Since 2012, Geoscience Australia (GA) has been providing spatial support and advice to the National Situation Room (NSR) (formally the Crisis Coordination Centre (CCC)) within Emergency Management Australia (EMA) as part of GA’s collaboration with the Attorney-General’s Department. A key information requirement identified by EMA was the need to quickly understand what is in an event area. To address this requirement Geoscience Australia designed the Exposure Report which greatly simplifies the interpretation of exposure information for timely emergency response and recovery decision-making. The Exposure Report is generated by extracting the relevant attributes from the Geoscience Australia National Exposure information System (NEXIS) such as demographics, building, business, agriculture, institutions and infrastructure in an event footprint, geographical boundary or potentially threatened area. This automated process quickly presents the required information in a clear and easily accessible report detailing estimates of what exists in the event area. By improving the timeliness and accuracy of information used by the NSR, Geoscience Australia is enhancing the government’s ability to respond to disaster and activate appropriate financial assistance for recovery.

A publicly available AGOL Dashboard that periodically updates to show the status of requests made to the Australian Exposure Information Platform (AEIP), categorised as Running, Queued and Completed (www.aeip.ga.gov.au)

Introductory video to explaining Linked Data and DGGS practices and philosophies

Linked Data refers to a collection of interrelated datasets on the Web expressed in a standard structure. These Linked Data and relationships among them can be reached and managed by Semantic Web tools. Linked Data enables large scale integration of and reasoning on data on the Web. This cookbook is to documents the processes and workflows required to create a Linked Data API for a dataset in the Foundation Base Project in Geoscience Australia (GA) and further publish it on the AWS.

The pace, with which government agencies, researchers, industry, and the public need to react to national and international challenges of economic, environmental, and social natures, is constantly changing and rapidly increasing. Responses to the global COVID-19 pandemic event, the 2020 Australian bushfire and 2021 flood crisis situations are recent examples of these requirements. Decisions are no longer made on information or data coming from a single source or discipline or a solitary aspect of life: the issues of today are too complex. Solving complex issues requires seamless integration of data across multiple domains and understanding and consideration of potential impacts on businesses, the economy, and the environment. Modern technologies, easy access to information on the web, abundance of openly available data shifts is not enough to overcome previous limitations of dealing with data and information. Data and software have to be Findable, Accessible, Interoperable and Reusable (FAIR), processes have to be transparent, verifiable and trusted. The approaches toward data integration, analysis, evaluation, and access require rethinking to: - Support building flexible re-usable and re-purposeful data and information solutions serving multiple domains and communities. - Enable timely and effective delivery of complex solutions to enable effective decision and policy making. The unifying factor for these events is location: everything is happening somewhere at some time. Inconsistent representation of location (e.g. coordinates, statistical aggregations, and descriptions) and the use of multiple techniques to represent the same data creates difficulty in spatially integrating multiple data streams often from independent sources and providers. To use location for integration, location information needs to be embedded within the datasets and metadata, describing those datasets, so those datasets and metadata would become ‘spatially enabled’.

<p>Iron oxide-copper-gold (IOCG) mineral systems are a desirable undercover exploration target due to their large alteration footprint and potentially high metal content. To assist in understanding the potential for IOCG mineral systems beneath cover in the Tennant Creek to Mount Isa region as part of Exploring for the Future, a predictive mineral potential assessment has been undertaken using a knowledge-based, mineral systems approach.<p>This mineral potential assessment uses a 2D, GIS-based workflow to qualitatively map four key mineral system components: (1) Sources of metals, fluids and ligands, (2) Energy to drive fluid flow, (3) Fluid flow pathways and architecture, and (4) Deposition mechanisms, such as redox or chemical gradients. For each of these key mineral system components theoretical criteria, representing important ore-forming processes, were identified and translated into mappable proxies using a wide range of input datasets. Each of these criteria are weighted and combined using an established workflow to produce the final map of IOCG potential, all of which is well documented in the accompanying IOCG Assessment Criteria Table.<p>Two assessments have been undertaken. The first is a comprehensive assessment containing all available geospatial information and is highly reliant on the level of geological knowledge. As such, it preferentially highlights mineral potential in well-understood areas, such as outcropping regions and performs less well in covered areas, where there is a greater likelihood of data gaps. The second assessment utilises only datasets which can be mapped consistently across the assessment area. As such, these are predominately based on geophysical data and are more consistent in assessing exposed and covered areas. However, far fewer criteria are included in this assessment.<p>Both assessment highlight new areas of interest in underexplored regions, of particular interest a SW-NE corridor to the East of Tennant Creek of moderate/high potential in the Barkly region. This corridor extends to an area of moderate potential in the Murphy Inlier region near the Gulf of Carpentaria on the NT/QLD border.

