An Application of Visual Analytics Methods to Cluster and Categorize Data Processing Jobs in High Energy and Nuclear Physics Experiments

Galkin, Timofei; Grigoryeva, Maria; Klimentov, A.; Korchuganova, Tatiana; Milman, I.; Pilyugin, V.V.; Titov, Mikhail

doi:10.26583/sv.10.5.03

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…The possible structure of this relationship, as well as its interpretation, is largely determined by the structure of a specific GCE and the content of the tasks of analyzing its results that the researcher faces. However, we can consider general relationships that can be used to describe and analyze a wide class of computational experiments [7][8][9][10]. The following two situations can serve as examples of such relationships:…”

Section: Formalization Of Gce Structure and Its State Considering Rel...mentioning

confidence: 99%

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Generalized Computational Experiment State Analysis Using Three-Dimensional Visual Maps

Zakharova¹,

Korostelyov²,

Podvesovskii³

et al. 2022

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The paper continues a series of publications of the authors' research materials in the field of developing an approach to dynamic planning and control of a generalized computational experiment based on visualization methods and visual analytics. A generalized computational experiment involves multiple solution of a numerical simulation problem for different sets of values of model defining parameters, which makes it possible to obtain a solution immediately for a certain class of mathematical modeling problems specified in a multidimensional parameter space. The paper considers an extension of the existing authors' approach to analysis of a generalized computational experiment state using visual maps, based on visualization metaphors that can display not only individual images but also their relationships. A method is proposed for constructing visual maps of a generalized computational experiment focused on visualizing relationships between single computational experiments in three-dimensional space. The method is based on the mechanism of formalization of the relationships between single computational experiments, as well as the concept of a graph model visualization metaphor that defines a visual map prototype. A description is given of a software system for constructing and analyzing three-dimensional visual maps of a generalized computational experiment. The paper also considers examples of its application in estimating the accuracy of numerical models of the OpenFOAM software platform for a three-dimensional problem of inviscid flow around a cone.

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Section: Formalization Of Gce Structure and Its State Considering Rel...mentioning

confidence: 99%

“…In the considered GCE for assessing the accuracy of solvers, examples of adjacent combinations of values of the defining parameters are combinations (3, 10, 0) and (3, 10, 5) or combinations (7,15,5) and (7,15,10).…”

Section: Formalization Of Gce Structure and Its State Considering Rel...mentioning

confidence: 99%

Generalized Computational Experiment State Analysis Using Three-Dimensional Visual Maps

Zakharova¹,

Korostelyov²,

Podvesovskii³

et al. 2022

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“…The Interactive Visual Explorer (InVEx) is developed as a generic interactive visual analytics tool for the analysis and exploration of big volumes of multidimensional data [1]. InVEx is based on the combined usage of intellectual data analysis methods and advanced interactive visualization techniques.…”

Section: Introductionmentioning

confidence: 99%

Nested Intellectual Data Grouping and Clusterization for the Interactive Visual Explorer

et al. 2020

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The Interactive Visual Explorer (InVEx) application is designed as a visual analytics tool for Big Data analysis. Visual analytics is an integral approach to data analysis, combining methods of intellectual data analysis with advanced interactive visualization. One of the main objectives of InVExis to process large data samples by decreasing their level of detail (LoD).The proposed approach includes clustering as well as flexible grouping by different parameters, providing the exploration of data from the lowest to the highest level of details. The results of grouping and clusterization arevisualized using interactive 3D scene and parallel coordinates, allowing the user to gain insight into data, to explore hidden correlations and trends of parameters.

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“…InVEx (Interactive Visual Explorer) [1] is a toolkit for visual analysis of multidimensional data. This visualization system was developed to cover the needs of representation of the computing metadata of the ATLAS experiment [2] at Large Hadron Collider (LHC) and can address similar tasks in other domains.…”

Section: Introductionmentioning

confidence: 99%

Enhancements in Functionality of the Interactive Visual Explorer for ATLAS Computing Metadata

et al. 2020

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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.

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An Application of Visual Analytics Methods to Cluster and Categorize Data Processing Jobs in High Energy and Nuclear Physics Experiments

Cited by 6 publications

References 6 publications

Generalized Computational Experiment State Analysis Using Three-Dimensional Visual Maps

Generalized Computational Experiment State Analysis Using Three-Dimensional Visual Maps

Nested Intellectual Data Grouping and Clusterization for the Interactive Visual Explorer

Enhancements in Functionality of the Interactive Visual Explorer for ATLAS Computing Metadata

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