Objective 11 – Collaborate with other sectors, including small and medium-sized enterprises, community organisations and academia
We are drawing on a diversity of thinking and leading-edge skills from businesses, academia and the Australian community, to solve real and challenging problems. This means that we’re simplifying the process for small and medium enterprises to compete for government business. We’re making it easier for academics to access public data to support their research through data.gov.au and we’re engaging with community organisations and individuals to really understand your needs. We’re also finding ways to bring these sectors together to make the most of their different skills and to create better solutions for you.
The Digital Marketplace to date has awarded more than $2.73 billion worth of contracts to sellers, with 70% of this value going to SMEs in the 2019-20 Financial Year.
The NSW Spatial Digital Twin is one the largest in the world (in terms of land coverage and data being delivered), supporting 8,000 square kilometres with 3D data.
Automation of the data collection for Power station to create Large-scale Generation Certificates (LGCs) saves the industry approximately 490 hours of industry effort per month based on 30 minutes per month per power station (979 power stations).
Digital Twin - a powerful data sharing, collaboration and visualisation tool for Australia
Develop a digital model platform capturing Australia’s built and natural environments, to enable data better planning, design and management our cities. This includes climate and natural disaster management.
- provides a secure platform to facilitate role-based access to open, shared and closed data
- easy online access to data discovery visualisation and querying through a web browser
- reduces data duplication, increases collaboration capabilities
- provides a trusted authoritative source for the data sets.
Digital Twin is a digital model of the built and natural environments based on rich historical and real time data. Digital Twins are powerful tools that can enable data collaboration between planners, infrastructure owners, builders, property developers, policy makers, researchers and the community. It can be used to help better plan, design and manage our cities, including for climate and natural disaster management.
CSIRO’s Data61 partnered with federal and state governments and industry to develop a Spatial Digital Twin capability for Australia. In February 2020, NSW Minister for Customer Service launched the NSW Spatial Digital Twin. This is one the largest in the world (in terms of land coverage and data being delivered), supporting 8,000 square kilometres with 3D data at time of launch. It unlocks high-value transport, infrastructure, property, planning and environmental datasets, reducing data duplication and ensuring that the Digital Twin is the one authoritative source of this information.
NSW Spatial Services provides the Spatial Data Collaboration Portal. Together with Data61’s TerriaJS -based mapping software and Magda data discovery tool, it provides a secure platform to facilitate role-based access to open, shared and sensitive data. This platform allows data custodians (government, industry, academia, or the community) to share data while retaining control over their data at the same time. The software allows users to access the data visualisation through a web browser, without installing any software.
These Digital Twin tools are the latest government data platforms in the journey commenced by National Map and TerriaJS in 2014. Additional platforms developed along the way include:
- the Australian Renewable Energy Mapping Infrastructure (AREMI) with Australian Renewable Energy Agency
- the National Drought Map with the National Drought and North Queensland Flood Response and Recovery Agency
- Digital Earth Australia Map and Digital Earth Africa Map with Geoscience Australia.
CSIRO’s Data61 has also partnered with the Queensland Government on a QLD Spatial Digital Twin which is soon to be released.
Note: The National Map, underpinned by Data61’s TerriaJS software, now provides access to over 11,000 data sets from governments across Australia. National Map is managed by the Digital Transformation Agency and supported by Geoscience Australia and other agencies.
CSIRO (Data 61)
Utilise solar irradiance data to automatically estimate the amount of generation for solar power stations that are under 1MW in determining the Large-scale Generation Certificates (LGC) entitlement.
- reduce cost to both industry and government in administrating LGC claims
- increased accuracy in data collection
- increased capability to identify claim discrepancies quickly and efficiently.
Power station operators report energy generation monthly via the Renewable Energy Certificate (REC) Registry to create Large-scale Generation Certificates (LGCs) in their account. They do this by logging into REC Registry each month, manually enter energy generated (TLEG) for each power station and submit data to substantiate their claim. The Clean Energy Regulator (CER) assesses these claims against the data provided and either approves or fails the LGCs accordingly.
Industry feedback suggest each claim takes approximately 30 minutes per month, per power station to lodge with the CER. With 979 power stations in this category, this equates to approximately 490 hours of industry effort per month. In addition, it requires 2 FTE to identify discrepancies in the claims and conduct detailed assessments on their validity.
Using solar irradiance data, CER can automatically estimate the amount of generation for solar power stations that are under 1MW to determine the LGC entitlement without manual intervention from scheme participants or CER staff. Scheme participants who opt-in to the irradiance method will have their generation data automatically entered in the REC Registry. Participants will be able to review their generation and, if they identify discrepancies between the irradiance value and their metered data, contact the CER for a correction. This will provide a two-fold benefit – help us refine our calculations for better accuracy and provide confidence to scheme participants they will receive their full entitlement.
The CER has engaged the Bureau of Meteorology (BOM) and Solcast, another weather observation company, to provide data which will enable the calculation of LGC entitlement on behalf of a solar photovoltaic (PV) power station.
Clean Energy Regulator
Cloud analytics platform
The Australian Bureau of Statistics (ABS) DataLab, provides online access for government and academic researchers to undertake complex statistical analysis on ABS microdata.
- improved security and access to microdata
- increased capability for Australians to integrate and undertake complex analysis of ABS statics.
In 2018, under the Data Integration Partnership for Australia (DIPA), the ABS commenced a project to deliver a Cloud based analytics and storage platform for the ABS DataLab. The ABS DataLab provides online access for government and academic researchers to undertake complex statistical analysis on ABS microdata. Microdata is data in a unit record file that provides detailed information about people, households, businesses or other types of records. Microdata remains in the secure ABS environment. DataLab users view and analyse de-identified unit record information using software including R, Python, Stata and SAS. All analytical outputs for use outside the DataLab are checked by the ABS before release to ensure individuals and businesses cannot be identified.
The aim of the Cloud DataLab project is to improve DataLab performance, increase capacity to meet growing demand, enhance user experience and to further improve the already strong ABS DataLab data security protections. The Cloud DataLab can also support secure sharing of data across government agencies.
The ABS Cloud DataLab Beta environment has been established, with a trial that commenced in May 2020. A number of government and academic analysts are participating in the Beta trial, which will continue to December 2020. During this time, the ABS will collect feedback from users on their experiences and iteratively improve the platform. In addition, the ABS will collect metrics on usage and Cloud costs. DataLab has been developed in a user centred way, involving focus groups, surveys, and user testing of alpha versions of the environment.
In parallel to the Beta Trial, ABS have also commenced work on a CRM User Portal. This portal will further improve the user experience, replacing email and paper-based processes for requesting, approving and managing access to data.
Australian Bureau of Statistics