AndreaBozzo/ceres-open-data-index huggingface dataset:
National Ecosystem Accounts - Rivers 2025

This dataset presents extent and condition data for Australian rivers and streams for three time periods: 2010–11, 2015–16 and 2020–21.

Freshwater ecological condition, especially that of rivers, is known to be influenced strongly by adjacent land use. Land Use Intensity (LUI), extracted from the Australian Bureau of Agricultural and Resource Economics (ABARES) Land Use data [(Land use of Australia 2010–11 to 2020–21)](https://www.agriculture.gov.au/abares/aclump/land-use/land-use-of-australia-2010-11-to-2020-21), is used as a proxy for inferring the condition (landscape characteristic) of freshwater ecosystems. 

Land Use Intensity (LUI) is defined by the ALUM classification [(Australian Land Use and Management Classification Version 8 (October 2016))](https://www.agriculture.gov.au/abares/aclump/land-use/alum-classification) as a measure of the intensity of different land uses, with the primary classes ordered from 1 (mostly natural) to 5 (intensive uses) in terms of increasing intensity. Category 6 represents areas obscured by water bodies. These areas are excluded from the ordinal classification as they do not have associated land-use intensity levels, thus cannot be used as a proxy for river condition.

The data was compiled using river extent data sourced from the Bureau of Meteorology (BoM) [Geofabric v3.3](https://www.bom.gov.au/water/geofabric). River segments were created based on two characteristics: River Region, which are reporting regions for major river catchments in Australia, sourced from the Regions product within the BoM Geofabric v3.3; and Ecosystem Functional Group (EFG), which is the finest level of the [International Union for Conservation of Nature’s](https://iucn.org/) [Global Ecosystem Typology](https://global-ecosystems.org/) (IUCN GET) classification system.

The river segments were further broken down by assigning the LUI category for each of the corresponding time periods. Spatial layers representing Land Use Intensity were overlaid with river segments, allowing each segment to inherit the LUI classification from the adjacent land use. The subsequent river fragments were then grouped into multipart line features, with each feature representing a unique combination of River Region, EFG, and LUI for each period. This process is described in the [National Ecosystem Accounts, experimental estimates Methodology](https://www.abs.gov.au/methodologies/national-ecosystem-accounts-experimental-estimates-methodology/2020-21).

This dataset was used to produce summary statistics for the [National Ecosystem Accounts, experimental estimates](https://www.abs.gov.au/statistics/environment/environmental-accounts/national-ecosystem-accounts-experimental-estimates/2020-21). The statistics provide an overview of river condition across river regions, states and territories, based on the total length of rivers that fall within each of the LUI categories. 

Tags: ABS, Australian Bureau of Statistics, IUCN GET, National Ecosystem Accounts, River Condition, River Regions
Organization: Environmental and Thematic Statistics
Annual Family Income, 1996-1997 to 1998-1999 (Three Year Average)

    

This data relates to the average annual family income of broadacre and dairy
farm properties which responded to the ABARE annual farm survey over a three
year period from 1996 -1997 to 1998 -1999. Average annual family income is
calculated as the family share of farm income plus any wages (that are
included as farm costs for taxation assessment) paid to the owner manager,
spouse and dependant children, plus all off-farm income of owner manager and
spouse. The data is reported at the Statistical Division (SD) level for
Australia. This data relates to broadacre and dairy farms run by owner
managers and has been collected by annual farm survey interview and is
supplemented by information in the farm accounts. The data is presented at a
scale of 25000000. The following attributes are contained within the dataset;
Sd code a a unique 3 digit code for Statistical Divisions (SD), Sd name a the
name of the Statistical Division (SD), Faminc a the average annual farm family
income for the period 1996-1997 to 1998-1999. RSE a the relative standard
error of the average farm equity ratio for the period 1996-1997 to 1998-1999.
Ag_land_ha a hectares of agricultural land use in the Statistical Division
(SD). Note that metropolitan areas are assigned a value of -99999, whilst
areas with no data are assigned a value of -88888.

See [further metadata](http://data.daff.gov.au/anrdl/metadata_files/pa_afi__r9aa
__00512a00.xml) for more detail.



