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data analysis tools and services which are common to several DLCLs. This paper describes the | data analysis tools and services which are common to several DLCLs. This paper describes the | ||
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Version vom 26. Mai 2014, 11:35 Uhr
Optimization of data life cycles
Optimization of data life cycles
Published: 2013
Oktober
Buchtitel: Int. Conf. on Computing in High Energy and Nuclear Physics, 2013
Verlag: Proceedings of CHEP 2013
Organisation: Int. Conf. on Computing in High Energy and Nuclear Physics, 2013
Referierte Veröffentlichung
BibTeX
Kurzfassung
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 effciency 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.