Abstract Australia's Land Borders is a product within the Foundation Spatial Data Framework (FSDF) suite of datasets. It is endorsed by the ANZLIC – the Spatial Information Council and the Intergovernmental Committee on Surveying and Mapping (ICSM) as the nationally consistent representation of the land borders as published by the Australian states and territories. It is topologically correct in relation to published jurisdictional land borders and the Geocoded National Address File (G-NAF). The purpose of this product is to provide:

a building block which enables development of other national datasets; integration with other geospatial frameworks in support of data analysis; and visualisation of these borders as cartographic depiction on a map.

Although this service depicts land borders, it is not nor does it purport to be a legal definition of these borders. Therefore it cannot and must not be used for those use-cases pertaining to legal context. Termination Points are the point at which the state border polylines meet the coastline. For the purpose of this product, the coastline is defined as the Mean High Water Mark (MHWM). In the absence of a new MHWM for NSW, the Jervis Bay termination points are defined by the NSW cadastre. This feature layer is a sub-layer of the Land Borders service. Currency Date modified: 10 November 2021 Modification frequency: None Data extent Spatial extent North: -14.88° South: -38.06° East: 153.55° West: 129.00° Source information Catalog entry: Australia's Land Borders The Land Borders dataset is created using a range of source data including:

Australian Capital Territory data was sourced from the ACT Government GeoHub – ‘ACT Boundary’. No changes have been made to the polylines or vertices of the source data. In the absence of any custodian published border for Jervis Bay – New South Wales, a border has been constructed from the boundary of the NSW cadastre supplied by NSW Spatial Services. Geoscience Australia’s GEODATA TOPO 250K data was considered as an alternative, however, that border terminated short of the coastline as it stops at the shoreline of the major water bodies. Therefore, a decision was made to use the NSW and OT supplied cadastre to create a new representation of the Jervis Bay border that continued to the coastline (MHWM), in place of the TOPO 250K data. In the absence of publicly available data from New South Wales, the land borders for New South Wales have been constructed using the data of adjoining states Queensland, South Australia, Victoria and the Australian Capital Territory. This approach is agreeable to New South Wales Government for this interim product. In the absence of publicly available data from the Northern Territory the land borders for the Northern Territory have been constructed using the data of adjoining states Western Australia, Queensland and South Australia. This approach is agreeable to Northern Territory Government for this interim product. Queensland state border and coastline data have been download from the Queensland Spatial, Catalogue – QSpatial. Publicly available data for the state borders of South Australia was downloaded from data.gov.au and is ‘SA State Boundary - PSMA Administrative Boundaries’. Downloaded as a file geodatabase in GDA2020. Victorian state border data has been downloaded from the Victorian state Government Spatial Datamart, it is titled ‘FR_FRAMEWORK_AREA_LINE’. The Victorian state border data was used for the NSW/VIC section of border due to the absence of any publicly available data from New South Wales for this section of the border. Western Australian state border data was downloaded from the WA Government as publicly available. The Western Australia state border data has been used for the WA/NT section of the border due to the absence of publicly available data from Northern Territory for this section of the border. Selecting the SA data for the WA/SA border would introduce mismatches with the WA cadastre. It would also not improve the SA relationship with the SA cadastre. Using the WA data for the WA/SA section of the border aligns each state with its own cadastre without causing overlaps.

Sources specific to the Termination Points are as follows:

Jurisdictions Coastline data source

NT/QLD Publicly available Queensland Coastline and State Border data

QLD/NSW Publicly available Queensland Coastline and State Border data

NSW/VIC VIC Framework (1:25K) line

VIC/SA Coastline Capture Program (of SA by Tasmania)

SA/WA Coastline Capture Program (of SA by Tasmania)

WA/NT Coastline Capture Program (of NT by Tasmania)

