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Optimization of data life cycles


Christopher Jung, M. Gasthuber, A. Giesler, M. Hardt, J. Meyer, Fabian Rigoll, K. Schwarz, R. Stotzka, A. Streit



Published: 2014

Buchtitel: Int. Conf. on Computing in High Energy and Nuclear Physics, 2013
Verlag: Journal of Physics: Conference Series
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.


Projekt

LSDMA



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet
Energieinformatik