TY  - JOUR
AU  - Basaglia, T.
AU  - Bellis, M.
AU  - Blomer, J.
AU  - Boyd, J.
AU  - Bozzi, C.
AU  - Britzger, D.
AU  - Campana, S.
AU  - Cartaro, C.
AU  - Chen, G.
AU  - Couturier, B.
AU  - David, G.
AU  - Diaconu, Cristinel
AU  - Dobrin, A.
AU  - Duellmann, D.
AU  - Ebert, M.
AU  - Elmer, P.
AU  - Fernandes, J.
AU  - Fields, L.
AU  - Fokianos, P.
AU  - Ganis, G.
AU  - Geiser, A.
AU  - Gheata, M.
AU  - Lopez, J. B. Gonzalez
AU  - Hara, T.
AU  - Heinrich, L.
AU  - Herner, K.
AU  - Hildreth, M.
AU  - Jayatilaka, B.
AU  - Kado, M.
AU  - Keeble, O.
AU  - Kohls, A.
AU  - Naim, K.
AU  - Lange, C.
AU  - Lassila-Perini, K.
AU  - Levonian, S.
AU  - Maggi, M.
AU  - Marshall, Z.
AU  - Vila, P. Mato
AU  - Mečionis, A.
AU  - Morris, A.
AU  - Piano, S.
AU  - Potekhin, M.
AU  - Schröder, M.
AU  - Schwickerath, U.
AU  - Sexton-Kennedy, E.
AU  - Šimko, T.
AU  - Smith, T.
AU  - South, D.
AU  - Verbytskyi, A.
AU  - Vidal, M.
AU  - Vivace, A.
AU  - Wang, L.
AU  - Watt, G.
AU  - Wenaus, T.
TI  - Data preservation in high energy physics
JO  - The European physical journal / C
VL  - 83
IS  - 9
SN  - 1434-6044
CY  - Heidelberg
PB  - Springer
M1  - PUBDB-2023-07863
M1  - arXiv:2302.03583
M1  - DPHEP-2023-01
SP  - 795
PY  - 2023
AB  - 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.
KW  - computer: network (INSPIRE)
KW  - hardware (INSPIRE)
KW  - Grid computing (INSPIRE)
KW  - data preservation (INSPIRE)
KW  - transverse (INSPIRE)
KW  - interface (INSPIRE)
KW  - neural network (INSPIRE)
KW  - statistical analysis (INSPIRE)
KW  - data analysis method (INSPIRE)
KW  - data compilation (INSPIRE)
KW  - data management (INSPIRE)
KW  - programming (INSPIRE)
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:001064474800002
DO  - DOI:10.1140/epjc/s10052-023-11885-1
UR  - https://bib-pubdb1.desy.de/record/600295
ER  -