JBT (OT) NSW Cadastre

Lineage statement At the southwest end of the NT/SA/WA border the South Australian data for the border was edited by moving the end vertex ~1.7m to correctly create the intersection of the 3 states (SA/WA/NT). At the southeast end of the NT/QLD/SA border the South Australian data for the border was edited by moving the end vertex ~0.4m to correctly create the intersection of the 3 states (NT/SA/QLD). Queensland data was used for the NT/QLD border and the QLD/NSW border due to the absence of publicly available data from the Northern Territory for these section of the border. Data published by Queensland also included a border sections running westwards along the southern Northern Territory border and southwards along the western New South Wales border. These two sections were excluded from the product as they are not within the state of Queensland. Queensland data was also used in the entirety for the SA/QLD segment of the land borders. Although the maximum overlap between SA and QLD state border data was less than ~5m (and varied along the border), the Queensland data closely matched its own cadastre and that of South Australia. The South Australian data overlapped the Queensland data, it also did not match the South Australian cadastre. Therefore, a decision to use the Queensland data for the QLD/SA section of the border ensured the best possible topological consistency with the published cadastre of each state. The South Australian/Victorian state border, north-south, were generally very similar with some minor deviations from each other from less than 1m to ~60m (there is one instance of deviation of 170m). The section of border that follows the Murray River is matched, for the most part by both states. Over three quarters of the border running along the river is matched with both states. There is a mismatch between the states in the last quarter of the border along the river, the northern section, however, both states still have the border running inside, or along, the river polygon (Surface hydrology), the Victorian data was chosen for this section purely for consistency as the Victorian data was used for the preceding arcs. Overall, the Victorian data was selected for use as the South Australia/Victoria land border. After taking the existing cadastre and GNAF points into account and it did not introduce extra errors into the relationship between the land borders and the cadastre of either state. In parts, it improved the relationship between the South Australian cadastre and the SA/VIC state border. This interim product will be updated when all states and territories have published agreed, authoritative representations of their land borders. This product will also be updated to include land mass polygons at time when the Coastline Capture Program is complete. This dataset is GDA 2020 compliant - transformed into GDA2020 from it's original source datum. Reference System Code 2020.00. Data dictionary All Layers

Attribute name Description

CREATE_DATE Date on which the positional data point was created in the data set

Field All features in this data set are labelled "TERMINATION_POINT"

SOURCE Project from which the data point information is derived

STATEMENT Legal disclaimer for the positional data

STATES Termination points divide at least two states and/or territories

Contact Geoscience Australia, clientservices@ga.gov.au

Snapshot img

Government Open Data Management Platform Market Size 2024-2028

The government open data management platform market size is forecast to increase by USD 96.48 million at a CAGR of 9.73% between 2023 and 2028.

The market is experiencing significant growth due to the increasing demand for digitalization in government operations. This trend is driving the adoption of advanced technologies such as artificial intelligence (AI) and machine learning (ML) in open data management platforms. However, data privacy concerns remain a major challenge for market growth. As governments look to make more data available to the public, ensuring the security and confidentiality of sensitive information is paramount. This report provides a comprehensive analysis of these trends and challenges, offering insights into the market's future direction. The rising demand for transparency and accountability in government operations is also fueling the adoption of open data platforms.However, the implementation of stringent data security measures is essential to mitigate the risks associated with data breaches and unauthorized access. Overall, the market is expected to witness steady growth In the coming years, driven by the increasing adoption of digital technologies and the need for more efficient and effective government services.

What will be the Size of the Government Open Data Management Platform Market During the Forecast Period?

Request Free SampleThe market encompasses solutions that facilitate the enhancement, sharing, cataloging, storage, publication, and download of machine-readable data through central web portals. This market is experiencing significant growth due to the increasing demand for open data access from various stakeholders, including government employees, lay citizens, and civic hackers. An integrated software suite for open data management offers metadata management capabilities, data analytics tools, and machine learning algorithms to improve data quality and usability. The market's size is expanding as governments worldwide recognize the potential of open data to drive innovation, transparency, and accountability. For-profit companies are increasingly collaborating with governments to provide comprehensive open data management platforms, ensuring interoperability and standardization across various data sources.Overall, the market is poised for continued growth as more organizations embrace the benefits of open data and the need for efficient, accessible, and secure data management solutions.

How is this Government Open Data Management Platform Industry segmented and which is the largest segment?

