AndreaBozzo/ceres-open-data-index huggingface dataset:
Multidata approach to map paleovalleys in the Western Musgrave region

The Australian Government’s Exploring for the Future Musgrave Palaeovalley Project investigated the groundwater systems of the Western Musgrave region. This arid desert area spans the borders of Western Australia, Northern Territory, and South Australia, and contains no perennial surface water features. Consequently, remote communities, the environment, and industry in the area depend solely on groundwater.

To enhance the understanding of palaeovalley geology and groundwater systems, 19,400 line kilometres of airborne electromagnetics (AEM) were acquired, and 18 bores were sampled for hydrochemical data, including isotopes and environmental tracers. These new data were integrated with legacy AEM data from historical mineral exploration and a regional bore database of approximately 200 bores.

Utilising these datasets, we developed a three-dimensional model of palaeovalleys and Cenozoic systems, producing the region’s first hydrogeological conceptual model. Palaeovalleys in the study area generally slope gently southward, with sufficient thickness to contain significant amounts of groundwater. We also identified several areas where neo-tectonic faulting disrupts palaeovalley flow paths, likely leading to groundwater compartmentalisation and upwelling.&lt;

Cenozoic groundwater in the region was found to be fresh to brackish and well-connected on a regional scale. Isotopic and tracer data indicate that most groundwater is relatively young (&lt;100 years) and recharged by events associated with cyclones and monsoons. We also propose a hypothesis linking high nitrate groundwaters commonly encountered in arid Australia with conditions created by the often-targeted calcrete aquifers.

The project's findings highlight the crucial role of groundwater in arid environments and demonstrate the importance of integrating geophysical and hydrochemical methods.

Presented at the 52nd Congress of International Association of Hydrogeologists (IAH2025)

Tags: AEM, EFTF – Exploring for the Future, Groundwater hydrology, Musgraves, Published_External, groundwater, hydrochemistry, palaeovalleys
Organization: Geoscience Australia Data
Grants funding paid to organisations (retired)

<strong>This dataset was previously managed by the former Department of Communities, Child Safety and Disability Services. Since the Machinery of Government changes in December 2017, this dataset is no longer supported.</strong>



Yearly funding provided to non-government organisations in Queensland by the Department of Communities, Child Safety and Disability Services.

Grant payments now published in the data set:   DCCSDS-Queensland Government Investment portal (QGIP)       
https://data.qld.gov.au/dataset/dccsds-queensland-government-investment-portal-qgip

Tags: Child Safety and Disability Services, community, funding, government, grants, organisations
Organization: Families, Seniors, Disability Services and Child Safety
Low Head to Swan Island Bathymetry - 1:25,000 Series

The Low Head to Swan Island - 1:25,000 Series depicts bathymetric contours from Low Head [146d 17m, -41d 03m] to Swan Island [148d 06m, -40d 44m] from the coastline to 1500m from the coastline. The contours are at 5 metre intervals. The dataset is intended to be used to fulfil coastal management objectives according to The Living Marine Resources Act 1995. It is not to be used for navigational purposes.

Tags: FISHERIES, FISHERIES Aquaculture, FISHERIES Marine, MARINE Coasts
Organization: Tasmania Government's The List Data
Seismic refraction survey of the Wayatinah "A" power station site and penstock lines, Tasmania

Details and results are given of a seismic refraction survey made at the request of the Hydro-Electric Commission of Tasmania, to investigate the proposed site for a power station with penstock lines and tail race. The power station is part of the Wayatinah "A" project. The object of the survey was to determine the thickness of the alluvial gravel formation on the river flat, the weathered section of the sandstone and the dolerite, and to indicate the presence of shear zones. Three traverses parallel to the proposed penstock line, and 100 feet apart, and three cross traverses were surveyed in January and February, 1954. After completion of the original survey two additional traverses were surveyed on the location chosen for the power station, penstock lines and tail race site.

