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dc.contributor.authorByrne, Thomas J.*
dc.contributor.authorCampean, I. Felician*
dc.contributor.authorNeagu, Daniel*
dc.date.accessioned2018-04-26T11:49:23Z
dc.date.available2018-04-26T11:49:23Z
dc.date.issued2018-05
dc.identifier.citationByrne 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.en_US
dc.identifier.urihttp://hdl.handle.net/10454/15655
dc.descriptionnoen_US
dc.description.abstractDemand 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.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.21278/IDC.2018.0490
dc.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.en
dc.subjectKnowledge managementen_US
dc.subjectBig data analysisen_US
dc.subjectDesign modelsen_US
dc.subjectAutomotive systemsen_US
dc.titleTowards a framework for engineering big data: An automotive systems perspectiveen_US
dc.status.refereedYesen_US
dc.typeConference paperen_US
dc.type.versionPublished versionen_US
refterms.dateFOA2018-07-28T03:50:52Z


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