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    Cognitive big data: survey and review on big data research and its implications. What is really “new” in big data?

    Access Status
    Fulltext not available
    Authors
    Lugmayr, Artur
    Stockleben, B.
    Scheib, C.
    Mailaparampil, M.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Lugmayr, A. and Stockleben and Scheib and Mailaparampil 2017. Cognitive big data: survey and review on big data research and its implications. What is really “new” in big data?. Journal of Knowledge Management. 21 (1): pp. 197-212.
    Source Title
    Journal of Knowledge Management
    DOI
    10.1108/JKM-07-2016-0307
    ISSN
    1367-3270
    School
    Department of Film and Television
    URI
    http://hdl.handle.net/20.500.11937/51502
    Collection
    • Curtin Research Publications
    Abstract

    Purpose – The purpose of this paper is to introduce and define Cognitive Big Data as a concept. Furthermore, it investigates what is really “new” in Big Data, as it seems to be a hyped-up concept that has emerged during recent years. The purpose is also to broaden the discussion around Big Data far beyond the common 4V (velocity, volume, veracity and variety) model. Design/methodology/approach – The authors established an expert think tank to discuss the notion of Big Data, identify new characteristics and re-think what really is new in the idea of Big Data, by analyzing over 60 literature resources. They identified typical baseline scenarios (traffic, business processes, retail, health and social media) as a starting point from which they explored the notion of Big Data from different perspectives. Findings – They concluded that the idea of Big Data is simply not new and recognized the need to re-think a new approach toward Big Data. The authors also introduced a five-Trait Framework for “Cognitive Big Data”, socio-technical system, data space, data richness, knowledge management (KM)/decision-making and visualization/sensory presentation. Research limitations/implications – The viewpoint is centered on cognitive processes as KM process. Practical implications – Data need to be made available in an understandable form for the right application context and in the right portion size that it can be turned into knowledge and eventually wisdom. The authors need to know about data that can be ignored, data that they are not aware of (dark data) and data that can be fully utilized for analysis (light data). In the foreground is the extension of human mental capabilities and data understandability. Social implications – Cognitive Big Data implies a socio-technological knowledge system. Originality/value – Introduction of cognitive Big Data as concept and framework.

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