ScaDS Dresden/Leipzig – A competence center for collaborative big data research
Autor(en):
Zusammenfassung
The efficient and intelligent handling of large, often distributed and heterogeneous data sets increasingly determines the scientific and economic competitiveness in most application areas. Mobile applications, social networks, multimedia collections, sensor networks, data intense scientific experiments, and complex simulations nowadays generate a huge data deluge. Nonetheless, processing and analyzing these data sets with innovative methods open up new opportunities for its exploitation and new insights. Nevertheless, the resulting resource requirements exceed usually the possibilities of state-of-the-art methods for the acquisition, integration, analysis and visualization of data and are summarized under the term big data. ScaDS Dresden/Leipzig, as one Germany-wide competence center for collaborative big data research, bundles efforts to realize data-intensive applications for a wide range of applications in science and industry. In this article, we present the basic concept of the competence center and give insights in some of its research topics.
- Vollständige Referenz
- BibTeX
Jäkel, R., Peukert, E., Nagel, W. E. & Rahm, E.,
(2018).
ScaDS Dresden/Leipzig – A competence center for collaborative big data research.
it - Information Technology: Vol. 60, No. 5-6.
Berlin:
De Gruyter.
(S. 327-333).
DOI: 10.1515/itit-2018-0026
@article{mci/Jäkel2018,
author = {Jäkel, René AND Peukert, Eric AND Nagel, Wolfgang E. AND Rahm, Erhard},
title = {ScaDS Dresden/Leipzig – A competence center for collaborative big data research},
journal = {it - Information Technology},
volume = {60},
number = {5-6},
year = {2018},
,
pages = { 327-333 } ,
doi = { 10.1515/itit-2018-0026 }
}
author = {Jäkel, René AND Peukert, Eric AND Nagel, Wolfgang E. AND Rahm, Erhard},
title = {ScaDS Dresden/Leipzig – A competence center for collaborative big data research},
journal = {it - Information Technology},
volume = {60},
number = {5-6},
year = {2018},
,
pages = { 327-333 } ,
doi = { 10.1515/itit-2018-0026 }
}
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Mehr Information
ISSN: 2196-7032
Datum: 2018
Sprache:
(en)
(en)
Typ: Text/Journal Article

