Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/5685
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. 65–85en_US
dc.description.abstractBig Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing.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
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.languageiso639-1other-
Appears in Collections:Fulltext Publications
Files in This Item:
File Description SizeFormat
BigDataSemantics.pdf970.58 kBAdobe PDFView/Open
Show simple item record

Page view(s)

161
Last Week
0
Last month
2
checked on Feb 6, 2024

Download(s)

344
checked on Feb 6, 2024

Google ScholarTM

Check


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