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2019 | OriginalPaper | Buchkapitel

Visualization of Data: Methods, Software, and Applications

verfasst von : Gintautas Dzemyda, Olga Kurasova, Viktor Medvedev, Giedrė Dzemydaitė

Erschienen in: Advances in Mathematical Methods and High Performance Computing

Verlag: Springer International Publishing

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Abstract

Visualization is a part of data science, and essential to enable sophisticated analysis of data. The visualization ensures the human participation in most decisions when analyzing data. In this paper, we review methods and software for visualization of multidimensional data. The emphasis is put on the web-based DAMIS solution for data analysis, allowing researchers to carry out the primary data analysis and to investigate the projection of multidimensional data on a plane, the similarities between the data items, the influence of individual features, and their relationships by visual analysis techniques, using the high-performance computing resources. DAMIS is applied to the visual efficiency analysis of regional economic development to evaluate how regional resources are reflected in the economic results. The projection methods (principal component analysis, multidimensional scaling) and artificial neural networks (self-organizing map, SAMANN) are the core strategies for the analysis.

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Vorheriges Kapitel The Resiliency of Multilevel Methods on Next-Generation Computing Platforms: Probabilistic Model and Its Analysis

Nächstes Kapitel HPC Technologies from Scientific Computing to Big Data Applications

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Titel: Visualization of Data: Methods, Software, and Applications
verfasst von: Gintautas Dzemyda
Olga Kurasova
Viktor Medvedev
Giedrė Dzemydaitė
Verlag: Springer International Publishing
Buch: Advances in Mathematical Methods and High Performance Computing
Print ISBN: 978-3-030-02486-4

Electronic ISBN: 978-3-030-02487-1

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-02487-1_18

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