LSDMA stands for “Large-Scale Data Management and Analysis” and was a portfolio theme funded by the German Helmholtz Association from 2012–2016. Under leadership of the Karlsruhe Institute of Technology (KIT), four Helmholtz centres (KIT, FZ Jülich, DESY, GSI), six universities (University of Hamburg, University of Ulm, Heidelberg University, HTW Berlin, TU Dresden and GU Frankfurt) and the German Climate Computing Centre
(DKRZ) joined to enable data-intensive science by optimising data life cycles in selected scientific communities.
In our Data Life Cycle Labs (DLCLs), data experts performed joint R&D together with scientific communities to optimise data management and analysis tools, processes and methods. Complementing the activities in the DLCLs, the Data Services Integration Team (DSIT) focused on the development of generic tools and solutions, which are applied by several scientific communities. munities. Examples are authentication, authorisation, identity management, archiving or metadata. Overall 78 scientists – among them 21 PhD researchers – were working in LSDMA and have achieved very interesting results ranging from communityspecific solutions, e.g. in energy or climate/environmental research, to generic tools and methods, e.g. for meta-data handling or federated AAI. This book gives an overview on these fascinating R&D.
In addition, LSDMA organised several annual events: the international symposium on “The Challenge of Big Data in Science”, community forums, technical forums and PhD meetings – all these events promoted the enabling of
data-intensive science, brought together LSDMA consortium partners with the scientific communities and fostered the spreading and uptake of LSDMA solutions.
New projects originate from the new connections among people in LSDMA and their scientific results, e.g. the DFG-funded MASi project focusses on metadata management for applied sciences and the EC-funded project INDIGO-DataCloud aims at developing a data/compute platform for dataintensive scientific communities provisioned over hybrid einfrastructures. Much of the work of LSDMA is meanwhile carried forward in the third round of the Helmholtz programme-oriented funding (PoF-3). Internationally several LSDMA scientists are actively participating in the Research Data Alliance (RDA) through participating and/or leading working and interest groups as well as severing as elected members in RDA boards such as the Technical Advisory Board (TAB).
I want to express our gratitude to the German Helmholtz Association and the German Federal Ministry of Education and Research for funding the LSDMA portfolio theme.
Have a nice time reading the book.