Tags: agriculture, demography, economics, geoscientificinformation, humanenvironment, indicators, socialissues, statistics, surveys
Organization: Australian Bureau of Agricultural and Resource Economics and Sciences
Employment Service Areas (ESAs) 2013+ (Disability Employment Services)

The ESA geospatial boundary was initially developed prior to 2009, primarily based on grouping Australian Bureau of Statistics Statistical Local Area boundaries. Following the introduction of the Community Development Programme (CDP, formerly Remote Jobs and Communities Programme) on 1 July 2013, it took responsibility for Employment Services in remote areas. As a result, some ESA boundaries changed and some ESAs were removed, to exclude remote areas. 

Further information regarding the Community Development Programme is available from the National Indigenous Australians Agency (https://www.niaa.gov.au/indigenous-affairs/employment/cdp) website.

Update:

The Digital Atlas of Australia (https://digital.atlas.gov.au/) was launched in May 2024 to provide a centralised, user-friendly platform for accessing and analysing national datasets related to Australia’s geography, its people and its environment.

Users can now access Employment Service Area information from the Digital Atlas which are more detailed and provide a higher definition than what is offered thru the 
Employment Services Areas (ESAs) 2013+ (Disability Employment Services)

Disability Employment Service Areas (2013) Search Tool | Digital Atlas of Australia (https://digital.atlas.gov.au/apps/52e6996b9569447db6fbb76a5648fff9/explore)

A KML file can also be downloaded from the following link

Employment Service Areas 2013 (Disability Employment Services) | Digital Atlas of Australia (https://digital.atlas.gov.au/datasets/c9ef644befec40c28db8a8cb053abce3_0/explore)

Tags: DES, DSS, Disability, Disability Employment Services, ESA, Employment, Employment Service Area, Geospatial, Map, Social Services
Organization: Department of Social Services
Kerb Channels

A geo-spatial layer depicting the approximate location of kerb channels as of November 2015

Please note that as part of the attribution of this data under the CC BY licence terms with which it is supplied, users should include the following statement: 'The information is provided to assist in field investigations. All locations, dimensions and depths shown are to be confirmed on site'.

The City of Gold Coast is not a professional information provider and makes no representations or warranties about the accuracy, reliability, completeness or suitability for any particular purpose of the Data provided here. This Data is not provided with the intent that any person will rely on it for the purpose of making decisions with financial or legal implications. Persons who place such reliance on the Data do so at their own risk.

Tags: City of Gold Coast, CoGC, GIS, Gold Coast, Infrastructure, Roads
Organization: City of Gold Coast
Australian Dryland Salinity Assessment Spatial Data (1:2,500,000) – NLWRA 2001

    

The maps represent a compilation of dryland salinity risk and hazard mapping
for 2000, 2020 and 2050. The map shows the broad distribution of areas
considered as having either a high salinity risk or a high salinity hazard. In
southern Australia where groundwater level and trend data are available,
assessments that are more confident have been possible. However, in northern
Australia groundwater data for trend analysis are very sparse or non-existent.
In these regions, salinity assessments have been based on the presence of
geological, landscape, regolith, land use and climate attributes which are the
prime drivers of salinity. This national map provides a basis for identifying
those regions where more detailed assessments are warranted, and where land
use changes should be targeted if the risks are to be managed.The bulk of non-
agricultural areas in Western Australia, South Australia and western New South
Wales were considered to have a very low salinity risk and were not
assessed.Please note that the Commonwealth and all suppliers of source data
used to derive the maps of aAustralia, Forecast Areas Containing Land of High
Hazard or Risk of Dryland Salinity from 2000 to 2050a3 do not warrant the
accuracy or completedness of information in this product. Any person using or
relying upon such information does so on the basis that the Commonwealth and
data suppliers shall bear no responsibility or liability whatsoever for any
errors, faults, defects or omissions in the information.

See [further metadata](http://data.daff.gov.au/anrdl/metadata_files/pa_dsa__r9nn
d_00211a00.xml) for more detail.



Tags: biodiversity, environmentandnaturalresourcemanagement, geosciences, geoscientificinformation, land, waterandirrigation, watersalinity
Organization: Australian Bureau of Agricultural and Resource Economics and Sciences
CEWH Murray-Darling Basin valley boundaries

Spatial data set of valley boundaries in the Murray-Darling Basin used to support the Commonwealth Environmental Water Holder’s (CEWH) monitoring, evaluation and research activities.  Modified from the Sustainable Rivers Audit (SRA) valleys to partition the Selected Areas used in the Long Term Intervention Monitoring (LTIM) project and Flow-MER program and to align with water accounting in the Basin.