The government open data management platform industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. End-userLarge enterprisesSMEsDeploymentOn-premisesCloud-basedGeographyNorth AmericaCanadaUSEuropeUKFranceAPACSouth AmericaMiddle East and Africa

By End-user Insights

The large enterprises segment is estimated to witness significant growth during the forecast period. Government Open Data Management Platforms (ODMPs) serve as crucial tools for large enterprises to access, analyze, and derive valuable insights from data published by government agencies. These platforms offer a wealth of information on various sectors, including demographics, socioeconomic factors, infrastructure, and more. By leveraging this data, enterprises can gain a deeper understanding of market trends, consumer behavior, and emerging opportunities. Additionally, ODMPs can help reduce costs by enabling identification of new suppliers, optimization of supply chains, and improvement of energy efficiency. The holistic evaluation of ODMPs encompasses an integrated software suite, open data portal, metadata management, data analytics, enhancement, sharing, data cataloging, data storage, data publication, and machine-readable formats.These platforms offer a central web portal for easy access by citizens, civic hackers, for-profit companies, and government organizations. Technological advancements, such as cloud computing, IoT technologies, and investments in industry verticals, continue to drive developments in ODMPs. Success factors include instantaneous data processing, unification of data, segmentation of users, and understanding behavior patterns to cater to targeted markets. Marketers can utilize ODMPs to personalize ads and access customer data, environmental data, sensor data, and spatial data storage. System integrators and intermediaries play a key role in implementing and optimizing these platforms for their clients. Current priorities for ODMPs include ensuring security, interoperability, and scalability.

Get a glance at the market report of various segments Request Free Sample

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The Energy Resources Division has compiled a database containing the time-depth pairs for all open-file checkshots and VSP’s acquired in onshore South Australia. Periodic updates will be made as new data becomes open-file. The Energy Resources Division has compiled a database containing the time-depth pairs for all open-file checkshots and VSP’s acquired in onshore South Australia. Periodic updates will be made as new data becomes open-file.

The Biological Databases of South Australia (BDBSA) is South Australia's flora and fauna database that stores and manages specimen and observation records. This record is the flora component that contains 1,050,631 plant measurements collected from 224,572 sites, across 5565 plant species since 1976. This dataset includes vegetation structural attributes, observations on individual plants such as stem diameter, crown extent and crown density, as well as occurrence data. The resulting database provides a comprehensive record of plant diversity across sites ground-truthed during a diverse range of biodiversity projects undertaken in South Australia and provides a basis for future updating of mapping or other relevant work such as species modelling.

Only validated BDBSA data is made publicly available and all records of confidential taxa have been masked from the dataset. Data is accessible from the TERN Data Infrastructure, which provides the ability to extract subsets of vegetation data across multiple data collections and bioregions for more than 31 variables including stem diameter, tree crown extent, and number of individual plants.

With population growth in the Adelaide city centre a priority for both the Government of South Australia and the City of Adelaide, a joint research study was commissioned by the two organisations …Show full descriptionWith population growth in the Adelaide city centre a priority for both the Government of South Australia and the City of Adelaide, a joint research study was commissioned by the two organisations into the market for Adelaide city living. The work, undertaken by Hudson Howells in South Australia, identified key market segments for Adelaide, as well as providing insights into perceptions of Adelaide as a residential proposition, product preferences, competitor environment and relocation decision making. The research comprised four surveys and seven focus groups. Reports outlining the results of each study and the round of focus groups are available here as pdf files. Survey raw data is also provided here in excel and spss formats for use by the development community and others. In particular providing the data in spss format allows for further statistical interrogation and additional insights into the Adelaide city living market.

