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Title	Advancements in data management services for distributed e-infrastructures: the eXtreme-DataCloud project
Author(s)	Cesini, Daniele (INFN, Bologna) ; Donvito, Giacinto (INFN, Bari) ; Costantini, Alessandro (INFN, Bologna) ; Aguilar Gomez, Fernando (Cantabria Inst. of Phys.) ; Duma, Doina Cristina (INFN, Bologna) ; Fuhrmann, Patrick (DESY) ; Dutka, Lukasz (AGH-UST, Cracow) ; Viljolen, Matthew (Unlisted, NL) ; Battaglia, Serena (Unlisted, FR) ; Poireau, Vincent (Annecy, LAPP) ; Dell'Agnello, Luca (INFN, Bologna) ; Keeble, Oliver (CERN) ; Lemrani, Rachid (CC, Villeurbanne) ; Ohmann, Christian (Unlisted, DE) ; Marco de Lucas, Jesus (Cantabria Inst. of Phys.)
Publication	2019
Number of pages	8
In:	EPJ Web Conf. 214 (2019) 04044
In:	23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.04044
DOI	10.1051/epjconf/201921404044
Subject category	Computing and Computers
Abstract	The development of data management services capable to cope with very large data resources is a key challenge to allow the future e-infrastructures to address the needs of the next generation extreme scale scientific experiments. To face this challenge, in November 2017 the H2020 eXtreme DataCloud - XDC project has been launched. Lasting for 27 months and combining the expertise of eight large European research organisations, the project aims at developing scalable technologies for federating storage resources and managing data in highly distributed computing environments. The targeted platforms are the current and next generation e-Infrastructures deployed in Europe, such as the European Open Science Cloud (EOSC), the European Grid Infrastructure (EGI), and the Worldwide LHC Computing Grid (WLCG). The project is use-case driven with a multidisciplinary approach, addressing requirements from research communities belonging to a wide range of scientific domains: High Energy Physics, Astronomy, Photon and Life Science, Medical research. XDC is aimed at implementing data management scalable services, combining already established data management and orchestration tools, to address the following high level topics: policy driven data management based on Quality-of-Service, Data Life-cycle management, smart placement of data with caching mechanisms to reduce access latency, meta-data with no predefined schema handling, execution of pre-processing applications during ingestion, data management and protection of sensitive data in distributed e-infrastructures, intelligent data placement based on access patterns. This contribution introduces the project, presents the foreseen overall architecture and the developments that are being carried on to implement the requested functionalities.
Copyright/License	publication: © 2019-2024 The Authors (License: CC-BY-4.0)

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