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    Towards a framework for engineering big data: An automotive systems perspective

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    Conference paper (1.197Mb)
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    Publication date
    2018-05
    Author
    Byrne, Thomas J.
    Campean, I. Felician
    Neagu, Daniel
    Keyword
    Knowledge management
    Big data analysis
    Design models
    Automotive systems
    Rights
    © 2018 Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Croatia. Published by the above and the Design Society, Glasgow. Reproduced in accordance with the publisher's self-archiving policy.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Demand for more sophisticated models to meet big data expectations require significant data repository obligations, operating concurrently in higher-level applications. Current models provide only disjointed modelling paradigms. The proposed framework addresses the need for higher-level abstraction, using low-level logic in the form of axioms, from which higher-level functionality is logically derived. The framework facilitates definition and usage of subjective structures across the cyber-physical system domain, and is intended to converge the range of heterogeneous data-driven objects.
    URI
    http://hdl.handle.net/10454/15655
    Version
    Published version
    Citation
    Byrne TJ, Campean F and Neagu D (2018) Towards a framework for engineering big data: An automotive systems perspective. 15th International Design Conference (Proceedings) - Design 2018. 21-24 May 2018. Dubrovnik, Croatia.
    Link to publisher’s version
    https://doi.org/10.21278/IDC.2018.0490
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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