What is the Data and Decision Science Initiative?

The Data and Decision Science Initiative developed from a 2019 review of our capacity in “Big Data” and health informatics. The initiative is part of the 2020-2025 UOW strategic plan where data and decision science is recognised as an important component of the transformative models and technologies for our research, innovation and impact (section 2.5). Specifically, a UOW Data and Decision Science Initiative (DDSI) is listed as a component of delivering the UOW strategy. The National Institute for Applied Statistics Research Australia (NIASRA) plays a key leadership role in coordinating and delivering the initiative.

DDSI key areas

Research: Virtual network of Data and Decision Science researchers

  • Focal point for coordinating the development of Data Science at UOW
  • Composed of researchers actively using or interested in Data Science methods
  • Themed meetings emphasising translation
  • Initial focus on
    • existing collaborations in the areas of Health and Wellbeing and Social Analytics. Strategically collaborations through the DDSI give a competitive advantage in translation in health & well being
    • Researchers already engaged in Data Science (R and Python users)

External/Industry engagement: Capitalising on existing links

  • Data and decision science network will provide enhanced opportunities for external engagement

Education: Training in data science and reproducibility of research

  • Internal and external training and education in data science
  • Upskilling research students and staff (particularly Early Career Researchers) in data and decision science methods
  • Workshops (Graduate Research School, Statistical Consulting Centre)

T shaped graduates: Reviewing service subjects to refocus on data science

  • Review of service subjects in statistics and quantitative methods offered through the school of maths and applied statistics to give data science focus
  • Graduates literate in data science and reproducible research

Research & Education

The DDSI facilitates networking of researchers throughout UOW who use data and decision science or research data and decision science methodology. There is substantial overlap in current methodological requirements of data science, handling big data, and increased transparency in reproducible reporting of analysis between disciplines. The value add through the development of this network is the consolidation of resources and knowledge sharing, allowing the ability to improve research performance and industry engagement by the addition of novel and cutting edge data science methodology to grant applications, and upskilling of PhD students, post-doctoral and other research staff in data science methodology. Relevant methodologies include integration of data from multiple sources, analysis of linked data, reproducibility of research, machine learning, causal analysis of large-scale observational data, Bayesian design and decision making, ethics and privacy.

Watch some of our Data and Decision Science Network Presentations

Interactive Data Visualisation - Bradley Wakefield

The net benefit correspondence theorem - Senior Professor Simon Eckermann

Machine Learning Taster - Professor Alberto Nettel-Aguirre

Which stats package should I use? - Professor Marijka Batterham, Brad Wakefield, Professor Alberto Nettel-Aguirre

Transparency and reproducibility for quantitative research: Like the Layers of an Onion - Professor Ben Marwick


The figure outlines newly created teaching and education developments involving data science. These include developments in undergraduate and postgraduate degrees, liaising with the Graduate Research School to develop postgraduate training in Data Science, developed and planned internal and external short courses which can be developed into modules for micro-credentials.Teaching and education developments involving data science on the data and decision science initiative

For further information contact: Professor Marijka Batterham, Coordinator of the DDSI