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Australian State/Territory : QLD
Research Topic : Indigenous methodologies
Socio-Economic Objective : Application packages
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  • Funded Activity

    Discovery Projects - Grant ID: DP0211789

    Funder
    Australian Research Council
    Funding Amount
    $205,818.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0558879

    Funder
    Australian Research Council
    Funding Amount
    $463,000.00
    Summary
    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.
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