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Visual Data Models in Scientific Search for Interpretation of Multiparametric Signals

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Creativity in Intelligent Technologies and Data Science (CIT&DS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1909))

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Abstract

Modern visualization methods are used to convey information about an object or process and as a tool for search and decision-making process. Data and signals, in analog and digital form, are only valuable if they are analyzed for a specific goal. In this work we etablish the classification of visualization tasks from the point of analyzing heterogeneous multidimensional data, including the case when at the initial stage it is required to formulate a research hypothesis. A classification of visualization metaphors is presented, which is necessary for a conscious choice of tools for visualization and data analysis. This is important for understanding and managing the interpretability of information, the formation of the correct meaning and operational understanding. We demonstrate examples of static and dynamic models of visualization. Based on the semantic model and proposed classification, the principles of visual metaphors formation for solving several applied tasks in various fields of knowledge (oil and gas production, biomedicine, materials science, education, management, etc.) are formulated.

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Author information

Authors and Affiliations

  1. V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia

    Alena Zakharova

  2. Tomsk Polytechnic University, Tomsk, Russia

    Aleksey Shklyar & Evgeniya Vekhter

Authors
  1. Alena Zakharova
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  2. Aleksey Shklyar
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  3. Evgeniya Vekhter
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Corresponding author

Correspondence to Alena Zakharova .

Editor information

Editors and Affiliations

  1. Volgograd State Technical University, Volgograd, Russia

    Alla G. Kravets

  2. Volgograd State Technical University, Volgograd, Russia

    Maxim V. Shcherbakov

  3. University of Patras, Patras, Greece

    Peter P. Groumpos

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Zakharova, A., Shklyar, A., Vekhter, E. (2023). Visual Data Models in Scientific Search for Interpretation of Multiparametric Signals. In: Kravets, A.G., Shcherbakov, M.V., Groumpos, P.P. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2023. Communications in Computer and Information Science, vol 1909. Springer, Cham. https://doi.org/10.1007/978-3-031-44615-3_8

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  • DOI: https://doi.org/10.1007/978-3-031-44615-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-44614-6

  • Online ISBN: 978-3-031-44615-3

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