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Visualization of Large Datasets in Virtual Reality Systems

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Extended Reality (XR Salento 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14218))

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Abstract

This article explores the technology of large data files and the possibilities of their visualization in virtual reality. The three-dimensional unlimited scene, perception of perspective, freedom of movement, and interaction using natural gestures are all unique properties of virtual reality that can significantly change the way we receive, control, and evaluate visualization. Individual elements are discussed in detail, and their positive and negative aspects are described along with the potential applications. The knowledge gained from exploring extensive data files and virtual reality is used to develop two interactive demonstrations. The first virtual scene deals with the visualization of data from the smart city of Aarhus. The second demonstration works with the statistical data pertaining to the Czech Republic. The benefits and findings are then evaluated and summarized. The work also describes other possible uses of this technology and directions for further development.

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References

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Acknowledgments

This work and the contribution were supported by a project of Students Grant Agency (SPEV 2023) - FIM, University of Hradec Kralove, Czech Republic.

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Authors and Affiliations

  1. University of Hradec Kralove, Rokitanskeho 62, 50002, Hradec Kralove, Czech Republic

    Bruno Ježek, Ondřej Šimeček, Martin Konvička & Antonín Slabý

Authors
  1. Bruno Ježek
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  2. Ondřej Šimeček
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  3. Martin Konvička
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  4. Antonín Slabý
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Corresponding author

Correspondence to Martin Konvička .

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Editors and Affiliations

  1. University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis

  2. University of Naples Federico II, Naples, Italy

    Pasquale Arpaia

  3. CNR-STIIMA, Lecco, Italy

    Marco Sacco

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Ježek, B., Šimeček, O., Konvička, M., Slabý, A. (2023). Visualization of Large Datasets in Virtual Reality Systems. In: De Paolis, L.T., Arpaia, P., Sacco, M. (eds) Extended Reality. XR Salento 2023. Lecture Notes in Computer Science, vol 14218. Springer, Cham. https://doi.org/10.1007/978-3-031-43401-3_4

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  • DOI: https://doi.org/10.1007/978-3-031-43401-3_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43400-6

  • Online ISBN: 978-3-031-43401-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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