Synthetic Data Community of Practice (SynD) Membership Nomination Form |
Background
SynD was established to create a collaborative platform for professionals, experts, and stakeholders in the field of digital health and data science. Founding organisational members of SynD are Digital Health CRC Limited (“DHCRC”), La Trobe University, The University of Queensland, The University of Sydney, Western Australia Department of Health and Northern Territory Government (NT Health).
Mission Statement
“To unlock the value of health information through the use of synthetic data to advance research, education, innovation and service delivery within the health and care sector.”
Objectives
Develop a synthetic data coordinated program of work and national collaborative approach to facilitate evidence and knowledge exchange for:
SynD was established to create a collaborative platform for professionals, experts, and stakeholders in the field of digital health and data science. Founding organisational members of SynD are Digital Health CRC Limited (“DHCRC”), La Trobe University, The University of Queensland, The University of Sydney, Western Australia Department of Health and Northern Territory Government (NT Health).
Mission Statement
“To unlock the value of health information through the use of synthetic data to advance research, education, innovation and service delivery within the health and care sector.”
Objectives
Develop a synthetic data coordinated program of work and national collaborative approach to facilitate evidence and knowledge exchange for:
Advocacy, education and training
Provide a platform for the promotion of synthetic data use and synthetic data capability development and knowledge through joint research publications, conference and symposium presentations, lectures, workshops, datathons, webinars, training sessions and education short course / micro-credential content development.
Governance processes and standards
Lead the development of national governance processes, frameworks and standards for synthetic data, including data ethics and accountability, privacy protection and data quality assessment.
Technical solutions
Identify and map synthetic data applications and products / assets being used and document and measure the outcomes and impacts from these synthetic data technical solutions to support further synthetic data technical innovation and quality improvement.
Knowledge sharing
Facilitate the exchange of best practices, lessons learned, and emerging trends in the use of synthetic data within the health and care sectors for mutual benefit, to maximise synthetic data opportunities and benefits and provide guidance and support on synthetic data challenges.
Use cases
Collaborate on joint synthetic data use cases to solve health related challenges and unlock new synthetic data opportunities for mutual benefit.