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February 5, 2026

Keep-up Production in JUNO’s Offline Data Processing

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Authors

WYWeiqing YinTLTao LinYZYizhou Zhang

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Overview

Demonstrates a data processing pipeline in neutrino physics, addressing data complexity and volume challenges.

Key Points

  • The objective is to develop a scalable pipeline for managing JUNO's offline data processing workflow.
  • Designed the Keep Up Production (KUP) pipeline architecture.
  • Implemented job management and data visualization components.
  • Utilized modern web technologies for enhanced functionality.
  • Incorporated automation and modularity to streamline the process.
  • Enabled real-time monitoring of the data processing system.
  • Successfully managed massive data processing requirements.
  • Improved efficiency through automation and job management.
  • Enhanced user experience with effective data visualization tools.
  • Addressed the challenges posed by data complexity and volume.

Cite This Study

Yin et al. (2025) studied this question.

synapsesocial.com/papers/6984349af1d9ada3c1fb2e06https://doi.org/10.1051/epjconf/202533701176/pdf
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Keep-up Production in JUNO’s Offline Data Processing2025
  2. 2Data Challenges in JUNO distributed computing infrastructure towards JUNO data-taking2025
  3. 3Data Challenges in JUNO distributed computing infrastructure towards JUNO data-taking2025
  4. 4Offline data processing in the First JUNO Data Challenge2024
  5. 5Monitoring System for JUNO Distributed Computing Infrastructure and Services2026