Today, data are collected and recorded at an increasing rate. In Science, data are a valuable good which can be reproduced at a high cost only or not at all. Data exploration represents the 4th pillar of modern science besides experiment, theory and simulation.
“Large-Scale Data Management and Analysis” (LSDMA) extends the data services for research of the Helmholtz Association of research centres in Germany with community specific Data Life Cycle Laboratories (DLCL). The DLCLs work in close cooperation with scientists and they process, manage and analyse data during its whole life cycle. The joint research and development activities in the DLCLs lead to community-specific tools and mechanisms. The DLCLs are complemented with a Data Services Integration Team (DSIT). It provides generic technologies and infrastructures for multi-community use, based on research and development in the areas of data management, data access and security, storage technologies and data preservation.
- A Best Practice Analysis of HDF5 and NetCDF-4 Using Lustre (Christopher Bartz, Konstantinos Chasapis, Michael Kuhn, Petra Nerge, Thomas Ludwig), In High Performance Computing, Lecture Notes in Computer Science (9137), pp. 274–281, (Editors: Julian Martin Kunkel, Thomas Ludwig), Springer International Publishing (Switzerland), ISC 2015, Frankfurt, Germany, ISBN: 978-3-319-20118-4, ISSN: 0302-9743, 2015-06
- Compression By Default - Reducing Total Cost of Ownership of Storage Systems (Michael Kuhn, Konstantinos Chasapis, Manuel Dolz, Thomas Ludwig), In Supercomputing, Lecture Notes in Computer Science (8488), (Editors: Julian Martin Kunkel, Thomas Ludwig, Hans Werner Meuer), Springer International Publishing (Berlin, Heidelberg), ISC 2014, Leipzig, Germany, ISBN: 978-3-319-07517-4, ISSN: 0302-9743, 2014-06
- Evaluating Power-Performace Benefits of Data Compression in HPC Storage Servers (Konstantinos Chasapis, Manuel Dolz, Michael Kuhn, Thomas Ludwig), In IARIA Conference, pp. 29–34, (Editors: Steffen Fries, Petre Dini), IARIA XPS Press, ENERGY 2014, Chamonix, France, ISBN: 978-1-61208-332-2, ISSN: 2308-412X, 2014-04-20 – Awards: Best Paper
- Evaluating Lustre's Metadata Server on a Multi-socket Platform (Konstantinos Chasapis, Manuel Dolz, Michael Kuhn, Thomas Ludwig), In Proceedings of the 9th Parallel Data Storage Workshop, PDSW (2014), pp. 13–18, IEEE Press (Piscataway, NJ, USA), SC14, New Orleans, Louisiana, ISBN: 978-1-4799-7025-4, 2014