The annual Letter Books comprise 19 volumes, which contain primary copies of all of HYL Brown’s early work-related correspondence written after 1882, in his official capacity as SA Government Geologist, to his employer the SA Minister of Mines,... The annual Letter Books comprise 19 volumes, which contain primary copies of all of HYL Brown’s early work-related correspondence written after 1882, in his official capacity as SA Government Geologist, to his employer the SA Minister of Mines, plus later letters also written thus (through Brown) by his initial few qualified colleagues working in the fledgling SA Department of Mines from approximately 1904 to 1923. This record series content is of considerable historical importance. For the first 30 years of geoscientific work done by the SA Government, their year-by-year account running up to 1912 stands in place of any formal Annual Report issued by the Government Geologist or staff. The 312 departmental Letter Books records are individually registered are limited to reports made by HYL Brown which the SA Minister of Mines in the day considered to have enough economic (and political) value for him to table during Government business in the SA Parliament. Tabled reports subsequently became part of the Parliamentary Papers archive. But other reports of scientific activity and those giving reasoned advice for suggested lines of technical research that should be pursued, which did not carry immediate cadence, were ignored for formal promulgation. Pre the federation of the states of Australia in 1899-1900, South Australia had governance responsibility for what became the Northern Territory of this country. Therefore, HYL Brown and his colleagues conducted the first extensive resource surveys of that large tract and write about their findings. Several expeditions were made to different parts of the territory during that time, building on and adding to the work done by famous prior explorers like Stuart. As such, the LB records are a major part of captured early NT history, re. advice guiding the decisions made about its development. The original Letter Book volumes are now stored at State Records Archival Repository, to ensure preservation, and due to their fragile nature can only be viewed under supervision onsite. Please contact State Records to arrange access. They are not yet available as scanned versions, again due to their fragile nature

The 2015-16 Budget is now available. This dataset is a collection of data sources from the 2015-16 State Budget, specifically Budget Statements. The Budget Statements consists of financial reports …Show full descriptionThe 2015-16 Budget is now available. This dataset is a collection of data sources from the 2015-16 State Budget, specifically Budget Statements. The Budget Statements consists of financial reports presenting the State Government’s current and estimated future economic performance, fiscal strategy, budget priorities, expenditure, revenue, assets, liabilities, risks, regional South Australia and government business. Data from the 2015-16 State Budget are provided to assist those who wish to analyse, visualise and programmatically access these budget papers. This dataset was prepared by the Department of Treasury and Finance Budget Paper Tables We have made available the data tables from the State Budget Papers in Excel format.

On 22 June 2017, the Hon. Tom Koutsantonis released the 2017–18 State Budget. \r "We are protecting existing jobs and trying to help our traditional manufacturers survive in tougher economic conditions. We are backing our steel-makers in Whyalla and supporting component manufacturers in the car industry to develop new products and markets. We can do all this because of our prudent fiscal management that ensures we deliver a budget that records an operating surplus this year and across the forward estimates, meeting all our fiscal targets. This is a Labor Budget, a budget that will grow the jobs of today and create the jobs of the future. This is a budget that puts South Australians first."

Geoscape G-NAF is the geocoded address database for Australian businesses and governments. It’s the trusted source of geocoded address data for Australia with over 50 million contributed addresses distilled into 15.4 million G-NAF addresses. It is built and maintained by Geoscape Australia using independently examined and validated government data.

From 22 August 2022, Geoscape Australia is making G-NAF available in an additional simplified table format. G-NAF Core makes accessing geocoded addresses easier by utilising less technical effort.

G-NAF Core will be updated on a quarterly basis along with G-NAF.

Further information about contributors to G-NAF is available here.

With more than 15 million Australian physical address record, G-NAF is one of the most ubiquitous and powerful spatial datasets. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.

Updated versions of G-NAF are published on a quarterly basis. Previous versions are available here

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Changes in the May 2025 release

• Nationally, the May 2025 update of G-NAF shows an overall increase of 47,194 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,753,927 of which 14,909,770 or 94.64% are principal.

• At some locations, there are unit-numbered addresses that appear to be duplicate addresses. Geoscape is working to identify these locations and include these addresses as separate addresses in G-NAF. To facilitate this process, some secondary addresses have had the word RETAIL added to their building names. In the first instance, this process is being progressively rolled out to identified locations, but it is expected that the requirement for this will become ongoing.

• There is one new locality in G-NAF: Keswick Island, QLD.

• The source data used for generating G-NAF STREET_LOCALITY_POINT data in New South Wales has an updated datum and changed from GDA94 to GDA2020. This has resulted in updates to the STREET_LOCALITY_POINT geometry for approximately 91,000 records, however, more than 95% of these have moved less than a metre.

• Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.

Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.

Additional information: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

License Information

Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)

The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added.

The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.

End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

_G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

Preferred attribution for Adapted Material:

Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

What to Expect When You Download G-NAF

G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.

