Much of our research addresses Data61’s core strategy of better understanding data in the real world. In natural language processing we apply AI and other apply analytic techniques to extract meaning from human discourse. Our tools aggregate information from widely dispersed sources such as social media to draw novel insights, identifying trends and key events in a rapid and cost-effective manner. For example, we have developed techniques to assess social licence to operate by measuring stance as expressed in social media and other text-based sources.

We also work on improved methods of information extraction from the scientific literature. The volume of published science is increasing rapidly, so new tools and techniques are required to help scientists keep up with current knowledge, and identify new research opportunities.

Please see our Language and Social Computing Team webpage for more details.

Our economic research is focussed on better understanding the value(s) of data. Digital technology has dramatically reduced the costs of collecting and disseminating data; it has also brought greater awareness of its value. In economic terms data is a non-rival good, as one person’s use of it does not impede its use by others. However, this does not necessarily mean that individuals will be willing to collect and share data. As data has value it is theoretically possible for the beneficiaries to reward those who provide and share it. In practice this does not occur sufficiently due to the transaction costs this would entail and an absence of supporting institutions.

There is a need for interdisciplinary research into the socio-technical mechanisms required for efficient and equitable data sharing. This would consider potential technical approaches, such as privacy-preserving technologies, alongside institutional innovations such as data cooperatives or markets, which could realise the values of data. A key objective would be to avoid data monopolies, ensuring that both the costs and the benefits of data sharing are equitably distributed.

A practical example of this is our work with colleagues from across CSIRO to design and build the LOOC-C carbon farming tool, which draws data from a range of sources and makes it available, and relevant, to farmers and others interested in land sector carbon projects.

The impacts of digital technology are increasingly disrupting global labour markets. To take advantage of the productivity gains offered by these new technologies, human workers will need to reskill and upskill, to either focus their effort on existing tasks which are not readily automatable or to deliver new services that are enabled by the technology.

Through a collaboration with Adzuna Australia (aggregators of online job ads) we provide insight into technology developments and skills trends captured by mining the online job ads to understand what skills and attributes are sought after in the Australian labour market. We share the insights from these job ads via the Data61 Australian Skills Dashboard where they are used by government departments, educational institutions, researchers and policy developers who seek to understand where workers and skills are becoming more (or less) sought after in the Australian labour market.

We are also interested in how technology is changing the nature of work. We recently partnered with NBN co to carry out a comprehensive study of when and where Australians have been working, and socialising, from home since the start of the pandemic. And we are heavily involved in CSIRO’s Collaborative Intelligence Future Science Platform, looking at how best to combine human and artificial intelligence across a range of domains.