Data and Analysis Preservation, Recasting, and Reinterpretation
High Energy Physics - Phenomenology
2022-03-21 v1 High Energy Physics - Experiment
Abstract
We make the case for the systematic, reliable preservation of event-wise data, derived data products, and executable analysis code. This preservation enables the analyses' long-term future reuse, in order to maximise the scientific impact of publicly funded particle-physics experiments. We cover the needs of both the experimental and theoretical particle physics communities, and outline the goals and benefits that are uniquely enabled by analysis recasting and reinterpretation. We also discuss technical challenges and infrastructure needs, as well as sociological challenges and changes, and give summary recommendations to the particle-physics community.
Keywords
Cite
@article{arxiv.2203.10057,
title = {Data and Analysis Preservation, Recasting, and Reinterpretation},
author = {Stephen Bailey and Christian Bierlich and Andy Buckley and Jon Butterworth and Kyle Cranmer and Matthew Feickert and Lukas Heinrich and Axel Huebl and Sabine Kraml and Anders Kvellestad and Clemens Lange and Andre Lessa and Kati Lassila-Perini and Christine Nattrass and Mark S. Neubauer and Sezen Sekmen and Giordon Stark and Graeme Watt},
journal= {arXiv preprint arXiv:2203.10057},
year = {2022}
}
Comments
25 pages, 4 sets of recommendations. Contribution to Snowmass 2021