The VIDEA lab is a living lab that integrates research and visual innovation through multidisciplinary research. It aims to pioneer innovative solutions at the intersection of geospatial and visualisation science, health, and decision analytics in real-world environments.

In aligning with the mission of the Health Research Institute, the VIDEA lab aims to bring together experts from a diverse range of disciplines to advance public health and health services research and have real world impact. We do this through supporting and showcasing research conducted across HRI, engaging and collaborating with new and existing research partners, and developing tools for decision support in health and social policy planning.

Lab capabilities include:

Data management

Overseeing data flow, curation, management, and distribution activities aimed at supporting HRI research. Adhere to data governance requirements including security, confidentiality, and ethical use of health data.

High performance computing

Supporting storage and analysis of high volumes of data for research in collaboration with University eResearch and Information Technology teams.

Contextual indicators

The development, benchmarking, and evaluation of social and environmental determinants of health. Data integration and linkage of spatial and aspatial data for health research.

Geospatial modelling

Adopting Geographic Information Systems (GIS) to conduct a range of tasks involving spatial data and spatial analysis including investigating relationships between the built, natural, and social environment and their impact on health and wellbeing.

Geospatial visualisation

Enhance data exploration and communication through the development of spatial tools, mapping and visualisation.

Visualisation tools

The design and maintenance of interactive dashboards, infographics, and publication ready graphics.

Decision analytics

Decision analytics utilises technologies and analytical methods to develop adaptable decision support tools that forecast the impact of alternate decision options before they are implemented in the real world.