Tags: AU-TAS, Earth Sciences, GA Publication, Published_External, Record, seismic refraction, seismics
Organization: Geoscience Australia Data
Nepean River Flood Study

The Hawkesbury-Nepean River catchment is one of the largest coastal basins in NSW with an area of 21,400 square kilometres. The catchment at Penrith is 52% of the total area and of this portion, 80% is under the control of Warragamba Dam.
The Nepean valley within the Penrith LGA is characterised by a relatively narrow floodplain that is divided into three parts by the river channel. The northern floodplain area encompasses Penrith Lakes and the eastern side of the valley. The channel divides the valley south of this with the western side over Emu Plains and the eastern side over the Mulgoa and Central Business District (CBD) area.

Tags: Nepean River, Penrith City Council
Organization: Penrith City Council
Kalgoorlie–Boulder Photo-Voltaic (PV) Potential Maps: Weather Data

This dataset contains hourly weather station temperature records that underpin all photovoltaic potential calculations in the Kalgoorlie-Boulder solar assessment collection. It provides the climate foundation essential for understanding and validating the irradiance and PV potential outputs.

The dataset consists of hourly temperature observations (°C) extracted from TMYx (Typical Meteorological Year) climate files for Kalgoorlie-Boulder Airport (2004-2018) weather station. These values are used to apply temperature-dependent efficiency adjustments to PV panel performance calculations, as solar panel output decreases with rising temperatures above 25°C standard test conditions.

Users can reference this data to verify climate inputs, understand the meteorological context of PV estimates, or conduct sensitivity analyses showing how temperature variations affect system performance. It is particularly valuable for researchers validating the methodology, engineers developing refined performance models, or policy analysts assessing climate scenario impacts on solar generation.

The data represents synthesised typical hourly conditions throughout the year based on historic weather conditions rather than actual hourly observations, designed to capture characteristic patterns while smoothing extreme anomalies. This approach ensures PV estimates reflect long-term average conditions suitable for planning purposes.

This dataset complements the georeferenced irradiance and potential datasets in the collection by providing a temporal climate context. For spatial PV analysis, users should reference the footprint-based datasets that incorporate these temperature values into location-specific calculations.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University
Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Australian Footprints (Kalgoorlie, Boulder, Trafalgar)

This foundational spatial dataset provides the building footprint geometries and contextual attributes that enable all rooftop solar analyses in the Kalgoorlie-Boulder collection, serving as the essential geographic framework linking solar potential to specific locations.

The dataset integrates Microsoft Bing building footprints with Australian Bureau of Statistics mesh block boundaries, elevation derived from the Elvis – Elevation and Depth (Geoscience Australia) dataset, and 2021 Census dwelling counts, creating a comprehensive spatial reference for approximately 16,000 buildings across 530 mesh blocks. Each footprint includes geometric attributes, statistical geography codes (SA1-SA4, mesh block), topographic classification, elevation, and population context.

This resource enables users to filter solar datasets by administrative boundaries, analyse potential across different land use categories, relate solar capacity to population density, or develop custom spatial queries joining solar metrics with other urban datasets. It serves as the join key between solar irradiance/potential estimates and real-world building locations.

Critical applications include spatial planning analysis (identifying high-potential zones for solar incentive programs), equity assessment (evaluating renewable energy access across socio-economic areas), and infrastructure planning (relating distributed generation potential to grid connection points). GIS analysts can use mesh block and SA codes to integrate solar data with ABS Census statistics, health data, or other spatially-referenced datasets.

Footprints represent 2013-2018 building stock and may not capture recent construction. Elevation values support topographic context, but solar calculations use flat-roof assumptions. This is the recommended base layer for all spatial analyses using the solar datasets.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University
Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Daily Average Irradiance Values

This dataset provides daily average solar irradiance values for approximately 16,000 building footprints across Kalgoorlie-Boulder, Western Australia. It delivers rooftop-level estimates of solar radiation potential averaged by month, enabling rapid assessment of photovoltaic feasibility at the individual building scale.

