking, synthetic prediction, type 2 diabetes
Organization: Torrens University Australia - Public Health Information Development Unit
PHIDU - Premature Mortality - Cause (PHN) 2014-2018

This dataset, released February 2021, contains the statistics of premature mortality by various causes for people below 75 years, over the years 2014 to 2018. Causes for death include cancer (colorectal, lung, breast), diabetes, circulatory system diseases (ischaemic heart disease, cerebrovascular disease), respiratory system diseases (chronic obstructive pulmonary disease), and external causes (road traffic injuries, suicide and self-inflicted injuries)
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: Data compiled by PHIDU from deaths data based on the 2014 to 2018 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population is the ABS Estimated Resident Population (ERP) for Australia, 30 June 2014 to 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