Fuelled by a virtual explosion in digital capabilities the world is changing very fast and the field of Geoscience is no exception. Geoscience Australia (GA) has undergone a rapid digital transformation in the past 5 years. This has in part been driven by increasing organisational ICT costs, and partly by whole of government and more broadly global changes to the digital environment such as; growth in data, cheaper, more available cloud and infrastructure, new advances in AI and ML, new models for continuous development (DevOps) and public expectations that data will be available and accessible. The overarching principle of Geoscience Australia's Digital Strategy 2019-22 acknowledges that GA’s Enterprise ICT is inherently integrated with scientific data and ICT requirements, and more broadly these are the foundation of the digital science we are respected for at GA. As such, this strategy brings all three of these components together in a whole of agency digital strategy. The Digital Strategy focuses on strong foundations, systematic experimentation, data-driven science and digital culture and capability. Eighteen different strategies lie under these themes to help guide GA's focus for the next 3 years. There are also a number of high level KPI’s designed to help us measure our success.

Following the successful outcomes of the Tennant Creek-Mt Isa (TISA) mineral potential assessment (Murr et al., 2019; Skirrow et al., 2019), the methodology has been expanded to encompass the entire North Australian Craton (NAC). Like its predecessor, this assessment uses a knowledge-based, data-rich mineral systems approach to predict the potential for iron oxide-copper-gold (IOCG) mineralisation. With their high metal yield and large alteration footprint, IOCG mineral systems remain an attractive target in directing exploration efforts towards undercover regions. This mineral potential assessment uses a 2D GIS-based workflow to map four key mineral system components: (1) Sources of metals, fluids and ligands, (2) Energy to drive fluid flow, (3) Fluid flow pathways and architecture, and (4) Deposition mechanisms, such as redox or chemical gradients. For each of these key mineral system components, theoretical criteria representing important ore-forming processes were identified and translated into mappable proxies using a wide range of input datasets. Each of these criterion are weighted and combined using an established workflow to produce a models of IOCG potential. Metadata and selection rational are documented in the accompanying NAC IOCG Assessment Criteria Table. Two scenarios were modelled for this assessment. The first is a comprehensive assessment, targeting pre-Neoproterozoic mineral systems (>1500 Ma), using a combination of interpreted, geological and geophysical datasets. As geological interpretations are subjective to the geological knowledge of the interpreter, well-documented areas, such as shallow pre-Neoproterozoic basement, have a greater density of data. This increase in data density can create an inherent bias in the modelled result towards previously explored shallow terrains. The second assessment utilises only datasets which can be mapped consistently across the assessment area. As such, these are predominately based on geophysical data and are more consistent in assessing exposed and covered areas. However, far fewer criteria are included in this assessment, and observations are reflective of only the modern geological environment. Both assessments highlight existing mineral fields in WA, NT and QLD, and suggest that these regions extend under cover. Furthermore, regions not previously known for IOCG mineralisation display a high modelled potential, offering exploration prospects in previously unknown or discounted areas.

<p>Digital Earth Australia manages a cloud based service that makes use of open source software and open standards to deliver satellite imagery to its clients. <p>In conjunction with Frontier SI and Commonwealth Scientific and Industrial Research Organisation, Geoscience Australia’s Digital Earth Australia project has developed a cloud architecture that utilizes the Open Data Cube (ODC) to deliver Earth Observation (EO) data through Open Geospatial Consortium (OGC) API standards, interactive Jupyter notebooks and direct file access.​ <p>This infrastructure enables EO data to be used to make decisions by industry and government partners, and reduces the time required to deliver new EO data products. ​ <p>To store the data, DEA utilises Amazon Web Services (AWS) Object store: Simple Storage Service (S3) to hold an archive of Cloud Optimised GeoTIFFs (COGs). ​ <p>This data is indexed by Open Data Cube (ODC) an open source python library. DEA deploy processing, visualisation and analysis applications that make use of the indexed data. This method reduces the duplication of code and effort and creates an extensible framework for delivering data.

HiQGA is a general purpose software package for spatial statistical inference, geophysical forward modeling, Bayesian inference and inversion (both deterministic and probabilistic). It includes readily usable geophysical forward operators for airborne electromagnetics (AEM), controlled-source electromagnetics (CSEM) and magnetotellurics (MT). Physics-independent inversion frameworks are provided for probabilistic reversible-jump Markov chain Monte Carlo (rj-MCMC) inversions, with models parametrised by Gaussian processes (Ray and Myer, 2019), as well as deterministic inversions with an "Occam inversion" framework (Constable et al., 1987). In development software for EFTF since 2020