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000186725 037__ $$aFZJ-2015-00795
000186725 041__ $$aEnglish
000186725 1001_ $$0P:(DE-Juel1)132239$$aRiedel, Morris$$b0$$eCorresponding Author$$ufzj
000186725 1112_ $$aVlaams Supercomputing Centrum (VSC) User Day$$cBrussels$$d2014-01-16 - 2014-01-16$$wBelgium
000186725 245__ $$aEUDAT – Towards A Pan-European Collaborative Data Infrastructure
000186725 260__ $$c2014
000186725 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1422274831_24683$$xInvited
000186725 3367_ $$033$$2EndNote$$aConference Paper
000186725 3367_ $$2DataCite$$aOther
000186725 3367_ $$2ORCID$$aLECTURE_SPEECH
000186725 3367_ $$2DRIVER$$aconferenceObject
000186725 3367_ $$2BibTeX$$aINPROCEEDINGS
000186725 502__ $$cUniversity of Iceland
000186725 520__ $$aThe constantly growing amounts of global, diverse, complex, but extremely valuable scientific data is an opportunity, but also a major challenge for research. In recent years, several pan-European e-Infrastructures and a wide variety of research infrastructures have been established supporting multiple research communities. But the accelerated proliferation of data arising from powerful new scientific instruments, scientific simulations and digitization of library resources, for example, have created a more urgent demand for increasing efforts and investments in order to tackle the specific challenges of data management and to ensure a coherent approach to research data access and preservation. A vision of a ‘collaborative data infrastructure’ for science was outlined by the European high level expert group on scientific data listing 12 high level requirements and 24 challenges to overcome. In this talk, we take stock of activities of the pan-European EUDAT collaborative data infrastructure that aims to address these challenges and exploit new opportunities to satisfy many of the high level requirements with concrete data services. Data Analytics techniques in context will be highlighted (e.g. machine learning algorithms, statistical data mining approaches, etc.) in order to advance in science and engineering in ways not possible before.
000186725 536__ $$0G:(DE-HGF)POF2-412$$a412 - Grid Technologies and Infrastructures (POF2-412)$$cPOF2-412$$fPOF II$$x0
000186725 536__ $$0G:(EU-Grant)283304$$aEUDAT - EUropean DATa (283304)$$c283304$$fFP7-INFRASTRUCTURES-2011-2$$x1
000186725 773__ $$y2014
000186725 8564_ $$uhttp://morrisriedel.de/sites/default/files/share/2013-01-16-EUDAT-RIEDEL-v1-Small.pdf
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000186725 9141_ $$y2014
000186725 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132239$$aForschungszentrum Jülich GmbH$$b0$$kFZJ
000186725 9132_ $$0G:(DE-HGF)POF3-512$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vData-Intensive Science and Federated Computing$$x0
000186725 9131_ $$0G:(DE-HGF)POF2-412$$1G:(DE-HGF)POF2-410$$2G:(DE-HGF)POF2-400$$3G:(DE-HGF)POF2$$4G:(DE-HGF)POF$$aDE-HGF$$bSchlüsseltechnologien$$lSupercomputing$$vGrid Technologies and Infrastructures$$x0
000186725 920__ $$lyes
000186725 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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