Visualization of Large Datasets in Virtual Reality Systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020731" target="_blank" >RIV/62690094:18450/23:50020731 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-43401-3_4" target="_blank" >http://dx.doi.org/10.1007/978-3-031-43401-3_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-43401-3_4" target="_blank" >10.1007/978-3-031-43401-3_4</a>
Alternative languages
Result language
angličtina
Original language name
Visualization of Large Datasets in Virtual Reality Systems
Original language description
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. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-031-43400-6
ISSN
0302-9743
e-ISSN
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Number of pages
17
Pages from-to
52-68
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Cham
Event location
Lecce
Event date
Sep 6, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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