AndreaBozzo/ceres-open-data-index huggingface dataset:
VIC DELWP - Victoria Unearthed - Sands & McDougall Business Directory (Point) 1896-1974

This dataset presents the location of business listings from Sands &amp; McDougall's Directory of Victoria. The data was created by digitising the published business directories using an Optical Character Recognition (OCR) process. The extracted information includes the business name, address and business type as listed in the Sands &amp; McDougall directories. The address information was subsequently geocoded to provide a spatial location. The data spans the the Sands &amp; McDougall's Directory of Victoria publication years 1896, 1925 and 1974.
Victoria Unearthed is a collection of data which includes past and present information about historical businesses, potential land and groundwater contamination, as well as information about contamination management and cleanup activities. Victoria Unearthed has been created in response to the Independent Inquiry into the Environmental Protection Authority (EPA).
For further information about this dataset, visit the data source:Government of Victoria - Department of Land, Water and Planning.
Please note:


Attributes captured by OCR ("directory address", "business name" and "business type") are uncorrected and may include errors.


The positional accuracy is affected by the limitations inherent with OCR and geocoding. Some issues such as changing street names, are exacerbated by the age of the records.


The directories were not consistent in the amount of information captured as the business address, in many cases it only lists the town or suburb for the business.


A modern (July 2018) property address, street or locality as defined by VicMap has been captured for all records.


Additional information has been provided to allow the accuracy of the results to be evaluated with each record containing the data used at each stage of the data capture process.



Tags: economy, environment, housing
Organization: Government of Victoria - Department of Environment Land Water and Planning
PHIDU - Potentially Preventable Admissions - All Conditions  (LGA) 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 Local Government Area (LGA) 2016 geographic boundaries.
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
SA3-P16a Highest Year of School Completed by Age by Sex-Census 2016

SA3 based data for Highest Year of School Completed by Age by Sex, in Place of Enumeration Profile (PEP), 2016 Census. Count of persons aged 15 years and over who are no longer attending primary or secondary school. P16 is broken up into 2 sections (P16a - P16b), this section contains 'Males Year 12 or equivalent Age 15-19 years' - 'Persons Year 9 or equivalent Total'. The data is by SA3 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, highest year of schooling, p16a, pep, place of enumeration profile, school, sex
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
SA3-I05b Type of Educational Institute Attending by Indigenous Status by sex-Census 2016

SA3 based data for Type of Educational Institution Attending (Full/Part Time Students Status by Age) by Indigenous Status by Sex, in Aboriginal and Torres Strait Islander People Profile (ATSIP), 2016 Census. Count of persons attending an educational institution.  I05 is broken up into two sections (I05a and I05b), this section covers ‘Type of educational institution not stated Indigenous status not stated Persons’ - ‘Total Total Persons’. The data is by SA3 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, aboriginal torres strait islander peoples, atsip, census, education, educational institution, i05b, indigenous status, sex, student
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
City of Melbourne CLUE Employment by CLUE Industries (Block) 2015

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 2015.
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: 2015, census, clue, employment, industry, land, melbourne, use
Organization: Local Government of Victoria - City of Melbourne
SA4-P44 Method of Travel to Work by Sex-Census 2016

SA4 based data for Method of Travel to Work by Sex, in Place of Enumeration Profile (PEP), 2016 Census. Count of employed persons aged 15 years and over (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, pep, place of enumeration profile, travel
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
ABS Census - C01 Summary Of Persons (CD) 1981

The 1981 Census Collection District Summary File (CDSF) presents summary characteristics of persons and their dwellings for every Collection District (CD) in Australia for 1981. The census information is made up of 34 tables giving data for both persons and dwellings.
This table contains a summary of persons. Census counts were 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 Census Collection District 1981 boundaries. Periodicity: 5-Yearly. 
This data is ABS data (cat. no. 2103.0 &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 1981 geographic boundaries are available from data.gov.au.
For more information please refer to "Making Sense of Census 1981".

Tags: 1981, c01, census, persons, place of enumeration, summary
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
Mobility Australia - New South Wales Monthly Trains Origin-Destination Flow (SA2) 2019

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
CER - Small-scale Installations - Small Generation Unit - Solar Panel (POA) 2017

This dataset presents the footprint of the number of installations of small generation unit (SGU) solar panel systems and their rated output in kilowatts (kW). The data spans the months of 2017 and includes the total for the year. 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 SGU (small-scale solar panel, wind and hydro systems) and kW capacity by installed postcode, and solar water heaters (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:


AURIN has spatially enabled the original data by joining the data with the 2016 ASGS POAs


The data is current as at 30-09-2018.


