We're working to enhance the delivery of services throughout the community, using machine learning and constraints-based optimisation.
Real world problems often require linking population-sized datasets. The aim of this project was to automate and improve linkage quality, fairness and speed to ensure optimal performance of linkages in a real-world setting.
Developing an API to enable the fast and free discovery of historical aerial photography from Geoscience Australia's archives.
The goal of the project was to investigate the effect of the type of logic on logical rule authoring and to understand how to manage complexity at scale in logical rule authoring. In addition, the project aims to identify the benefit in terms of effort and ease-of-use of using DDL instead of classical logic is investigated, as well as to identify additional logical features to ensure alignment between legal texts and their corresponding logical representation.
The Longitudinal Linked Employer-Employee Data System (L-LEEDS) Project explores approaches for building software components to support a privacy-preserving, federated data sharing model, as a foundation for a future whole-of-government distributed privacy-preserving, data analytics environment.
Federated Magda aims to form a comprehensive solution for the management of data within government agencies. Aligning with wider federal government initiatives around data use, Federated Magda enables more of the data held by government to be released and shared.
An artificial intelligence engine for traffic congestion management developed for Transport for NSW.
Data61's "Knowledge Extraction in Context" system is a proof-of-concept prototype that demonstrates the feasibility of converting content from conservation statutory documents into knowledge that can be searched, browsed, visualised and used to provide insights about threats, habitats and interactions concerning Australian threatened species. The resulting prototype helps to unlock the knowledge stored only in PDFs so that it can potentially feed into downstream conservation and environment-related data analytics.
YDYR enables the transformation of spatial data between different spatial geographies, allowing users to re-project data onto a different geographic region. It improves on existing methods by modelling the relationship between the data of interest and ancillary data available on a common set of regions. As well as improving the accuracy of the transformation, it delivers estimates of uncertainty that can be propagated through to downstream analysis and inform the user of the quality of the transformation
We’re working with Rio Tinto in Western Australia’s Pilbara region to maximise the throughput of their rail system by using simulations to balance train scheduling with maintenance and other system constraints.
We're re-imagining regulation as an open platform based on digital logic to help support a growing ecosystem of digital regulation tools and services.
Our social media monitoring tool Vizie is transforming the way government agencies listen to, understand and respond to customer feedback from social media.
Libraries face unique challenges when using social media channels to help deliver services. We have developed tools to support libraries in dealing with complex data archival and analysis as well as customer engagement.
There’s no shortage of smart undergraduate and post-graduates students wanting to work and build skills while studying.
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