https://doi.org/10.1051/epjconf/202024505032
Enhancements in Functionality of the Interactive Visual Explorer for ATLAS Computing Metadata
1
Lomonosov Moscow State University, Leninskie Gory, 1, building 4, Moscow, 119234, Russian Federation
2
Moscow Center of Fundamental and Applied Mathematics, GSP-1, Leninskie Gory, Moscow, 119991, Russian Federation
3
Ivannikov Institute for System Programming, Alexander Solzhenitsyn st., 25, 109004, Moscow, Russian Federation
4
National Research Nuclear University “MEPhI”, Kashirskoe shosse, 31, 115409, Moscow, Russian Federation
5
Brookhaven National Laboratory, Upton, New York, United States of America
6
National Research Center “Kurchatov Institute”, Akademika Kurchatova pl., 1, 123182, Moscow, Russian Federation
Published online: 16 November 2020
The development of the Interactive Visual Explorer (InVEx), a visual analytics tool for the computing metadata of the ATLAS experiment at LHC, includes research of various approaches for data handling both on server and client sides. InVEx is implemented as a web-based application which aims at the enhancing of analytical and visualization capabilities of the existing monitoring tools and facilitates the process of data analysis with the interactivity and human supervision. The current work is focused on the architecture enhancements of the InVEx application. First, we will describe the user-manageable data preparation stage for cluster analysis. Then, the Level-of-Detail approach for the interactive visual analysis will be presented. It starts with the low detailing, when all data records are grouped (by clustering algorithms or by categories) and aggregated. We provide users with means to look deeply into this data, incrementally increasing the level of detail. Finally, we demonstrate the development of data storage backend for InVEx, which is adapted for the Level-of-Detail method to keep all stages of data derivation sequence.
© The Authors, published by EDP Sciences, 2020
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.
