Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0775510
Funder
Australian Research Council
Funding Amount
$400,000.00
Summary
Australian Social Science Data Archive: Network Extension and Sub-archive Development. The Australian Social Science Data Archive is a national facility that allows all researchers and members of the public to access a wide range of social science data sets for on-line analysis. The archive contains data that covers forty years of social, political and economic surveys. The archive also acts as a gateway for social science researchers to access data from equivalent overseas institutions in North ....Australian Social Science Data Archive: Network Extension and Sub-archive Development. The Australian Social Science Data Archive is a national facility that allows all researchers and members of the public to access a wide range of social science data sets for on-line analysis. The archive contains data that covers forty years of social, political and economic surveys. The archive also acts as a gateway for social science researchers to access data from equivalent overseas institutions in North America, the European Union and OECD countries.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100031
Funder
Australian Research Council
Funding Amount
$3,973,202.00
Summary
ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand ....ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.Read moreRead less
ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less
Leaves in 3D: photosynthesis and water-use efficiency. This project aims to develop leaf anatomical ideotypes with improved photosynthesis and water-use efficiency for wheat, rice, chickpea and cotton using novel three dimensional imaging and modelling techniques. This project expects to generate new understanding of the role of leaf anatomy on leaf function. Expected outcomes of this project include the world's first 3D spatially-explicit, anatomically accurate model of leaves of crop plants to ....Leaves in 3D: photosynthesis and water-use efficiency. This project aims to develop leaf anatomical ideotypes with improved photosynthesis and water-use efficiency for wheat, rice, chickpea and cotton using novel three dimensional imaging and modelling techniques. This project expects to generate new understanding of the role of leaf anatomy on leaf function. Expected outcomes of this project include the world's first 3D spatially-explicit, anatomically accurate model of leaves of crop plants to allow virtual experiments identifying optimized anatomy for improved photosynthetic performance. Benefits to the agricultural industry include increased crop productivity and water-use efficiency to meet future global food demand and to make the most of Australia's limited water resourcesRead moreRead less
How effective are environmental flows? Novel approaches for monitoring and assessing ecological responses to large-scale flow alteration. Australia has begun a multi-billion dollar program to return water to stressed rivers as environmental flows. However, during times of unprecedented water scarcity, such an investment in the environment can be controversial because the ecological benefits of released water are mostly poorly understood. This project will demonstrate the effectiveness of environ ....How effective are environmental flows? Novel approaches for monitoring and assessing ecological responses to large-scale flow alteration. Australia has begun a multi-billion dollar program to return water to stressed rivers as environmental flows. However, during times of unprecedented water scarcity, such an investment in the environment can be controversial because the ecological benefits of released water are mostly poorly understood. This project will demonstrate the effectiveness of environmental flows, and promote greater understanding of the links between flow patterns and river health. The project will build upon existing knowledge to create a sound framework for planning, monitoring, and evaluation of environmental watering decisions across regional Australia, greatly improving our ability to sustainably manage rivers into the future.Read moreRead less
Building models for complex data. The purpose of this project is to better understand the process of building statistical models and construct new methods for building models for particular kinds of complex data. The expected outcomes include a new way of thinking about model building and practical tools which together enable us to get more value out of analysing complex data.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0989083
Funder
Australian Research Council
Funding Amount
$550,000.00
Summary
Australian Social Science Data Archive: Provision of Advanced Research Infrastructure and Collaborative Environment. The Australian Social Science Data Archive (ASSDA) supports researchers in a wide range of social science and humanities disciplines. These researchers are both primary and secondary users of data collected across a range of economic, social, political and cultural areas. Increasingly, complex public policy problems require multi-disciplinary solutions based on a range of data sou ....Australian Social Science Data Archive: Provision of Advanced Research Infrastructure and Collaborative Environment. The Australian Social Science Data Archive (ASSDA) supports researchers in a wide range of social science and humanities disciplines. These researchers are both primary and secondary users of data collected across a range of economic, social, political and cultural areas. Increasingly, complex public policy problems require multi-disciplinary solutions based on a range of data sources to address these problems. This proposal provides a means for Australia's leading edge researchers to advance the knowledge base that can lead to the development of strong evidence based policy. The open access policies of ASSDA ensures that the general public, media, non-government organisation (NGOs) and government agencies are able to examine the public use data sets that are used by researchers to arrive at their conclusions.Read moreRead less
Bayesian inversion and computation applied to atmospheric flux fields. This project aims to make use of unprecedented sources of measurements, from remote sensing and in situ data, to estimate the sources and sinks of greenhouse gases. An overabundance of greenhouse gases in Earth's atmosphere is arguably the most serious long-term threat to the planet's ecosystems. This project will combine measurement uncertainties, process uncertainties in the physical transport models, and any parameter unce ....Bayesian inversion and computation applied to atmospheric flux fields. This project aims to make use of unprecedented sources of measurements, from remote sensing and in situ data, to estimate the sources and sinks of greenhouse gases. An overabundance of greenhouse gases in Earth's atmosphere is arguably the most serious long-term threat to the planet's ecosystems. This project will combine measurement uncertainties, process uncertainties in the physical transport models, and any parameter uncertainties, to provide reliable uncertainty quantification for the estimates. This will be achieved with new Bayesian spatio-temporal inversions and big-data computational strategies. The resulting statistical inferences on greenhouse-gas flux fields will enable the development of critical mitigation strategies. These new statistical inferences will be a valuable resource to policy-makers worldwide, who are assessing progress towards global commitments. Further, the final product may assist in developing cost-effective mitigation strategies in the presence of uncertainty.Read moreRead less
Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically an ....Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically and clinically significant discoveries in biomedical research. This project will help Australian researchers in statistics and users of statistics (from fields as diverse as biology, ecology, medicine, finance, agriculture and the social sciences) to make better predictions that are easier to understand.Read moreRead less
Prediction, inference and their application to modelling correlated data. This project aims to create new, improved methods for prediction and making inference about predictions for a variety of correlated data types through inventing sophisticated and novel resampling schemes such as the generalised fast bootstrap and repeated partial permutation. The research will impact on both the theory and practice of statistics and on substantive fields which use mixed or compositional models to analyse d ....Prediction, inference and their application to modelling correlated data. This project aims to create new, improved methods for prediction and making inference about predictions for a variety of correlated data types through inventing sophisticated and novel resampling schemes such as the generalised fast bootstrap and repeated partial permutation. The research will impact on both the theory and practice of statistics and on substantive fields which use mixed or compositional models to analyse dependent data. This will be a significant improvement in the assessment and stability of statistical models in areas such as social, ecological and geological sciences.Read moreRead less