BORA 1.0

• Main Author: Tan Jerome, Nicholas
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2023
• Subjects: Orca
• Online Access: https://doi.org/10.5281/zenodo.10598381

BORA is an open source visualization framework supporting large-scale experiments by generating personalized data displays and enabling the human-in-the-loop concept within the experiment. Despite the complex experiment setup, BORA allows scientists to build their desired data displays with no programming knowledge. There are two facets to the framework, with the first facet being a read-only data displays where it helps scientists to monitor the health of the experiment subsystems. The second facet enables scientists to control the systems and data acquisition parameters. It enables feedback for multiple data processing pipelines that interact with the large volume of data in real-time. Bora is built around RESTful APIs and offers support for various standard protocols through plugin extensions for databases (e.g., Redis) and for control protocols (e.g., OPC). Furthermore, we implemented experiment-specific protocols used in our projects, such as ORCA. One unique feature of BORA is that it supports video streaming analysis of experimental data, allowing visual representation of the subsystem, e.g., surface temperature monitoring, detector heatmap. Github Repository: https://github.com/kit-ipe/bora This release is used across all KATRIN's displays, as well as the BESS experiment. (https://github.com/kit-ipe/bora/releases/tag/v1.0)