| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01109 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/epjconf/202533701109 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701109
Advancements in the in-file metadata system for the ATLAS experiment
1 Argonne National Laboratory, Lemont, IL, United States**
2 University of Massachusetts, Amherst MA, United States
3 Brookhaven National Laboratory, Upton, NY, United States
* e-mail: mszymanski@anl.gov, speaker
** Argonne National Laboratory’s work was supported by the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357
Published online: 7 October 2025
The High-Luminosity upgrade of the Large Hadron Collider (HL-LHC) will increase luminosity and the number of events by an order of magnitude, demanding more concurrent data processing. Event processing is trivially parallel, but metadata handling is more complex and breaks that parallelism. However, correct and reliable in-file metadata is crucial for all workflows of the experiment, enabling tasks such as job configuration, decoding trigger information, and keeping track of event selection. Therefore, ATLAS is enhancing its current in-file metadata system to support metadata creation and propagation in more robust ways. This work presents developments in the evolution of the metadata system. We investigate storage technologies tailored for infile metadata payload, exploring advancements in the ROOT framework, which is used for storing data collected by the ATLAS experiment. We also discuss the challenging process of summarising the content of metadata objects when combining information from several sources.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

