People Research Data Commons

The challenge

The data that health researchers need is distributed across government, research and health service sectors. Researchers and innovators face challenges knowing whether useful data exists, who holds it, and how to access it.

For this focus area, we aim to make the health data, software and models researchers need to improve healthcare more findable, accessible, reusable and interoperable (FAIR). 

Our activities

We’re developing a Discovery Framework that describes a consistent set of informatics practices – including for metadata, identifiers, vocabularies and metadata syndication – to enable a national view of health data. Health Data Australia will serve as a catalogue of Australian health data assets and related research outputs by acting as a central metadata aggregation point. ARDC partners from academia, government, National Collaborative Research Infrastructure Strategy (NCRIS) facilities, health services and industry can adopt and adapt the Framework to suit their specific needs and objectives.

For our next steps, we’re working with:

• the academic research sector to support the efficient collection, management and sharing of health studies data to improve healthcare via our Health Studies Australian National Data Asset (HeSANDA) activity
• key government agencies to facilitate discovery and streamline access to health data for researchers via our Government Health Data Assets activity
• NCRIS facilities for consistency in their data collection, curation and access standards to make their data findable and accessible as national data assets.

The challenge

Health information of patients and research subjects must be kept secure and not disclosed during the process of research or service improvement. Data custodians therefore require researchers to use secure environments for data analysis. Researchers don’t always have access to secure environments for the data they want to share or access, or when secure environments do exist, they can inadvertently create data silos that impede national-scale multidisciplinary collaborations.

Our activities

Through our Trusted Research Environments activity, we’re establishing a National Trusted Research Environment (TRE) Framework in response to calls for a national conversation around a TRE’s core features, a reference architecture, and principles to underpin consistency and interoperability. The ARDC is harnessing expertise from a number of previous TRE projects such as SeRP, ERICA and CADRE. The Framework will provide a common blueprint and offer best-practice guidelines beneficial to many universities and research institutions seeking accreditation under the Office of the National Data Commissioner (ONDC) Data Scheme.

Aligned with the Framework, we’re establishing networks of secure access services that will:

• provide TRE coverage for secondary use of data in strategic academic research areas, such as clinical trials and cohorts
• be consistent, appropriate, interoperable and comprehensive across government, NCRIS, and the broader research sector for the data researchers need.

The challenge

To solve the grand challenges facing society, researchers seek insights by combining data from government, research, and health service providers. Because these data are collected in a wide range of scientific, clinical or operational contexts, they use different standards and structures, which makes it difficult for researchers to bring these together.

Across these data sources, we will promote and support standardisation of data structures, common medical concept definitions, and common identifiers for concepts, people, resources, etc. 

Our activities

We’re developing a national semantic interoperability framework, which will outline opportunities for data contributors in research or healthcare to easily adopt common data models, ontologies and identifiers and join up data to increase its value.

The next steps are to:

• work with survey and data collection tool developers to support national and international or community-appropriate standards for data collection during health studies
• establish streamlined and enduring approaches to integrating research studies with public-sector administrative datasets, including national-level approaches to common data models and infrastructure for discovering and querying standardised data
• develop common ontologies and data models to enable federated datasets to operate as national data assets across universities and NCRIS facilities.

The challenge

Applying advanced analytics techniques like machine learning to national sensitive data collections across multiple secure data repositories raises data challenges that require innovative solutions.

Our activities

Through our Advanced Analytics in Healthcare activity, we’re working with the Australian Data Science Network (ADSN) to publish a National Infrastructure Framework for Health Analytics. It will document and prioritise AI infrastructure needs in:

• underpinning hardware infrastructure
• national reference data assets
• underpinning federated and foundational infrastructure
• shared tools and platforms
• coordinated socio-technical systems (STS) assets on a national level – including training, policy and guidelines, culture, and community support.. 

A demonstrator will also be developed in parallel with the Framework to test and illustrate some of these components.

We’ll then run a coordinated set of pilot activities to implement various aspects of the Framework with:

• universities, medical research institutes and national research collaborations
• government data custodians
• NCRIS facilities.