We are investing a total of $2.8 million, with $4.215 million co-investment from collaborating organisations, for seven leading-edge projects that will add value by aggregating, harmonising and integrating complementary data across Australia’s national facilities.

ProjectsNCRIS collaborators
OzBarley: from genome to phenome and back again (https://doi.org/10.47486/XN001): Modern cereal breeding and crop improvement rely on genotypic and phenotypic data to identify important genetic regions that drive crop performance such as high yield, salinity, drought or heat tolerance. However, there are few public and trusted data assets available to Australian researchers and breeders. The aim of the OzBarley project is to develop a publicly available Genotype-to-Phenotype (G2P) data asset meeting FAIR principles that is specifically designed by, and for, Australian researchers and breeders focusing on barley as an economically important model crop.

The OzBarley G2P data asset will provide the basis for the discovery of important genes and will reduce the barrier to entry for future barley funding applications. OzBarley will serve as the foundation for researchers to grow the data asset in the future by contributing additional data sets that follow the data standards set out within this project.

Beneficiaries of the OzBarley project will be academics and breeders alike and it will provide a platform for public-private collaboration, a direct path to market and ultimately improved barley varieties for Australian growers.
Australian Plant Phenomics Facility (APPF)
Bioplatforms Australia (BPA)
Building a National High-Resolution Geophysics Reference Collection for 2030 Computation (https://doi.org/10.47486/XN002): Geophysics data has many applications in the resources sector and is also vital in minimising risk and damage from natural hazards and human activities. Many geophysical datasets have never been publicly released because in some domains it is not general practice to make underpinning raw data accessible, and/or there is no infrastructure capability to make large volume data accessible. Large volumes of geophysical data have been acquired by universities, industry, Federal/State Government agencies since 1950, including recent collections by the AuScope and TERN NCRIS facilities.

This project will bring the rawer forms of AuScope and TERN data to combine with existing Government geophysical data assets and made FAIR using supercomputers at NCI. This integration will enable more rapid data processing for 2030 next-generation scalable, data-intensive computation including Artificial Intelligence (AI)/Machine Learning (ML) and data assimilation. Research teams will be able to analyse large volumes of high-resolution data and see the quality of their algorithms quickly.
National Computational Infrastructure (NCI)
Terrestrial Ecosystem Research Network (TERN)
Integrating clinical and experimental genotype-phenotype data for biomedical discovery and disease management (https://doi.org/10.47486/XN003): Mice and humans share a similar set of genes and as a result their biology has played a critical role in medical advancements in recent years. Our understanding of key observable characteristics (phenotypes) in mice has helped drive medical interventions for conditions such as obesity, diabetes, immune defects, blood cancers such as leukaemia and many more. However, a deeper functional understanding of the genomic determinants of human health and disease is required to optimise clinical management and advance biomedical research. In particular, more efficient links between human and experimental datasets are required.

This project will result in the linkage of two of Australia’s most important biomedical datasets, in a highly curated, user-friendly and accessible environment. The new data asset will improve researcher ability to discover and experimentally validate gene function to improve disease diagnosis and treatment, especially in clinical human studies where state-of -the-art genomic technologies have been used to identify genetic variation related to health and disease. Use cases for the data asset include pursuing the most promising variants that have supportive evidence from both datasets, as potential drivers of disease (pathogenic variants) or novel drug targets (protective variants); improve clinical cancer diagnosis in the young, and improve overall understanding of genetic drivers of cancer; improve the ability to interpret potentially pathogenic variation in human autoimmune disease.
Phenomics Australia (PA)
Bioplatforms Australia (BPA)
Data nexus: coupling genomic and oceanographic data to enhance integration (https://doi.org/10.47486/XN004): Every millilitre of the vast ocean ecosystem provides a habitat for millions of microorganisms that modulate ocean health and ultimately control global climate. However, the scales, tools and data products used to study the ocean are very different to those used to study microbes, and both research disciplines require extensive, domain specific skills that have little overlap.

