A continuous integration and web framework in support of the ATLAS publication process

• Published in: The European physical journal. C, Particles and fields Vol. 16; no. 5
• Main Authors: Espinosa, J. P. Araque, Levcovitz, G. Baldi, Bianchi, R. M., Brock, I., Carli, T., Castro, Nuno Filipe, Ciocio, A., Colautti, M., Menezes, A. C. Da Silva, Fonseca, G. De Oliveira da, Alves, L. Domingues Macedo, Hoecker, A., Ramos, B. Lange, Pinhão, G. Lemos Lúcidi, Maidantchik, C., Malek, F., McPherson, R., Picco, G., Santos, M. Teixeira Dos
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01-05-2021
• Subjects: and distribution of data; archiving; Ciências Físicas; Ciências Naturais; Computing (architecture; farms; frameworks and databases; GRID for recording; Science & Technology; Software architectures (event data models; storage
• DOI: 10.1088/1748-0221/16/05/T05006
• EISSN: 1434-6052

The ATLAS collaboration defines methods, establishes procedures, and organises advisory groups to manage the publication processes of scientific papers, conference papers, and public notes. All stages are managed through web systems, computing programs, and tools that are designed and developed by the collaboration. A framework called FENCE is integrated into the CERN GitLab software repository, to automatically configure workspaces where each analysis can be documented by the analysis team and managed by the relevant coordinators. Continuous integration is used to guide the writers in applying consistent and correct formatting when preparing papers to be submitted to scientific journals. Additional software assures the correctness of other aspects of each paper, such as the lists of collaboration authors, funding agencies, and foundations. The framework and the workflow therein provide automatic and easy support to the researchers and facilitates each phase of the publication process, allowing authors to focus on the article contents. The framework and its integration with the most up to date and efficient tools has consequently provided a more professional and efficient automatized work environment to the whole collaboration.
ATLAS Collaboration for the support provided to achieve the results described in this paper. We are grateful to ATLAS collaborators who provided invaluable comments and input to the paper and the framework it presents. Special acknowledgements go to Marzio Nessi for helping initiate the Glance project in ATLAS and for supporting its development, and to Kathy– 20 –Pommes for supervising the Glance team at CERN