The National Reef Monitoring Network brings together shallow reef surveys conducted around Australia into a centralised database. The IMOS National Reef Monitoring Network sub-Facility collates, cleans, stores and makes this data rapidly available from contributors including: Reef Life Survey, Parks Australia, Department of Biodiversity, Conservation and Attractions (Western Australia), Department of Environment, Water and Natural Resources (South Australia), Department of Primary Industries (New South Wales), Tasmanian Parks and Wildlife Service and Parks Victoria.

The data provided by the National Reef Monitoring Network contributes to establishing and supporting national marine baselines, and assisting with the management of Commonwealth and State marine reserves.

Reef Life Survey (RLS) and the Australian Temperate Reef Network (ATRC) aims to improve biodiversity conservation and the sustainable management of marine resources by coordinating surveys of rocky and coral reefs using scientific methods, with the ultimate goal to improve coastal stewardship. Our activities depend on the skills of marine scientists, experienced and motivated recreational SCUBA divers, partnerships with management agencies and university researchers, and active input from the ATRC partners and RLS Advisory Committee.

RLS and ATRC data are freely available to the public for non-profit purposes, so not only managers, but also groups such as local dive clubs or schools may use these data to look at changes over time in their own local reefs. By making data freely available and through public outputs, RLS and ATRC aims to raise broader community awareness of the status of Australia?s marine biodiversity and associated conservation issues.

This dataset contains records of bony fishes and elasmobranchs collected by Reef Life Survey (RLS) and Australian Temperate Reef Collaboration (ATRC) divers and partners along 50m transects on shallow rocky and coral reefs using standard methods. Abundance information is available for all species recorded within quantitative survey limits (50 x 5 m swathes either side of the transect line, each distinguished as a 'Block'), with size and biomass data also included when available. These observations form the Method 1 component of the surveys.

This dataset supersedes the RLS specific "Reef Life Survey (RLS): Global reef fish dataset" collection that was available at https://catalogue-rls.imas.utas.edu.au/geonetwork/srv/en/metadata.show?uuid=9c766140-9e72-4bfb-8f04-d51038355c59 (provision of data was stopped in June 2021).

The Premier’s Community Initiatives Fund has been established by the Premier of South Australia to provide financial assistance to organisations that offer direct services and support to members of the South Australian Community, but do not receive mainstream funding. The Premier’s Community Initiatives Fund provides financial assistance for projects that benefit people who are disadvantaged, people with a disability or socially isolated members of the South Australian community. The objective of the Fund is to make available grants of up to $10,000 to assist organisations to undertake a one-off project that will benefit the South Australian community. The dataset contains information on the successful and unsuccessful organisations, the projects and outcomes, location of the project by suburb and electorate and the approved amount of the grant.

The Biological Databases of South Australia (BDBSA) is South Australia's flora and fauna database that stores and manages specimen and observation records. This record is the fauna component that contains over 2.3 million measurements collected from over 200,000 sites, across 726 species since 1976. This dataset includes occurrence data and morphometric information for invertebrates, fish, mammals, birds, reptiles and amphibians. The resulting database provides a comprehensive record of biodiversity across sites visited during a diverse range of biodiversity projects undertaken in South Australia and provides a basis for future monitoring or other relevant work such as species modelling.

Only validated BDBSA data is made publicly available and all records of sensitive taxa have been masked from the dataset. Data is accessible from the TERN EcoPlots portal, which provides the ability to extract subsets of fauna data across multiple data collections and bioregions for more than 27 variables including animal body size, body length, head length, number of individual animals, and number of individual plants.

