Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11889/5685
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ceravolo, Paolo | - |
dc.contributor.author | Azzini, Antonia | - |
dc.contributor.author | Angelini, Marco | - |
dc.contributor.author | Catarci, Tiziana | - |
dc.contributor.author | Cudr-Mauroux, Philippe | - |
dc.contributor.author | Damiani, Ernesto | - |
dc.contributor.author | Mazak, Alexandra | - |
dc.contributor.author | Van Keulen, Maurice | - |
dc.contributor.author | Jarrar, Mustafa | - |
dc.contributor.author | Santucci, Giuseppe | - |
dc.contributor.author | Sattler, Kai-Uwe | - |
dc.contributor.author | Scannapieco, Monica | - |
dc.contributor.author | Wimmer, Manuel | - |
dc.contributor.author | Wrembel, Robert | - |
dc.contributor.author | Zaraket, Fadi A. | - |
dc.date.accessioned | 2018-10-24T06:01:48Z | |
dc.date.available | 2018-10-24T06:01:48Z | |
dc.date.issued | 2018-05 | - |
dc.identifier.citation | 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: 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.issn | 1861-2040 | - |
dc.identifier.uri | http://www.jarrar.info/publications/BigDataSemantics.pdf | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11889/5685 | - |
dc.description | Article published in : Journal on Data Semantics ; June 2018, vol. 7, no. 2, pp. 65–85 | en_US |
dc.description.abstract | Big Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing.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 | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartofseries | Volume 7, Issue 2; | - |
dc.subject | Big data | en_US |
dc.subject | Semantics - Data processing | en_US |
dc.subject | Electronic data processing | en_US |
dc.subject | Data structures (Computer science) | en_US |
dc.subject | Database management | en_US |
dc.subject.lcsh | Semantic computing | |
dc.title | Big data semantics | en_US |
dc.type | Article | en_US |
newfileds.department | Engineering and Technology | en_US |
newfileds.item-access-type | open_access | en_US |
newfileds.thesis-prog | none | en_US |
newfileds.general-subject | Computers and Information Technology | الحاسوب وتكنولوجيا المعلومات | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
item.languageiso639-1 | other | - |
Appears in Collections: | Fulltext Publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
BigDataSemantics.pdf | 970.58 kB | Adobe PDF | View/Open |
Page view(s)
161
Last Week
0
0
Last month
2
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.