The dataset was created to support distributed energy planning by combining Microsoft Bing building footprints (2D) with climate data from CSIRO and http://climate.onebuilding.org , processed through the LBNL Radiance lighting simulation suite. Each footprint includes monthly, daily and hourly averages (W/m²) calculated from hourly irradiance simulations based on TMYx climate files (2004-2018).

This resource is particularly valuable for building owners and property managers conducting preliminary PV feasibility studies, local governments developing renewable energy strategies, and researchers analysing urban solar potential at building resolution. The daily and monthly average formats provide accessible metrics for comparing seasonal variation and estimating annual energy generation potential without requiring processing of hourly data.

Coverage includes 530 mesh blocks spanning Kalgoorlie, Boulder, and Trafalgar. Values represent rooftop-plane irradiance assuming flat surfaces and do not account for roof tilt, orientation variations, or shading from trees or adjacent structures. For detailed hourly analysis or specific panel configurations, users should reference the complementary hourly datasets in this collection.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University
Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Daily Average Potential Values

This dataset translates solar irradiance into estimated daily photovoltaic energy output (kWh) for individual buildings, incorporating panel characteristics and temperature efficiency losses to deliver actionable generation estimates.

Covering approximately 16,000 footprints, the dataset provides monthly daily average PV potential values that account for panel efficiency (27%), temperature coefficient (-0.5%/°C), and optimal panel layout within each rooftop geometry. These values represent realistic generation expectations from standard mid-performance panels (0.96 x 1.64m, 300W), enabling direct comparison of building-level solar capacity across the urban area.

The dataset was created to bridge the gap between raw irradiance data and practical energy planning. By incorporating panel specifications and calculating maximum feasible panel counts per rooftop (accounting for edge setbacks and spacing), it delivers estimates directly usable for installation feasibility studies and energy self-sufficiency analysis.

Target users include building owners evaluating solar investment opportunities, property developers assessing renewable energy contributions, and municipal planners setting district-level clean energy targets. The daily average format provides accessible seasonal generation patterns without requiring specialised photovoltaic modelling software.

Estimates assume flat-mounted panels in optimal orientation and do not account for actual roof pitch, shading, or site-specific installation constraints. For hourly generation profiles needed for grid integration studies or battery sizing, reference the hourly PV potential dataset. For customised panel specifications, apply your parameters to the irradiance datasets.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University
Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Monthly Cumulative Potential Values

This dataset aggregates photovoltaic generation potential to monthly and annual totals for each building, providing the energy budget metrics most directly applicable to economic feasibility analysis and renewable energy target setting.

The dataset delivers cumulative PV output (kWh) for 12 months plus annual totals across approximately 16,000 buildings, incorporating panel performance characteristics and temperature efficiency adjustments. These values represent the total energy that could be generated under standard mid-performance panel specifications, accounting for maximum feasible panel placement on each rooftop.

Monthly cumulation serves economic and policy applications: calculating annual revenue under feed-in tariffs, estimating return on investment timelines, assessing progress toward municipal renewable energy goals, and comparing seasonal capacity factors across building types. The dataset enables rapid screening of high-potential properties and portfolio-level solar capacity assessment.

Key users include energy consultants conducting pre-feasibility studies, local government officers tracking climate action plan progress, and commercial property managers evaluating solar investment across multiple buildings. Financial analysts can use annual totals for cash flow projections, while urban planners can aggregate values to understand district or city-wide renewable generation potential.

Values assume optimal panel specifications and placement. For custom panel types, users should apply efficiency ratios to the irradiance datasets. For sub-monthly temporal analysis (grid integration, demand matching), reference the hourly dataset.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University
Healthdirect - NHSD - Services Directory 2025

The National Health Services Directory ('NHSD'), published by Healthdirect Australia, is a comprehensive and consolidated national directory of health services and related health service providers in both the public and private sectors across all Australian jurisdictions. The purpose of the NHSD is to provide consistent, authoritative, reliable and easily accessible information about health services to the public and to support health professionals with the delivery of healthcare.

