The Centre for Information Resilience (CIRES) is an Australian Research Council (ARC) Industrial Transformation Training Centre.

Our Centre aims at building workforce capacity in Australian organisations to: create, protect and sustain agile data pipelines capable of detecting and responding to failures and risks across the information value chain in which the data is sourced, shared, transformed, analysed and consumed.

Building on strong foundations of responsible data science, we bring together end-users, technology providers, and cutting-edge research, to lift the socio-technical barriers to data driven transformation.

We support the development of resilient data pipelines capable of delivering game-changing productivity that position Australian organisations at the forefront of technology leadership and value creation from data assets.

  • Bias Mitigation in Human in the Loop Decision Systems
    This project focuses on integrating fairness into learning algorithms used in the context of policing services and tasks and aims to observe if this leads to improved outcomes and experiences.

  • Data as a Service Architecture
    In this project, the aim is to develop a novel system for making efficient and effective queries and recommendations based on multi-source data from the Queensland Police Service.

  • Community Attitude to Law Enforcement Data
    This project, in collaboration with the Queensland Police Service aims to develop qualitative and participatory research methods that can be used by data-driven organizations to understand and better communicate the impact of using human data to customers, users, and the public.

  • Defining and Measuring Analytics Value
    This project in collaboration with Aginic/Mantel Group, and commenced in February 2022 with the recruitment of PhD researcher Daisy Xu at The University of Queensland. It will develop a systematic methodology to define and measure the value of data and analytics for organisations. The methodology can provide Aginic and other firms investing in analytics with an evidence-based approach for ongoing value creation and measurement from data.