Engaging Outsiders in Sport: Transforming Sport Event Legacy Planning . The project aims to investigate intersectional inequities in sport participation for girls, women and non-binary people in Queensland by working with them to envision legacies for the 2032 Olympic and Paralympic Games. Using a co-creation approach this project expects to identify how and what benefits can be achieved through legacy planning that engages with end-users who have historically been marginalised in sport. In doin ....Engaging Outsiders in Sport: Transforming Sport Event Legacy Planning . The project aims to investigate intersectional inequities in sport participation for girls, women and non-binary people in Queensland by working with them to envision legacies for the 2032 Olympic and Paralympic Games. Using a co-creation approach this project expects to identify how and what benefits can be achieved through legacy planning that engages with end-users who have historically been marginalised in sport. In doing so, the expected outcomes of the project include the development of evidence-based resources to improve engagement in sport and to build capacity and sustain meaningful change for communities and organisations.Read moreRead less
Ontologically-based Evaluation, Comparison and Engineering of Integrated Process Modelling Techniques. Integrated process modelling techniques such as UML and ARIS form the conceptual platform for many management and IT projects. Though most IS development tools contain these techniques, anecdotal evidence indicates many shortcomings. This project uses a well-established theory developed in philosophy and applied in information systems domains for the evaluation of these techniques. The expec ....Ontologically-based Evaluation, Comparison and Engineering of Integrated Process Modelling Techniques. Integrated process modelling techniques such as UML and ARIS form the conceptual platform for many management and IT projects. Though most IS development tools contain these techniques, anecdotal evidence indicates many shortcomings. This project uses a well-established theory developed in philosophy and applied in information systems domains for the evaluation of these techniques. The expected outcomes are evaluations of ARIS and UML. Thus, this project contributes to the development of two of the most popular modelling techniques. Based on the theory used and the results of an international empirical study, suggestions for the further development of these techniques will be derived.Read moreRead less
Governance of Agile Software Development Projects. The aim of the project is to generate theoretical knowledge on how to govern agile teams effectively. Effective governance of software development projects is essential for companies to protect their information technology investments. Nowadays, companies have migrated to agile software development where requirements and solutions evolve iteratively and change frequently; yet formal approaches to governance (eg steering committee and detailed pl ....Governance of Agile Software Development Projects. The aim of the project is to generate theoretical knowledge on how to govern agile teams effectively. Effective governance of software development projects is essential for companies to protect their information technology investments. Nowadays, companies have migrated to agile software development where requirements and solutions evolve iteratively and change frequently; yet formal approaches to governance (eg steering committee and detailed plans) are ineffective and impede flexibility, agility and creativity. This project aims to identify informal governance approaches for agile projects based on team embeddedness and network theory. With this knowledge, management could ensure projects deliver value at an acceptable cost, quality and timescale.Read moreRead less
Expressiveness Comparison and Interchange Facilitation between Business Process Execution Languages. Developments in the area of business process management are currently hindered by the plethora of diverse business process execution languages. This project will develop techniques for dealing with interoperability issues induced by this language heterogeneity. The project combines theoretical research, grounded in concurrency theory and workflow patterns, with pragmatic research focusing on lang ....Expressiveness Comparison and Interchange Facilitation between Business Process Execution Languages. Developments in the area of business process management are currently hindered by the plethora of diverse business process execution languages. This project will develop techniques for dealing with interoperability issues induced by this language heterogeneity. The project combines theoretical research, grounded in concurrency theory and workflow patterns, with pragmatic research focusing on languages supported by commercial tools. The outcome will be a framework for comparing the expressiveness of process execution languages and defining mappings between them. This will place Australia at the forefront of developments in business process management systems: a crucial technology in today's global, dynamic, and heterogeneous environments.
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Risk-aware business process management. Risk-aware business process management will revolutionise the identification and treatment of risks in business processes by integrating the latest technologies for risk management and process management. It will provide organisations with a range of new tools and techniques for designing, deploying and monitoring risk-aware business processes.
