Big Data Semantics

Paolo Ceravolo, 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 journalArticlepeer-review

56 Scopus citations


Big Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing.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 languageBritish English
Pages (from-to)65-85
Number of pages21
JournalJournal on Data Semantics
Issue number2
StatePublished - 1 Jun 2018


Dive into the research topics of 'Big Data Semantics'. Together they form a unique fingerprint.

Cite this