Journal Article

FZJ-2017-08570

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Advancing data management and analysis in different scientific disciplines

Fischer, M. (Corresponding author) ; Gasthuber, M. ; Giesler, A.FZJ* ; Hardt, M. ; Meyer, J. ; Prabhune, A. ; Rigoll, F. ; Schwarz, K. ; Streit, A.

2017
IOP Publ. Bristol

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Please use a persistent id in citations: http://hdl.handle.net/2128/16292  doi:10.1088/1742-6596/898/8/082026

Abstract: Over the past several years, rapid growth of data has affected many fields of science. This has often resulted in the need for overhauling or exchanging the tools and approaches in the disciplines' data life cycles. However, this allows the application of new data analysis methods and facilitates improved data sharing.The project Large-Scale Data Management and Analysis (LSDMA) of the German Helmholtz Association has been addressing both specific and generic requirements in its data life cycle successfully since 2012. Its data scientists work together with researchers from the fields such as climatology, energy and neuroscience to improve the community-specific data life cycles, in several cases even all stages of the data life cycle, i.e. from data acquisition to data archival. LSDMA scientists also study methods and tools that are of importance to many communities, e.g. data repositories and authentication and authorization infrastructure.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 512 - Data-Intensive Science and Federated Computing (POF3-512) (POF3-512)
2. LSDMA - Large Scale Data Management and Analysis (HGF-IVF-LSDMA) (HGF-IVF-LSDMA)

Appears in the scientific report 2017

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Database coverage:
; ; ; ; DOAJ Seal ; Nationallizenz ; SCOPUS

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