Improved Businesss Decision-Making via Liquid Process Model Collections. This project aims to develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes. Deploying theoretical, conceptual and empirical research, this project aims to capitalise on the value hidden in large process data, as recorded in ....Improved Businesss Decision-Making via Liquid Process Model Collections. This project aims to develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes. Deploying theoretical, conceptual and empirical research, this project aims to capitalise on the value hidden in large process data, as recorded in event logs. The approach is intended to be implemented in an open-source technology to facilitate advanced investigations and predictions that can ultimately lead to better strategic decision-making. This technology also has the potential to become a research-enabling tool for the large research community in business process management.Read moreRead less
Cost-aware business process management. The project aims to inform business process management (BPM) with the latest insights from the field of management accounting in order to make BPM systems cost-aware. By incorporating the cost dimension, organisations can obtain an accurate and immediate overview of the true cost of their processes and make cost-informed decisions.
Diagnosis and prediction of business process deviances. This project aims to develop an innovative approach based on process execution semantics, to analyse event data logged by IT systems in order to diagnose and predict business process deviance. Anticipated outcomes include novel business intelligence algorithms producing deviance diagnostics, predictions and recommendations and exposing results via interactive visual analytics. The outcomes are expected to aid process workers in steering bus ....Diagnosis and prediction of business process deviances. This project aims to develop an innovative approach based on process execution semantics, to analyse event data logged by IT systems in order to diagnose and predict business process deviance. Anticipated outcomes include novel business intelligence algorithms producing deviance diagnostics, predictions and recommendations and exposing results via interactive visual analytics. The outcomes are expected to aid process workers in steering business operations towards consistent and compliant outcomes and higher performance, and assist analysts and auditors to explain deviant operations. This should significantly benefit industries such as healthcare, insurance, retail and the government where compliance and integrity management are imperative.Read moreRead less
Mining Distributed, High-Speed, Time-Variant Data Streams. With the high-speed and large volume of data generation, the data mining research community is facing an unprecedented challenge to provide instant data mining outcomes for prompt usage. Getting access to derived information from multiple, dynamically changing data is vital for many business, science and security services. Extended networks of sensors and other devices assist many environments with data collection that should be correlat ....Mining Distributed, High-Speed, Time-Variant Data Streams. With the high-speed and large volume of data generation, the data mining research community is facing an unprecedented challenge to provide instant data mining outcomes for prompt usage. Getting access to derived information from multiple, dynamically changing data is vital for many business, science and security services. Extended networks of sensors and other devices assist many environments with data collection that should be correlated and processed towards discovery of dependencies, regularities and patterns. Data mining tools, especially of this new generation, are capable of dealing with data streams, and they offer great benefits for users from many industry sectors; defence, health management, security, commerce and science.Read moreRead less
Challenging big data for scalable, robust and real-time recommendations. With the advent of big data era, recommender systems are facing unprecedented challenges with respect to the four dimensions of big data: big volume, low veracity, high velocity and high variety. This project aims to develop a new generation of cost-effective techniques for scalable, robust and real-time recommendations utilising big data. This project aims to address these challenges to achieve scalable, robust and real-ti ....Challenging big data for scalable, robust and real-time recommendations. With the advent of big data era, recommender systems are facing unprecedented challenges with respect to the four dimensions of big data: big volume, low veracity, high velocity and high variety. This project aims to develop a new generation of cost-effective techniques for scalable, robust and real-time recommendations utilising big data. This project aims to address these challenges to achieve scalable, robust and real-time recommendations. This project will devise a series of cost-effective machine learning methods and schemes to deliver an end-to-end recommender framework. This project has the potential to significantly reduce the energy consumption of large-scale recommender systems as well as facilitating an increase in the use of recommendation applications for big data.Read moreRead less