Please refer to the <a href="https://www.healthterminologies.gov.au/understanding-clinical-terminology-landing/what-is-snomed-ct-and-amt/">National Clinical Terminology Service</a> for more information.

This dataset was derived from service, location and organisation profiles accessed through the Healthdirect provided NHSD API and has been spatialised as a point dataset. This directory is presented as a snapshot in time as at June 2025.

This dataset is available for access to academic users once they have agreed to the NHSD terms of use; other AURIN users can apply for access to the dataset <a href="https://aurin.org.au/resources/data/nhsd-data-application-form/">here</a>.

Tags: health, infrastructure, services
Organization: Healthdirect Australia
Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Monthly Cumulative Irradiance Values

This dataset quantifies cumulative monthly solar irradiance totals for building footprints in Kalgoorlie-Boulder, providing monthly and annual energy budgets essential for photovoltaic system sizing and economic analysis.

Derived from hourly simulations aggregated to monthly totals, the dataset delivers cumulative irradiance values (W/m²) for each of 12 months plus annual totals across approximately 16,000 buildings. This format directly supports PV system performance modelling, return-on-investment calculations, and comparative analysis of seasonal energy availability across different urban areas.

The data combines Microsoft Bing 2D building geometries with validated climate datasets and Radiance-based solar simulation. Monthly cumulation allows users to assess seasonal energy production patterns, identify optimal installation timeframes, and estimate annual yield without managing high-temporal-resolution data files.

Key applications include renewable energy target setting for local government, preliminary system sizing for commercial solar installations, and academic research into urban energy self-sufficiency potential. Energy utilities and planners can use monthly totals to model distributed generation contributions to grid supply across different seasons.

Values assume flat rooftop surfaces without accounting for actual roof pitch, azimuth, or shading effects. Users requiring panel-specific calculations should apply the irradiance values to their chosen panel specifications using standard photovoltaic performance models. For sub-monthly temporal dynamics, see the hourly potential dataset.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University
Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Australian Mesh Blocks (Kalgoorlie, Boulder, Trafalgar)

This dataset provides Australian Bureau of Statistics mesh block boundaries with integrated census demographics for Kalgoorlie-Boulder, enabling aggregation of building-level solar potential to standard statistical geography units for policy analysis and planning.

The dataset contains 530 mesh blocks - the finest-resolution census geography - enriched with 2021 Census dwelling and population counts, complete hierarchical statistical area codes (SA1-SA4), and topographic classifications. Mesh blocks serve as the fundamental spatial unit linking building-level solar estimates to Australian statistical datasets, enabling integration with census, health, transport, and other ABS data collections.

Key applications include analysing solar potential per capita across neighbourhoods, identifying areas with high rooftop capacity relative to population density, evaluating equity in renewable energy access across socio-economic areas, and aggregating building-level results to SA2 or SA3 regions for regional planning. This geography enables comparative analysis with other Australian cities using standardised ABS boundaries.

Target users include policy analysts requiring census-compatible spatial units, researchers linking solar potential to demographic or socio-economic variables, and government planners developing place-based renewable energy strategies. The hierarchical statistical area codes enable flexible aggregation from mesh blocks (finest scale) through SA1-SA4 to the state level.

Mesh block boundaries reflect 2021 Census geography and differ from 2016 Census in some locations. Use the "changed since 2016" flag to identify modified boundaries. Population counts represent usual residence on Census night, not daytime presence relevant to commercial solar usage.

Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href="https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf">here</a>; software stack details and calculation workflows are documented in <a href="https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf">here</a>.

Tags: PV Potential, PV Rooftops, Photo-Voltaic, Solar Irradiance Estimation, Urban Rooftop Aggregation
Organization: School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University