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Evaluating Rucio outside ATLAS: Common experiences from Belle II, CMS, DUNE, SKA, and LIGO
2019
Zenodo
For many scientific projects, data management is an increasingly complicated challenge. The number of data-intensive instruments generating unprecedented volumes of data is growing and their accompanying workflows are becoming more complex. Their storage and computing resources are heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organizations. These locations do not necessarily coincide with the places where data is produced
doi:10.5281/zenodo.3599074
fatcat:kbhs652wbrgp5adzfmub62gxlu