Long-term monitoring of waterbirds in the Coorong and Lower Lakes in South Australia is undertaken by the University of Adelaide and forms part of the annual waterbird census in the Lower Lakes, Coorong and the Murray Mouth (LLCMM) region. Waterbird monitoring in the Coorong commenced in 2000, and it expanded in 2009 to include the Lower Lakes. \r The LLCMM region is a Ramsar-listed wetland of international importance for migratory waterbirds. It is also one of the icon sites under The Living Murray program. The condition of the LLCMM region, and waterbird recruitment and populations, have been identified as targets against which to assess progress towards achieving the objectives of the Murray-Darling Basin Plan. The waterbird census data and findings form part of the ecological information used for this assessment.\r The 2016-17 monitoring program was funded by the Murray-Darling Basin Authority (MDBA). Between 2000 and 2016, the MDBA, South Australia’s Department of Environment, Water and Natural Resources (DEWNR), Nature Foundation South Australia, Earthwatch Australia and the University of Adelaide funded the monitoring program in different years.\r The MDBA has made the waterbird databases and related resources publicly available on data.gov.au as part of its commitment to the Australian Government policy on public data and information. The terms and conditions for using the data and related resources from this website can be found at https://www.data.gov.au/about. \r

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

For a more detailed description of the dataset and the coding process, see the codebook available in the .zip-file.

Purpose:

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

An investigation was made into the technologies involved in the automatic transfer of digital data from the remote areas of SA to the SADME Core Library Complex Glenside, to define the most economical approaches to the implementation of a totally... An investigation was made into the technologies involved in the automatic transfer of digital data from the remote areas of SA to the SADME Core Library Complex Glenside, to define the most economical approaches to the implementation of a totally electronic system. Covers the current acquisition equipment in the field, proposed extensions, current data transmission methods and alternatives that are and will become available.

The product consists of 8,595 line kilometres of time‐domain airborne electromagnetic (AEM) geophysical data acquired over part of the Musgrave Province in South Australia. This product release also includes electrical conductivity depth images derived from the dataset, and the survey operations and processing report.

The data were acquired using the airborne High Moment TEMPEST® electromagnetic and magnetic system, which covered a survey area that includes the south western portion of the WOODROFFE 1:250K Map Sheet (Crombie, Carbeena and western half of the Eunyarinna 1:100K Map Sheets); the northwestern portion of the LINDSAY 1:250K Map Sheet (northern half of the Moombunya and Moolalpinna 1:100K map sheets and northwestern quarter of the Willinna 1:100K map sheet). The survey lines where oriented N-S and flown 2km line apart.

The survey was funded by the Government of South Australia, as part of the Plan for Accelerating Exploration (PACE) Initiative, through the Department of State Development, (DSD). The survey was managed by Geoscience Australia as part of a national collaborative framework project agreement with SA. The principal objective of this project was to capture a baseline geoscientific dataset to provide further information on the geological context and groundwater resource potential, of the central part of the South Australian Musgrave Province.

Geoscience Australia contracted CGG Aviation (Australia) Pty to acquire High Moment TEMPEST® electromagnetic and magnetic data, between August and September 2016. The data were processed and modelled by CGG using its in‐house processing conductivity depth transform techniques.

The Musgrave Province in far north of South Australia is one of the last true exploration frontier areas in Australia, which extends into Northern Territory and Western Australia. The Musgrave Province is composed primarily of granulite facies quartzo-feldspathic metasedimentary and meta-igneous rocks, and includes a suite of layered mafic to ultramafic intrusions known as the Giles Complex. This geological setting has proven to be highly prospective for Ni-Cu-PGE mineral systems in the bordering states. A good example of this is the discovery of the Nebo and Babel nickel-copper-PGE sulphide deposits in 2000, followed by a subsequent number of other nickel (Ni), copper (Cu) and gold (Au) discoveries.

In South Australia, major discoveries have eluded mineral explorers and exploration activity has fallen behind that of the Northern Territory and Western Australia. This divergence is largely due to issues around land access and a lack of contemporary precompetitive geoscientific information and data. The limited surface mapping combined with extensive regolith cover and incomplete geophysical, geochemical and geochronological data sets make it difficult for new explorers to fully appreciate the full economic potential of the Musgrave Province.

The regional AEM survey data will be used to inform the distribution of cover sequences that obscure the basement geology and provide insight into the variation and characteristics of the overlaying sequences. The increased definition in the distribution of cover sequences and their variation and characteristics of the overlaying sequences will allow explorers to better assess exploration opportunities in the area.

The new AEM data should also assist in the definition of the groundwater resource potential of the region and help characterise the pre-Pliocene palaeovalley systems known to exist in the region. The selection of the survey area was undertaken through a consultative process involving the CSIRO, Geological Survey of South Australia and the exploration companies currently active in the region (including industry survey partner PepinNini Minerals Ltd).

