The Gross Domestic Product (GDP) in Australia was worth 1752.19 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Australia represents 1.65 percent of the world economy. This dataset provides - Australia GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied

The following spreadsheets are a flattened version of the data available in the Mines Atlas mapping application.

Operating Mines

The coverage contains data such as locations, mine names, commodity and weblinks. The information was sourced from Geoscience Australia's OZMIN database.

http://www.australianminesatlas.gov.au/mapping/downloads.html

Purpose

This dataset has been used as a proxy dataset to spatially locate volumes of extraction in the Hunter and Gloucester subregions where records from NSW office of Water science with volume were unable to be connected to a bore in NSW NGIS Extract

Dataset History

"This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied

In 2003 - 2004 Geoscience Australia developed the Australian Atlas of Mineral Resources, Mines, and Processing Centres - the Australian Mines Atlas - with its supporting partners Minerals Council of Australia and Department of Resources, Energy and Tourism.

Subsequently, the Mines Atlas is continually being updated with new mineral resource, location data and company web links.

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Aims

The Atlas aims to:

provide an authoritative understanding of Australia's known mineral and energy (solid fuel) assets, mines and production/processing centres (existing and planned)

present factual data that can assist with planning, decision making, investment, education and management of the environment

complement other national data sets dealing with land use, population, soils, agriculture, climate, water and vegetation

show where, and how, the mining industry is placed to continue its contribution to regional development in Australia and sustain its role as a major exporter of mineral commodities.

The Atlas delivers authoritative minerals and mining information to individual Australians and provides a virtual-showcase of the industry for global audiences.

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Objectives

The Atlas was developed as a working tool for use whenever and wherever customers can access the internet. It allows users to examine and evaluate digital spatial data related to the minerals industry against an array of infrastructure, demographic, resource and environmental dimensions.

The key objective of the Atlas is to serve the needs of diverse clients in many ways, including as:

a reliable and up-to-date reference with links to site specific and more detailed information, either directly, as for mineral resources, or through links, such as linking to the website of each particular owner company

an interactive decision support system with small-scale, map-making capability

a framework and instrument for education

an aid to visualise and understand complex issues relating to regional development of mining and mineral processing activities, and identify/promote opportunities for employment in remote areas

an aid to industry research.

Dataset Citation

Geoscience Australia (2015) Operating Mines OZMIN Geoscience Australia 20150201. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/65c0c042-1ba8-47a8-9793-4363672500b9.

Introduction

This Australian English Call Center Speech Dataset for the Real Estate industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English -speaking Real Estate customers. With over 40 hours of unscripted, real-world audio, this dataset captures authentic conversations between customers and real estate agents ideal for building robust ASR models.

Curated by FutureBeeAI, this dataset equips voice AI developers, real estate tech platforms, and NLP researchers with the data needed to create high-accuracy, production-ready models for property-focused use cases.

Speech Data

The dataset features 40 hours of dual-channel call center recordings between native Australian English speakers. Captured in realistic real estate consultation and support contexts, these conversations span a wide array of property-related topics from inquiries to investment advice offering deep domain coverage for AI model development.

Topic Diversity

This speech corpus includes both inbound and outbound calls, featuring positive, neutral, and negative outcomes across a wide range of real estate scenarios.

Such domain-rich variety ensures model generalization across common real estate support conversations.

Transcription

All recordings are accompanied by precise, manually verified transcriptions in JSON format.

These transcriptions streamline ASR and NLP development for English real estate voice applications.

Metadata

Detailed metadata accompanies each participant and conversation:

This enables smart filtering, dialect-focused model training, and structured dataset exploration.