The CEWH’s Flow-MER program examines the contribution of Commonwealth environmental water to the environmental objectives of the Basin Plan 2012 (Basin Plan) and is assisting the CEWO to demonstrate environmental outcomes and adaptively manage the water holdings. For more information and reporting using these data see https://data.gov.au/data/dataset/cewo-mer-program.

###Acknowledgement

The Commonwealth Environmental Water Office and Flow-MER program acknowledge the First Nations peoples as the Traditional Owners and Custodians of the lands, waterways and skies of the Murray-Darling Basin. We respect their continuing connection to culture and Country, and we thank them for their knowledge and science and the values reflected in these data.

###Citation

CEWH Flow-MER (2023) CEWH Murray-Darling Basin valley boundaries. Flow-MER Program. Commonwealth Environmental Water Holder, Australian Government Department of Climate Change, Energy, the Environment and Water. Sourced from https://data.gov.au/data/dataset/cewo-mdb-valleys on [date-sourced].

Organization: Commonwealth Environmental Water Holder
MDMS sample points (Flow-MER monitoring locations)

Location of sample Points configured in the Commonwealth Environmental Water Holder (CEWH) Monitoring Data Management System (MDMS) that stores monitoring data from the Long Term Intervention Monitoring (LTIM) project and CEWO Monitoring, Evaluation and Research (Flow-MER) program. Includes Selected Area monitoring locations and Basin stream-flow gauging sites used in hydrology models (model nodes).

Flow-MER Program (2019-2023)

Long Term Intervention Monitoring (LTIM) project (2014-2019)

###Acknowledgement

The Commonwealth Environmental Water Holder and Flow-MER program participants acknowledge the First Nations peoples as the Traditional Owners and Custodians of the lands, waterways and skies of the Murray-Darling Basin. We respect their continuing connection to culture and Country, and we thank them for their knowledge and science and the values reflected in these data.

###Citation

CEWH Flow-MER (2023) MDMS sample points (Flow-MER monitoring locations). Flow-MER Program. Commonwealth Environmental Water Holder, Australian Government Department of Climate Change, Energy, the Environment and Water. Sourced from https://data.gov.au/data/dataset/mdms-monitoring-locations on [date sourced].

Tags: CEWH, CEWO, Commonwealth Environmental Water Holder, Commonwealth Environmental Water Office, Environmental monitoring, Flow-MER, LTIM
Organization: Commonwealth Environmental Water Holder
District of Workforce Shortage Specialist

The District of Workforce Shortage (DWS) classification system for non-GP specialists is an impartial mechanism used by the Government to encourage a more equitable distribution of non-GP specialist doctors who are restricted under s19AB of the Health Insurance Act 1973, including International Medical Graduates (IMGs) and Foreign Graduates of Accredited Medical Schools (FGAMS).
•	The DWS classification system is also used to distribute Australian-trained Bonded non-GP specialists who have a return of service obligation.
•	The DWS system as applied to specialists refers to the broadest grouping of a specialty and includes all sub-categories of that specialty (i.e. identifies the Derived Major Specialty)
•	The DWS uses population and Medicare billing data to determine a specialist-to-population ratio in SA3 geographical regions of Australia.
•	Areas classified ASGS – RA 3-5 under the ABS’ Australian Statistical Geography Standard – Remoteness Areas (ASGS – RA) are automatically DWS for distributed specialties. 
•	There are currently eight specialties subject to distribution using the DWS classification system:
o	Anaesthetics
o	Cardiology
o	Diagnostic Radiology
o	General Surgery
o	Medical Oncology
o	Obstetrics and Gynaecology
o	Ophthalmology
o	Psychiatry
•	The attached file for the DWS as at November 2023 (most recent annual update). As the files may be updated at short notice for program purposes, please ensure you use the Health Workforce Locator for the most up-to-date and official DWS location status.  

