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001     187363
005     20230711154056.0
024 7 _ |2 Handle
|a 2128/8322
037 _ _ |a FZJ-2015-01034
041 _ _ |a English
100 1 _ |0 P:(DE-Juel1)132239
|a Riedel, Morris
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111 2 _ |a Big Data and Extreme Scale Computing 2015
|c Barcelona
|d 2015-01-28 - 2015-01-30
|g BDEC 2015
|w Spain
245 _ _ |a European Data Infrastructure - EUDAT: Data Services & Tools
260 _ _ |c 2015
336 7 _ |0 PUB:(DE-HGF)6
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336 7 _ |0 33
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336 7 _ |2 DataCite
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336 7 _ |2 ORCID
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520 _ _ |a With ever increasing scales towards extreme-scales in high performance computing large quantities of data are continuing to grow leading to a wide variety of challenges for computational sciences. Solutions are discussed in the talk of using analytics and visualizations in parallel - in-situ - to the extreme-scale simulation run in order to reduce, validate, or to even only understand the complex scientific datasets generated. Exchanging and sharing those data, replicating and archiving for later re-use, or permanently linking the data within publications are just a few challending areas for which the European Data Infrastructure EUDAT offers selected tools. The talk motivates this problem space towards extreme scales and outlines a potential set of tools and methods. one of the feasible sustainable approaches is known as a collaborative data infrastructure that encourages trust in users and, among other benefits, enables the removal of duplicate datasets.
536 _ _ |0 G:(DE-HGF)POF3-512
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536 _ _ |0 G:(EU-Grant)283304
|a EUDAT - EUropean DATa (283304)
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|f FP7-INFRASTRUCTURES-2011-2
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773 _ _ |y 2015
856 4 _ |u http://morrisriedel.de/sites/default/files/share/2015-01-28-EUDAT-Riedel-Small-v1.pdf
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914 1 _ |y 2015
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