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000187363 041__ $$aEnglish
000187363 1001_ $$0P:(DE-Juel1)132239$$aRiedel, Morris$$b0$$eCorresponding Author$$ufzj
000187363 1112_ $$aBig Data and Extreme Scale Computing 2015$$cBarcelona$$d2015-01-28 - 2015-01-30$$gBDEC 2015$$wSpain
000187363 245__ $$aEuropean Data Infrastructure - EUDAT: Data Services & Tools
000187363 260__ $$c2015
000187363 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1422512889_8066$$xInvited
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000187363 520__ $$aWith ever increasing scales towards extreme-scales in high performance computing large quantities of data are continuing to grow leading to a wide variety of challenges for computational sciences. Solutions are discussed in the talk of using analytics and visualizations in parallel - in-situ - to the extreme-scale simulation run in order to reduce, validate, or to even only understand the complex scientific datasets generated. Exchanging and sharing those data, replicating and archiving for later re-use, or permanently linking the data within publications are just a few challending areas for which the European Data Infrastructure EUDAT offers selected tools. The talk motivates this problem space towards extreme scales and outlines a potential set of tools and methods. one of the feasible sustainable approaches is known as a collaborative data infrastructure that encourages trust in users and, among other benefits, enables the removal of duplicate datasets.
000187363 536__ $$0G:(DE-HGF)POF3-512$$a512 - Data-Intensive Science and Federated Computing (POF3-512)$$cPOF3-512$$fPOF III$$x0
000187363 536__ $$0G:(EU-Grant)283304$$aEUDAT - EUropean DATa (283304)$$c283304$$fFP7-INFRASTRUCTURES-2011-2$$x1
000187363 773__ $$y2015
000187363 8564_ $$uhttp://morrisriedel.de/sites/default/files/share/2015-01-28-EUDAT-Riedel-Small-v1.pdf
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000187363 9130_ $$0G:(DE-HGF)POF2-412$$1G:(DE-HGF)POF2-410$$2G:(DE-HGF)POF2-400$$aDE-HGF$$bSchlüsseltechnologien$$lSupercomputing$$vGrid Technologies and Infrastructures$$x0
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