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Secure Remote Access Environment (SRAE)

Secure Remote Access Environment Srae

The Australian Institute of Health and Welfare’s (AIHW) Secure Remote Access Environment (SRAE) was implemented in 2019 leveraging an existing product developed by the University of NSW (UNSW), known as ERICA. The SRAE has been in operation now since July 2019 and is being used by a number of different internal and external research projects. 

The aim of this project is to enhance the SRAE to provide additional functionality to AIHW’s new Secure Remote Access Environment to support the requirements of increasingly large and complex data assets and to provide an efficient researcher experience in accessing these data.

 With the assistance of PHRN, AIHW will be able to enhance SRAE to support user requirements for complex and large datasets by implementing a capability that allows authorised users to access subsets of data from a primary data source that resides in the environment. This approach is referred to as a “views” approach to data access and contrasts with the practice of producing extracts of the data to be supplied into the research workspaces. The development of this capability will support and be supported by developments in security, data ingress, management, the NMLK and monitoring.

The requirement is driven by data custodian legislative and policy imperatives and a desire by AIHW to introduce greater flexibility in managing MELDA data in a researcher environment. Specifications have been developed from AIHW business units input in collaboration with advice from external agencies (primarily through the NIHSI Advisory Committee). The aim is to provide richer functionality for data custodians, researchers (Internal and external), data analysts and data linkage units.

The intent is to allow a single data source to be housed in the environment and provide a secure data extraction to only a subset of data that has been approved; enhanced data governance through monitoring usage and compliance; greater data custodian visibility and control over their data; and cost reduction and improved timeliness by not having to prepare individual data extracts on demand.

Project Status: Ongoing