Usage and Applications

This dataset is ideal for voice AI and NLP systems built for the real estate sector:

The online banking penetration rate in Australia was forecast to continuously increase between 2024 and 2029 by in total 4.1 percentage points. After the fifteenth consecutive increasing year, the online banking penetration is estimated to reach 71.28 percent and therefore a new peak in 2029. Notably, the online banking penetration rate of was continuously increasing over the past years.Shown is the estimated percentage of the total population in a given region or country, which makes use of online banking.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

This dataset is an output of a desk audit by Monash University Researcher, Tui McKeown, working with Ken Phillips, executive director of Independent Contractors Australia (ICA), which funded the project. Self-employed people make up 20% of the workforce and are internally recognised as a powerful entrepreneurial and consumer force. However, what is “known” about them is mostly based on assumptions rather than facts. The aims of the project were twofold. The first was to clearly identify and summarise the key features of three of the largest databases and research resources available within Australia for profiling this complex sector. The second is to see what synthesis can be achieved between these three sources as resources and so develop a deeper understanding of this sector. Source data included the Australian Bureau of Statistics (ABS) 2008 Forms of Employment Survey and the 2009 Australian Labour Market report; four reports by the Australian Taxation Office (ATO) into the micro business sector; and from Roy Morgan Research, a 2009 report into the self employed in Australia and the Roy Morgan Research Asteroid database which collected information between January 1999 and December 2008. All data is published in the full report (A desk audit into the data and research on micro-business profiling in Australia) that is available on the ICA website. It provides grounded and accurate information for policy frameworks and will assist those who need to communicate with self-employed people, as well as future PhD students and researchers.

Introduction

This Australian English Call Center Speech Dataset for the Retail and E-commerce industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English speakers. Featuring over 40 hours of real-world, unscripted audio, it provides authentic human-to-human customer service conversations vital for training robust ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, data scientists, and language model researchers to build high-accuracy, production-ready models across retail-focused use cases.

Speech Data

The dataset contains 40 hours of dual-channel call center recordings between native Australian English speakers. Captured in realistic scenarios, these conversations span diverse retail topics from product inquiries to order cancellations, providing a wide context range for model training and testing.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world scenario coverage.

Such variety enhances your model’s ability to generalize across retail-specific voice interactions.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

This granularity supports advanced analytics, dialect filtering, and fine-tuned model evaluation.

Usage and Applications

This dataset is ideal for a range of voice AI and NLP applications:

In 2025, the total revenue of the coffee market in Australia amounted to just over 12.85 billion U.S. dollars. Roast coffee represented around 11.45 billion U.S. dollars of the Australian coffee market that year, with instant coffee representing around 1.4 billion dollars. The Australian coffee market's revenue is expected to reach over 14.9 billion U.S. dollars by 2029.

Exports in Australia decreased to 44075 AUD Million in April from 45141 AUD Million in March of 2025. This dataset provides the latest reported value for - Australia Exports - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In 2025, Australia's at-home coffee market was worth around 1.5 billion U.S. dollars. In comparison, the out-of-home coffee market revenue amounted to around 11.35 billion U.S. dollars that same year. By 2029, the out-of-home coffee market in the country was expected to be worth around 13.2 billion U.S. dollars.

Coles Group recognized a total sales revenue of almost **** billion Australian dollars during the 2024 financial year. This represented a slight increase from the 2023 financial year, in which revenue was measured at around **** billion dollars. The company’s revenue has remained largely around this level since 2015. Coles Group: Key financials Coles Group is one of Australia’s largest and oldest supermarket chains and holds the second-largest share of the country’s grocery retail market. Its major market rival, Woolworths Group, accounts for the largest share, at around ** percent. Across the grocery retail giant's various operating segments, the Coles Group supermarkets segment generated the highest revenue in the 2024 financial year at approximately ** billion Australian dollars. The company has enjoyed a consistently rising profit after tax since 2021, with profits exceeding *** billion Australian dollars in 2024. Australia’s supermarket industry The supermarkets and grocery store retail industry in Australia has witnessed year-on-year growth since 2015, with over *** billion Australian dollars generated by the industry in the 2024 financial year. Around ***** supermarkets and grocery stores were in operation across Australia by the end of the 2024 financial year, with the largest number of stores located in New South Wales, Victoria, and Queensland.

Introduction

This Australian English Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of English speech recognition, spoken language understanding, and conversational AI systems. With 40 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 40 Hours of dual-channel call center conversations between native Australian English speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

Australia Exports to United States was US$14.73 Billion during 2024, according to the United Nations COMTRADE database on international trade. Australia Exports to United States - data, historical chart and statistics - was last updated on July of 2025.