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@ARTICLE{Jung:187993,
author = {Jung, C. and Gasthuber, M. and Giesler, A. and Hardt, M.
and Meyer, J. and Rigoll, F. and Schwarz, K. and Stotzka, R.
and Streit, A.},
title = {{O}ptimization of data life cycles},
journal = {Journal of physics / Conference Series},
volume = {513},
number = {3},
issn = {1742-6596},
address = {Bristol},
publisher = {IOP Publ.},
reportid = {FZJ-2015-01482},
pages = {032047},
year = {2014},
abstract = {Data play a central role in most fields of science. In
recent years, the amount of data from experiment,
observation, and simulation has increased rapidly and data
complexity has grown. Also, communities and shared storage
have become geographically more distributed. Therefore,
methods and techniques applied to scientific data need to be
revised and partially be replaced, while keeping the
community-specific needs in focus.The German Helmholtz
Association project "Large Scale Data Management and
Analysis" (LSDMA) aims to maximize the efficiency of data
life cycles in different research areas, ranging from high
energy physics to systems biology. In its five Data Life
Cycle Labs (DLCLs), data experts closely collaborate with
the communities in joint research and development to
optimize the respective data life cycle. In addition, the
Data Services Integration Team (DSIT) provides data analysis
tools and services which are common to several DLCLs. This
paper describes the various activities within LSDMA and
focuses on the work performed in the DLCLs.},
cin = {JSC},
ddc = {530},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {412 - Grid Technologies and Infrastructures (POF2-412)},
pid = {G:(DE-HGF)POF2-412},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000342287200128},
doi = {10.1088/1742-6596/513/3/032047},
url = {https://juser.fz-juelich.de/record/187993},
}