The data will be available from Geoscience Australia’s web site free of charge. It will also be available through the South Australian Government’s SARIG website at https://map.sarig.sa.gov.au. The data will also feed into the precompetitive exploration workflow developed and executed by the GSSA and inform a new suite of value-added products directed at the exploration community.

Transform Your Business with Our Comprehensive B2B Marketing Data Our B2B Marketing Data is designed to be a cornerstone for data-driven professionals looking to optimize their business strategies. With an unwavering commitment to data integrity and quality, our dataset empowers you to make informed decisions, enhance your outreach efforts, and drive business growth.

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There are over 24,000 specimens in this collection, including skulls, skins, skeletons, spirit specimens, photographs and frozen tissue. It includes over 1600 marine mammals and its comprehensiveness makes this collection the best of its kind in Australia. Other strengths of the collection include South Australian arid zone native mammals, many specimens of extinct species such as the thylacine and large numbers of bat species. The collection has also historical importance as it includes many specimens from early expeditions in Australia and to the subantarctic Islands and Antarctica. Well-known people such as Sir Douglas Mawson, Edgar R. Waite and Hedley Finlayson have contributed to the collection. The mammal collection includes sub-fossils and remains from owl pellets. This collection consists entirely of Australian material with 20000 - 25000 specimens covering 76 mammal species (including introduced species). The collection is made up of bulk bone deposits from the floor of caves, bones excavated from sinkholes, bones extracted from predator scats (eg. dingoes, foxes and Ghost Bats), pellets from birds of prey, particularly barn owls (both recent and pre-settlement material), and stick nest rat nests and middens. The sub-fossil collection is the second best of its kind in Australia. The SA Museum manages this dataset using the KE EMu collection management system. It is interpreted into the Darwin Core metadata schema (DwC) and semi-regularly exported to the Atlas of Living Australia (ALA: http://www.ala.org.au/) and the Online Zoological Collections of Australian Museums (OZCAM: http://www.ozcam.org.au/). Information about Darwin Core can be found here: http://rs.tdwg.org/dwc/index.htm. Data sourced from Australian museums on both the ALA and OZCAM should be identical, but on ALA they are combined with observational data from citizen science initiatives and other sources. Both of those sites make it possible to combine, interrogate and analyse data through web services such as the Spatial Analysis Portal (http://spatial.ala.org.au/). In the Spatial Portal ALA data can be combined with meteorological and other environmental data sourced from and made accessible by relevant government agencies. Data about endangered species are either withheld from online publication, or coordinates or other data are obscured on the ALA and OZCAM. In those circumstances more specific information is available directly from SA Museum collection managers if it is genuinely required for research purposes. SA Museum data can be downloaded in full from the Atlas of Living Australia, or broken down into discipline specific parts (e.g. Herpetology, Mammalogy etc). On download the ALA will request an email address (not mandatory) and a reason for download (mandatory) – this is required to track usage of the ALA data to help data providers determine priorities for upload and improvement.

Housing Affordability Supply and Demand Data. Number of South Australian households paying more than 30% of their household income on housing (rent or mortgage) broken down by very low, low and moderate income brackets. This dataset relates to section 4, Housing Stress, of the Affordability master reports produced by the SA Housing Authority. Each master report covers one Local Government Area and is entitled ‘Housing Affordability – Demand and Supply by Local Government Area’. The Demand for Supply for LGA reports are available online at: https://data.sa.gov.au/data/dataset/housing-affordability-demand-and-supply-by-local-government-area Explanatory Notes: Data sourced from the Australian Bureau of Statistics (ABS), Census for Population and Housing and it is updated every 5 years in line with the ABS Census. The nature of the income imputation means that the reported proportion may significantly overstate the true proportion. Census housing stress data is best used in comparing results over Censuses (ie did it increase or decrease in an area) rather than using it to ascertain what proportion of households were in rental stress. Income bands are based on household income. High income households can also experience rental stress. These households are included in the total but not identified separately. Data is representative of households in very low, low and moderate income brackets. Please note that 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.