This project will drive the integration of large DNA sequencing datasets that describe the composition and function of Australian marine microbial assemblages, with oceanographic datasets (e.g. water temperature, salinity, nutrients, dissolved oxygen, current direction) that describe the form and dynamics of Australian ocean ecosystems. The integration of these very different data types will accelerate our understanding of how changing environmental conditions drive the microbial processes that sustain the planet, while enabling non-microbial researchers direct access to key microbial insights that will enhance modelling of ecological and biogeochemical processes. This type of data integration does not exist anywhere else in the world and will provide great advantages to the Australian research community. The output dataset will exploit a wealth of existing information to develop data resources and tools that are compatible with ideas and needs from the community, including human health and wellbeing; management of protected/high value ecologies, and safeguarding Australian aquaculture and fisheries.
Integrated Marine Observing System (IMOS)
Bioplatforms Australia (BPA)
Ecosystem data integration to support national environmental reporting (https://doi.org/10.47486/XN005): The Australian Government’s Department of Agriculture, Water and the Environment (DAWE) produces the national State of the Environment (SoE) report every five years to meet statutory reporting obligations and update all Australians and decision-makers on environmental state, pressures, trends and key issues confronting the nation. SoE relies extensively on high-quality national data.

This project is a partnership between DAWE, the Atlas of Living Australia (ALA), Integrated Marine Observing System (IMOS), and Terrestrial Ecosystem Research Network (TERN) to develop new cross-facility data assets to support national environmental reporting. Integrated data products will have significant value beyond SoE with value delivered to the research sector and related government programs. The new national and highly visible FAIR data will have application in areas including environmental accounting and impact assessments; land, inland waters, coastal and marine management; agricultural development and biosecurity. Consolidating these assets in this way will serve as a showcase for NCRIS and for the significant contribution NCRIS research infrastructure is making to understanding the Australian environment. High-quality environmental information is also critical for Australia to meet its reporting obligations under international conventions (e.g. United Nations Sustainable Development Goals, Aichi Biodiversity Targets, United Nations Land Degradation Neutrality).
Atlas of Living Australia (ALA)
Terrestrial Ecosystem Research Network (TERN)
Integrated Marine Observing System (IMOS)
A National Scale Data Asset to Integrate Molecular Imaging with Bio-analytics (https://doi.org/10.47486/XN006): Electron Microscopy (EM) has advanced to the point where it is possible to determine the 3D structure of individual proteins in situ. However, a fundamental limitation of this technique is that the identification of proteins in the region of interest is exceptionally challenging, and relies on exhaustive comparative experiments.

This project will develop a new resource to organise and navigate multidimensional data and drive connectivity between molecular imaging and proteomic datasets. Specifically, it will enable a new, publicly accessible national scale data asset to underpin the integration of molecular imaging with bio-analytics, thus driving discovery research across the whole of the life sciences.

The resource will permit Australian researchers to attain one of the grand ambitions of biologists and understand the precise molecular makeup of the intracellular environment. Artificial Intelligence (AI) bioinformatics approaches will be used to seamlessly integrate and interrogate high-resolution imaging data (derived from optical and electron microscopy (EM) and X-ray crystallography) with proteomic/genomic data and gene ontology/protein interaction network data. Currently, this information is distributed across numerous disparate databases, precluding the ready interpretation and analysis of imaging data such as 3D tomograms output by the latest generation optical and electron microscopes. The online platform will host the final, released and annotated datasets and permit presentation of the data to the community and have immediate application in fields such as drug discovery, infectious diseases and molecular diagnostics.
European Molecular Biology Laboratory Australia (EMBL)
Microscopy Australia
Bioplatforms Australia (BPA)
Australian Urban Health Indicators (https://doi.org/10.47486/XN007): The Australian Urban Health Indicators project will develop a suite of new indicator data assets that will improve our understanding of the health of Australian urban and regional populations and identify incidence patterns and key risk factors across regions and population cohorts. The project will integrate health, socio-economic, environmental and other urban datasets to provide a more holistic spatially-explicit understanding of the health of the urban population. By integrating data on the social determinants of health with population health and health service planning data, new insightful, indicator data assets can be generated more rapidly, easily and accurately. The AusUrb-HI project will focus on three indicators:

  • Cancer Determinants
  • Heat Health Vulnerability
  • Urban Liveability and Health
These new indicators will allow health, urban and social infrastructure planners and policy makers to develop targeted policies and actions, that take into account regional differences between health outcomes and social, economic and environmental determinants.
Australian Urban Research Network (AURIN)
Population Health Research Network (PHRN)

These projects are still subject to contract execution.

Key resources

  • Read the news article about the successful projects