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@ARTICLE{Basaglia:600295,
author = {Basaglia, T. and Bellis, M. and Blomer, J. and Boyd, J. and
Bozzi, C. and Britzger, D. and Campana, S. and Cartaro, C.
and Chen, G. and Couturier, B. and David, G. and Diaconu,
Cristinel and Dobrin, A. and Duellmann, D. and Ebert, M. and
Elmer, P. and Fernandes, J. and Fields, L. and Fokianos, P.
and Ganis, G. and Geiser, A. and Gheata, M. and Lopez, J. B.
Gonzalez and Hara, T. and Heinrich, L. and Herner, K. and
Hildreth, M. and Jayatilaka, B. and Kado, M. and Keeble, O.
and Kohls, A. and Naim, K. and Lange, C. and Lassila-Perini,
K. and Levonian, S. and Maggi, M. and Marshall, Z. and Vila,
P. Mato and Mečionis, A. and Morris, A. and Piano, S. and
Potekhin, M. and Schröder, M. and Schwickerath, U. and
Sexton-Kennedy, E. and Šimko, T. and Smith, T. and South,
D. and Verbytskyi, A. and Vidal, M. and Vivace, A. and Wang,
L. and Watt, G. and Wenaus, T.},
collaboration = {{DPHEP Collaboration}},
title = {{D}ata preservation in high energy physics},
journal = {The European physical journal / C},
volume = {83},
number = {9},
issn = {1434-6044},
address = {Heidelberg},
publisher = {Springer},
reportid = {PUBDB-2023-07863, arXiv:2302.03583. DPHEP-2023-01},
pages = {795},
year = {2023},
abstract = {Data preservation is a mandatory specification for any
present and future experimental facility and it is a
cost-effective way of doing fundamental research by
exploiting unique data sets in the light of the continuously
increasing theoretical understanding. This document
summarizes the status of data preservation in high energy
physics. The paradigms and the methodological advances are
discussed from a perspective of more than ten years of
experience with a structured effort at international level.
The status and the scientific return related to the
preservation of data accumulated at large collider
experiments are presented, together with an account of
ongoing efforts to ensure long-term analysis capabilities
for ongoing and future experiments. Transverse projects
aimed at generic solutions, most of which are specifically
inspired by open science and FAIR principles, are presented
as well. A prospective and an action plan are also
indicated.},
keywords = {computer: network (INSPIRE) / hardware (INSPIRE) / Grid
computing (INSPIRE) / data preservation (INSPIRE) /
transverse (INSPIRE) / interface (INSPIRE) / neural network
(INSPIRE) / statistical analysis (INSPIRE) / data analysis
method (INSPIRE) / data compilation (INSPIRE) / data
management (INSPIRE) / programming (INSPIRE)},
cin = {ZEUS / H1},
ddc = {530},
cid = {I:(DE-H253)ZEUS-20120806 / I:(DE-H253)H1-20120806},
pnm = {611 - Fundamental Particles and Forces (POF4-611)},
pid = {G:(DE-HGF)POF4-611},
experiment = {EXP:(DE-MLZ)NOSPEC-20140101},
typ = {PUB:(DE-HGF)16},
eprint = {2302.03583},
howpublished = {arXiv:2302.03583},
archivePrefix = {arXiv},
SLACcitation = {$\%\%CITATION$ = $arXiv:2302.03583;\%\%$},
UT = {WOS:001064474800002},
doi = {10.1140/epjc/s10052-023-11885-1},
url = {https://bib-pubdb1.desy.de/record/600295},
}