Tags: Australian Bonded Doctors, Distribution Priority Area, District of Workforce Shortage, Health, Health Informatics, Health Policy, Health and Community Services, Medical Specialist
Organization: Department of Health, Disability and Ageing
Water Quality Zones

    

The dataset shows MDB Water Quality Regions / Zones as at March 2010. The
dataset has been derived from the SRA Valley Zones as created by Sustainable
Rivers Audit (SRA) program in Murray Darling Basin Authority (MDBA) which is a
comprehensive assessment of river health taken in the Murray Darling Basin.
This dataset was constructed in GDA94 coordinate system, using the Australian
Water Resources Council (AWRC) catchment layer and were then subdivided into
altitude zones. These altitude zones correspond to one of seven categories:
Montane, Upland, Slopes, Lowland, Upper, Middle, Lower and Mt Lofty.

The water quality regions have been defined using similar geomorphologic and
geophysical landscape characteristics. The amalgamations of altitude zones
were determined, using similar water quality parameter values. The water
quality regions as defined by this dataset have been used in the guide to the
Basin Plan.


Tags: geospatialinformation, mdba, murray darlingbasin, water
Organization: Murray-Darling Basin Authority
Sewers

Geo-spatial layers depicting the approximate location of Sewer Maintenance Holes and Sewer Connections as of June 2015.

Please note that as part of the atttribution of this data under the CC BY licence terms with which it is supplied, users should include the following statement: 'The information is provided to assist in field investigations. All locations, dimensions and depths shown are to be confirmed on site'.

The City of Gold Coast is not a professional information provider and makes no representations or warranties about the accuracy, reliability, completeness or suitability for any particular purpose of the Data provided here. This Data is not provided with the intent that any person will rely on it for the purpose of making decisions with financial or legal implications. Persons who place such reliance on the Data do so at their own risk.

Tags: City of Gold Coast, CoGC, Geo-spatial, Gold Coast, Water
Organization: City of Gold Coast
Wimmera CMA Landcare Groups

Polygon geospatial data of Landcare boundaries for the Wimmera region. Last updated 2015, with minor alterations since that time for additional groups and boundary changes.

__Field Descriptions__

+ __id__	Group ID
+ __group_name__	Group Name
+ __district_n__	District
+ __group_abbr__	Group Abbreviation
+ __group_cate__	Group Type
+ __network__	Landcare Network
+ __network_ot__	Landcare Network (Secondary)
+ __cma__ Catchment Management Authority
+ __cma_other__ Catchment Management Authority (Secondary)
+ __hectares__	Area (ha)
+ __subsite__	POZI Sub Site
+ __x__	Z Coordinate (Centroid)
+ __y__	Y Coordinate (Centroid)
+ __z__	Zoom Level (Openlayers)

*Data may not be available for all fields.

Although all due care has been taken to ensure that this data is correct, no warranty is expressed or implied by Wimmera CMA in its use.

Tags: Environment, Group, Landcare, Wimmera
Organization: Wimmera CMA
Farm family Cash Income, 1996-1997 to 1998-1999 (three year average)

    

This data relates to the average annual cash income of broadacre and dairy
farm properties which responded to the ABARE annual farm survey over a three
year period from 1996-1997 to 1998-1999. Average farm cash income is
calculated as difference between total cash receipts (total revenues received
by the farm business during the financial year) and total cash costs (payments
made by the farm business for materials and services, which includes debt
repayments and permanent/casual labour costs). The data is reported at the
Statistical Division (SD) level for Australia. This data relates to broadacre
and dairy farms run by owner managers and has been collected by annual farm
survey interview and is supplemented by information in the farm accounts.The
data is presented at a scale of 25000000. Projection -P Albers Equal-Area
Conic -D WGS84 -m 132 -o 0 -p -18 -p -36 -e 0 -n 0The following attributes are
contained within the dataset; Sd code a a unique 3 digit code for Statistical
Divisions (SD), Sd name a the name of the Statistical Division (SD),Cash_inc a
the average annual farm cash income for the period 1996-1997 to 1998-1999RSE a
the relative standard error of the average farm equity ratio for the period
1996-1997 to 1998-1999.Ag_land_ha a hectares of agricultural land use in the
Statistical Division (SD).Note that metropolitan areas are assigned a value of
-99999, whilst areas with no data are assigned a value of -88888.

