Prof. Nicola J Armstrong2, Dr. Gnana Bharathy3, Ms. Katie Buchhorn4, Mr. Tim Macuga4, Prof. Divya Mehta4, Prof. Kerrie Mengersen4, Dr. Anastasios Papaioannou1, A/Prof. Dimitri Perrin4, Dr. Emi Tanaka5
1Intersect Australia, Australia, 2Curtin University, Australia, 3Australian Research Data Commons, Australia, 4Queensland University of Technology, Australia, 5Australian National University, Australia
Biography:
Gnana works as AI/ML Research Data Specialist at the Australian Research Data Commons (ARDC) and is a practitioner, researcher and mentor, in AI and advanced analytics space. Gnana has been a Data Science and Design Consultant in the industry for over 15 years, has served a range of clients, and has conceptualized, developed and deployed several products, in health, energy, manufacturing, supply chain, environment, political and government sectors. Gnana is also engaged in application (AI applications in health, energy and social conflicts) and practice-based research, including in the AI risk, socio-technical systems and lifecycle. ORCID: https://orcid.org/0000-0001-8384-9509
Abstract:
Introduction: The Australian Research Data Commons (ARDC) has initiated the People Research Data Commons (RDC), a digital research infrastructure program aimed at enhancing digital health research and translation. ARDC collaborated with the Australian Data Science Network (ADSN) to evaluate the current state of digital health infrastructure in the health sector, focusing on computing resources, data and analytics methods, data accessibility, as well as the socio-technical elements. The primary goal is to identify the most critical national research infrastructure (NRI) components needed to support advanced health data analytics of health data and develop an Advanced Analytics Infrastructure Implementation PlanSpecification.
Methods: A mixed-methods approach was used, including surveys, focus groups, and environmental reviews. A questionnaire was distributed to academics, government officials, and industry representatives to gather comprehensive insights. Additionally, focus groups facilitated in-depth discussions, and an environmental review provided contextual understanding. Data from these methods were systematically analysed to develop the framework.
Results: These combined findings are being synthesised into a framework to serve as a specification for future ARDC co-investment projects. The framework aims to: a) Serve as a template for prioritising selecting ARDC partnership initiatives; b) Establish rapport with the research community, promoting the program's philosophy; c) Include NRI components, essential for supporting health research and translation; d) Integrate ARDC and other national infrastructure assets where applicable.
Conclusion: Our methodological framework and findings underscore the importance of strategic NRI to support advanced health data analytics, ensuring that the ARDC's initiatives align with the needs and priorities of the research community.