Large Data Acquisition and Analytics at Synchrotron Radiation Facilities

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Authors: Aashish Panta, Giorgio Scorzelli, Amy Ashurst Gooch, Werner Sun, Katherine S. Shanks, Suchismita Sarker, Devin Bougie, Keara Soloway, Rolf Verberg, Tracy D. Berman, Glenn Tarcea, John Allison
+2 more Michela Taufer, Valerio Pascucci
Cited by: 0

Abstract

Synchrotron facilities like the Cornell High Energy Synchrotron Source (CHESS) generate massive data volumes from complex beamline experiments, but face challenges such as limited access time, the need for on-site experiment monitoring, and managing terabytes of data per user group. We present the design, deployment, and evaluation of a framework that addresses CHESS's data acquisition and management issues. Deployed on a secure CHESS server, our system provides real time, web-based tools for remote experiment monitoring and data quality assessment, improving operational efficiency. Implemented across three beamlines (ID3A, ID3B, ID4B), the framework managed 50-100 TB of data and over 10 million files in late 2024. Testing with 43 research groups and 86 dashboards showed reduced overhead, improved accessibility, and streamlined data workflows. Our paper highlights the development, deployment, and evaluation of our framework and its transformative impact on synchrotron data acquisition.

Fields of Study & Subjects

Scientific Computing and Data Management Research Data Management Practices Distributed and Parallel Computing Systems

Publication details

Journal / source
arXiv (Cornell University)
Publication date
5 February 2026
Document type
Preprint