See [further metadata](http://data.daff.gov.au/anrdl/metadata_files/pa_fci__r9aa
__00811a00.xml) for more detail.



Tags: agriculture, cemography, economics, farming, farmperformance, farmsurveys, humanenvironment, indicators, productivity, statistics, surveys
Organization: Australian Bureau of Agricultural and Resource Economics and Sciences
2016 SoE Land Dust storm activity across Australia - Dust Stations

Map showing dust storm activity across Australia based on 356 stations, 2011 - 2011. Underpinning data sourced from Dustwatch Australia. For further information see: http://www.dustwatch.edu.au/index.php/modelled-wind-erosion/continental-erosion

Note. Data for years 2001 to 2009 have also been previously published in McTainsh G, Leys J, O’Loingsigh T, Strong C. Wind erosion and land management in Australia during 1940-1949 and 2000-2009. Report prepared by the Australian Government Department of Sustainability, Environment, Water, Population and Communities on behalf of the State of the Environment 2011 Committee. Canberra: DSEWPaC, 2011.

Map prepared by the Department of Environment and Energy in order to produce Figure LAN24 in the Land theme of Australia State of the Environment 2016 available at http://www.soe.environment.gov.au

The map service can be viewed at: https://soe.terria.io/#share=s-711c5zmmq1drL8d8AIMAaFau05R

Downloadable spatial data also available below.


Tags: 2016, 2016 SoE, Land, Land Map, SoE, SoE Map, State of the Environment
Organization: State of the Environment
Platforms

A geo-spatial layer depicting the approximate location and construction of platforms as of November 2015

Please note that as part of the attribution of this data under the CC BY licence terms with which it is supplied, users should include the following statement: 'The information is provided to assist in field investigations. All locations, dimensions and depths shown are to be confirmed on site'.

The City of Gold Coast is not a professional information provider and makes no representations or warranties about the accuracy, reliability, completeness or suitability for any particular purpose of the Data provided here. This Data is not provided with the intent that any person will rely on it for the purpose of making decisions with financial or legal implications. Persons who place such reliance on the Data do so at their own risk.


Tags: City of Gold Coast, CoGC, Gold Coast, Infrastructure, Tourism
Organization: City of Gold Coast
(Audit 2019) Congestion on major roads during 2031 PM peak

This layer is part of strategic transport modelling undertaken for [Urban Transport Crowding and Congestion](https://www.infrastructureaustralia.gov.au/publications/urban-transport-crowding-and-congestion), a supplementary report of the [Australian Infrastructure Audit 2019](https://www.infrastructureaustralia.gov.au/publications/australian-infrastructure-audit-2019).

These data represent average weekday transport performance during PM peak (4pm to 6pm). Note that any network links below relevant daily volume thresholds are not included. This is why some sections will appear missing or broken, and some links are isolated.

Tags: congestion, crowding, transport, urban transport
Organization: Infrastructure Australia
Tourism Regions 2020

This release provides tourism region maps and an allocation file for each and state and territory in 2020, based on the 2016 edition of the Australian Statistical Geography Standard (ASGS). Tourism regions are defined in consultation with the relevant national and state/territory tourism organisations. Each tourism region is constructed from allocations of whole Statistical Area Level 2s (SA2s), which are small spatial units of the ASGS.

Note that the Australian Bureau of Statistics manage the ASGS, however, tourism region boundaries are only updated every 5 years at each Census. In the interim, TRA manages the tourism region boundaries and publishes updated files every other year. TRA advises the ABS of new boundaries prior to each Census.

Tags: Boundaries, Tourism, Tourism Policy
Organization: Tourism Research Australia
Brimbank Arts Centres and Groups

This table outlines the point location of arts room, art gallery, artist studio and performance arts centre in Brimbank. Attribute includes Primary Category, facility name, address and etc.

While all due care has been taken to ensure the dataset is accurate and current, there may be errors or omissions in it. Brimbank City Council and its employees accept no responsibility for the completeness, accuracy or reliability of the data. Brimbank City Council and its employees also accept no responsibility for any loss, damage, claim, expense, cost or liability whatsoever (including in contract, tort including negligence, pursuant to statue and otherwise) arising in respect of or in connection with using or reliance upon the data in this dataset.

Tags: art, community-facilities
Organization: Brimbank City Council