Big Data Semantics

Paolo Ceravolo (Corresponding Author), Antonia Azzini, Marco Angelini, Tiziana Catarci, Philippe Cudré-Mauroux, Ernesto Damiani, Alexandra Mazak, Maurice van Keulen, Mustafa Jarrar, Giuseppe Santucci, Kai-Uwe Sattler, Monica Scannapieco, Manuel Wimmer, Robert Wrembel, Fadi Zaraket

    Research output: Contribution to journalArticleAcademicpeer-review

    18 Citations (Scopus)
    1 Downloads (Pure)

    Abstract

    Big Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing. It is, however, largely recognized that Big Data impose novel challenges in data and infrastructure management. Indeed, multiple components and procedures must be coordinated to ensure a high level of data quality and accessibility for the application layers, e.g., data analytics and reporting. In this paper, the third of its kind co-authored by members of IFIP WG 2.6 on Data Semantics, we propose a review of the literature addressing these topics and discuss relevant challenges for future research. Based on our literature review, we argue that methods, principles, and perspectives developed by the Data Semantics community can significantly contribute to address Big Data challenges.
    Original languageEnglish
    Pages (from-to)65-85
    Number of pages21
    JournalJournal on Data Semantics
    Volume7
    Issue number2
    Early online date23 May 2018
    DOIs
    Publication statusPublished - 1 Jun 2018

    Keywords

    • UT-Hybrid-D

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  • Cite this

    Ceravolo, P., Azzini, A., Angelini, M., Catarci, T., Cudré-Mauroux, P., Damiani, E., ... Zaraket, F. (2018). Big Data Semantics. Journal on Data Semantics, 7(2), 65-85. https://doi.org/10.1007/s13740-018-0086-2