Renewable Energy Target (RET) legislation allows a 12 month creation period for registered persons to create their certificates.


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). Further information can be found at theRenewable Energy Target FAQ.


Capacity data has been revised to account for past data entry errors which caused significant inconsistencies. These systems were installed between 2001 and 2003. As a result of this revision, the cumulative installed capacity from 2004 onwards has reduced by 5.517MW.



Tags: energy
Organization: Government of the Commonwealth of Australia - Clean Energy Regulator
SA2-G13d Language Spoken at Home by Proficiency in Spoken Eng by Sex-Census 2016

SA2 based data for Language Spoken at Home by Proficiency in Spoken English by Sex, in General Community Profile (GCP), 2016 Census. Count of persons. The list of languages consists of the most common Language Spoken at Home responses reported in the 2011 Census. G13 is broken up into 4 sections (G13a - G13d), this section contains 'Persons Speaks Greek And speaks English Very well or well' - 'Persons Total Total'. The data is by SA2 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, g13d, gcp, general community profile, language, language spoken at home, sa2
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
PHIDU - Admissions - By Procedures  (PHA) 2014-2015

This dataset, released December 2017, contains data relating to hospital admissions during 2014-2015 by the following procedures: tonsilectomy, myringotomy (ages 0-9), hysterectomy (ages 30-59), Caesarean section (ages 15-44), delivery birth (ages 15-44), coronary artery bypass graft, coronary angioplasty, cardiac catheterisation, hip fracture, knee replacement, knee arthroscopy, and colonoscopy. 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 using data from the Australian Institute of Health and Welfare, supplied on behalf of Stateand Territory health departments for 2014/15; and the average of the ABS Estimated Resident Population, 30 June 2014and 2015.
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
SA3-G06 Social Marital Status by Age by Sex-Census 2016

SA3 based data for Social Marital Status by Age by Sex, in General Community Profile (GCP), 2016 Census. Count of persons aged 15 years and over in the following categories: married in a registered marriage, married in a de facto marriage (including same-sex couples), and not married. Excludes persons in 'Visitors only' and 'Other non-classifiable' households, 'Non-private dwellings', and 'Migratory, off-shore and shipping' SA1s. Excludes persons who were temporarily absent on Census Night. The data is by SA3 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, g06, marital status, sa3, sex, social
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics
Geoscience Australia - National Aviation Control Towers 2015

The aviation control towers dataset was digitized in 2012 from aerial photography, orthophotos and satellite imagery held within Geoscience Australia and presents the point location of these control towers. The primary information source used to identify and attribute the dataset was the Airservices Australia website.
For more information please visit the Geoscience Australia Web Service Portal.
Please note: 

This dataset is a snapshot of Geoscience Australia's web service dataset as on 2019-02-15


Tags: infrastructure, transport
Organization: Government of the Commonwealth of Australia - Geoscience Australia
RAI - Labour Market Efficiency (LGA) 2011

This data has been created by the Regional Australia Institute for the [In]Sight competitive index released in 2012. Modelled on the World Economic Forums Global Competitiveness Report [In]Sight was developed in collaboration with Deloitte Access Economics and combines data from sources including the Australian Bureau of Statistics and the Social Health Atlas of Australia.
Both employment rates and the levels of labour force participation are key inputs into the creation of an efficient labour market. Generally long-term unemployment indicates the presence of inherent structural problems which may adversely impact competitiveness. Low labour force participation may reflect low education levels in the region a lack of economic opportunities or an atypical age structure (such as a skew towards retirement age persons).

Tags: labour market
Organization: Regional Australia Institute
QLD Senior Secondary Catchments (polygon) 2018

This dataset contains information detailing the locations of all Senior Secondary State School (years 11 to 12) Catchments Boundaries for Queensland, 2018. State school catchment boundaries are used to assist enrollment management. 
For more information visit the Queensland Government Data Portal .

Tags: 2018, catchment areas, education, qld, queensland , senior secondary school, state school
Organization: Government of Queensland - Department of Education and Training
Mobility Australia - Queensland Weekly Rail Origin-Destination Flow (SA2) 2020

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
ABS Census - U25 Annual Individual Income By Age By Sex (LGA) 1991

The 1991 Census Usual Residents Community Profiles present 25 tables containing summary characteristics of usual residents for Local Government Areas (LGA) in Australia. 
This table contains data relating to annual individual income by age and sex. Counts are of persons aged 15 years or more, based on their usual place of residence; 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.

Tags: 1991, annual, census, income, lga, population, residence, u25, urp, usual
Organization: Government of the Commonwealth of Australia - Australian Bureau of Statistics