Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/5685
Full metadata record
DC FieldValueLanguage
dc.contributor.authorCeravolo, Paolo
dc.contributor.authorAzzini, Antonia
dc.contributor.authorAngelini, Marco
dc.contributor.authorCatarci, Tiziana
dc.contributor.authorCudr-Mauroux, Philippe
dc.contributor.authorDamiani, Ernesto
dc.contributor.authorMazak, Alexandra
dc.contributor.authorVan Keulen, Maurice
dc.contributor.authorJarrar, Mustafa
dc.contributor.authorSantucci, Giuseppe
dc.contributor.authorSattler, Kai-Uwe
dc.contributor.authorScannapieco, Monica
dc.contributor.authorWimmer, Manuel
dc.contributor.authorWrembel, Robert
dc.contributor.authorZaraket, Fadi A.
dc.date.accessioned2018-10-24T06:01:48Z
dc.date.available2018-10-24T06:01:48Z
dc.date.issued2018-05
dc.identifier.citationPaolo 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: Big Data Semantics. Journal on Data Semantics. Volume 7, Issue 2, Pages(65-85), Springer, May 2018. ISSN 1861-2040, (doi.org/10.1007/s13740-018-0086-2).en_US
dc.identifier.issn1861-2040
dc.identifier.urihttp://www.jarrar.info/publications/BigDataSemantics.pdf
dc.identifier.urihttp://hdl.handle.net/20.500.11889/5685
dc.descriptionArticle published in : Journal on Data Semantics ; June 2018, vol. 7, no. 2, pp. 65–85
dc.description.abstractBig Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing.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 challengesen_US
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesVolume 7, Issue 2
dc.subjectBig Dataen_US
dc.subjectSemantics - Data processingen_US
dc.subjectElectronic data processingen_US
dc.subjectData structures (Computer science)en_US
dc.subjectDatabase managementen_US
dc.subject.lcshSemantic computing
dc.titleBig data semanticsen_US
dc.typeArticleen_US
newfileds.departmentEngineering and Technologyen_US
newfileds.item-access-typeopen_accessen_US
newfileds.thesis-prognoneen_US
newfileds.general-subjectComputers and Information Technology | الحاسوب وتكنولوجيا المعلوماتen_US
Appears in Collections:Fulltext Publications

Files in This Item:
File Description SizeFormat 
BigDataSemantics.pdf970.58 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.