Recommendations for Best Practices for Data Preservation and Open Science in HEP
These recommendations are the result of reflections by scientists and experts who are, or have been, involved in the preservation of high-energy physics data. The work has been done under the umbrella of the Data Lifecycle panel of the International Committee of Future Accelerators (ICFA), drawing on the expertise of a wide range of stakeholders. A key indicator of success in the data preservation efforts is the long-term usability of the data. Experience shows that achieving this requires providing a rich set of information in various forms, which can only be effectively collected and preserved during the period of active data use. The recommendations are intended to be actionable by the indicated actors and specific to the particle physics domain. They cover a wide range of actions, many of which are interdependent. These dependencies are indicated within the recommendations and can be used as a road map to guide implementation efforts. These recommendations are best accessed and viewed through the web application, see https://icfa-data-best-practices.app.cern.ch/
Authors
- Giacomo Tenaglia
- C. Lange (ORCID: https://orcid.org/0000-0002-3632-3157)
- Anne Gentil‐Beccot (ORCID: https://orcid.org/0000-0001-9199-655X)
- Michael Sparks (ORCID: https://orcid.org/0000-0002-6796-677X)
- U. Schwickerath (ORCID: https://orcid.org/0000-0001-8320-9835)
- Tibor Šimko
- E. Sexton-Kennedy (ORCID: https://orcid.org/0000-0001-9171-1980)
- C. Doglioni (ORCID: https://orcid.org/0000-0002-1509-0390)
- E. Lançon (ORCID: https://orcid.org/0000-0002-0225-187X)
- I. Osborne (ORCID: https://orcid.org/0000-0002-6955-1033)
- H. B. Newman (ORCID: https://orcid.org/0000-0003-0964-1480)
- Mihoko M. Nojiri (ORCID: https://orcid.org/0000-0002-7312-7542)
- G. A. Valdiviesso (ORCID: https://orcid.org/0000-0002-0381-3619)
- Des Fitzgerald (ORCID: https://orcid.org/0000-0003-1899-8481)
- S. Campana (ORCID: https://orcid.org/0000-0002-8437-7336)
- Gang Chen (ORCID: https://orcid.org/0000-0002-0758-1907)
- Hao Hu (ORCID: https://orcid.org/0000-0002-8859-0986)
- Alexander Winkler (ORCID: https://orcid.org/0000-0001-9536-7873)
- F. Z. Qi (ORCID: https://orcid.org/0000-0002-0448-2620)
- T. McCauley (ORCID: https://orcid.org/0000-0001-6589-8286)
- З. Маршалл (ORCID: https://orcid.org/0000-0003-0786-2570)
- Irakli Chakaberia
- Michael D Hildreth
- Graeme Andrew Stewart
- C. Diaconu (ORCID: https://orcid.org/0000-0002-6193-5091)
- V. Garonne
- S. Roiser (ORCID: https://orcid.org/0000-0002-5600-8592)
- J. M. Hogan
- K. Lassila-Perini (ORCID: https://orcid.org/0000-0002-5502-1795)
- Christoph Wissing
- Seema Sharma
- Salomé Rohr
- Olivia Mandica-Hart
- Nicola Tarocco
- Fleur Heiniger
Institutions
- Deutsches Elektronen-Synchrotron DESY (DE)
- Centre de physique des particules de Marseille (FR)
Publication Details
- Journal
- ArXiv.org
- Published
- 2025-01-01
- DOI
- https://doi.org/10.3204/pubdb-2025-03961
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00