=Paper=
{{Paper
|id=Vol-3041/149-152-paper-27
|storemode=property
|title=Visualization of Experimental Data in Web-Based Virtual Reality
|pdfUrl=https://ceur-ws.org/Vol-3041/149-152-paper-27.pdf
|volume=Vol-3041
|authors=Štefan Korečko,Martin Vaľa,Martin Fekete
}}
==Visualization of Experimental Data in Web-Based Virtual Reality==
https://ceur-ws.org/Vol-3041/149-152-paper-27.pdf
Proceedings of the 9th International Conference "Distributed Computing and Grid Technologies in Science and
Education" (GRID'2021), Dubna, Russia, July 5-9, 2021
VISUALIZATION OF EXPERIMENTAL DATA IN WEB-
BASED VIRTUAL REALITY
Š. Korečko1,a , M. Vaľa2, M. Fekete1
1
Department of Computers and Informatics, Faculty of Electrical Engineering and
Informatics, Technical University of Košice, Slovak Republic
2
Faculty of Science, Pavol Jozef Šafárik University in Košice, Slovak Republic
E-mail: a stefan.korecko@tuke.sk
Technological advances in the field of virtual reality and personal computation in general brought us
to the era of web-based virtual reality, where virtual environments can be accessed directly from web
browsers and without the need of installation of any additional software. Such online virtual
environments seem to be a promising tool for scientific data visualization. When accessed through
appropriate hardware, such as VR headsets, they also offer full immersion and isolation from external
influences. In this paper, we present a prototype solution for a histogram visualization in online
virtual environments. The prototype, named NDMVR, has been implemented using A-Frame
framework for visualization, React.js for compositionality and JSROOT for histogram data
acquisition. Its user interface is primarily adjusted to personal computers and VR headsets.
Keywords: virtual reality, extended reality, web-based, data, visualization
Štefan Korečko, Martin Vaľa, Martin Fekete
Copyright © 2021 for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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Proceedings of the 9th International Conference "Distributed Computing and Grid Technologies in Science and
Education" (GRID'2021), Dubna, Russia, July 5-9, 2021
1. Introduction and Related Work
There are several reasons why virtual reality (VR) can be considered a promising tool for
scientific data visualization. The first reason is that virtual reality allows us to inspect the data in non-
traditional ways. With an appropriate hardware, we can fully immerse into the data and observe them
as observing underwater objects when swimming or diving. And the hardware needed for the full
immersion is quite affordable. A VR headset costs about 500 Euros and a smartphone can be turned
into a headset with a Google Cardboard-like viewer for about 10 Euros. There are also other promising
possibilities such as visualization sharing or health improvement. By the visualization sharing we
mean that a scientist may invite others to join his or her virtual environment with a particular
visualization of a particular data set. Regarding the health, with an appropriate headset a scientist can
physically move when browsing through data, instead of just using a mouse or keyboard when sitting
in front of a computer. For decades, VR has been connected to the high energy physics research,
conducted on particle accelerators, such as the ones at CERN (Geneva) and JINR (Dubna). Via the
VENUS (Virtual Environment Navigation in the Underground Sites) project [1], VR had been
employed in the development of the LHC (Large Hadron Collider) itself. The infrastructure of LHC in
VR is also presented in [2], however with a different purpose. In [2], interactive, didactic, epistemic
models and corresponding activities are built for didactic purposes, namely to understand the ALICE
(A Large Ion Collider Experiment) detector. The work [2] utilizes the web-based VR, which means
that virtual environments can be opened as web pages in a web browser. Another work related to
ALICE is [3], which proposes to visualize data acquired in ALICE as 3D trajectories of particles. The
authors of [3] focus on compensating a distortion, which occurs when VR headsets are used to display
the trajectories.
The development presented here is an original software component named NDMVR (N-
DiMensional VR). NDMVR allows to visualize two- and three-dimensional histograms (TH2 and
TH3) in web-based VR. NDMVR is planned to be primarily used within a larger ecosystem, where
dynamic data acquisition will be provided by another original component, called SALSA. Its
utilization in other contexts is possible, too. As in the case of [2] and [3], NDMVR contributes to the
virtual reality utilization with respect to ALICE, but in a different way. Similarly to [2], it utilizes state
of the art technologies for the web-based VR and, as in [3], it focuses on the visualization of data
acquired in ALICE. However, [2] visualizes the equipment and not the data and [3] deals with
trajectories and not the histograms. The rest of the paper is organized as follows. Section 2 deals with
the software architecture of NDMVR and its relation to the data acquisition component SALSA. The
current functionality and user interface of NDMVR is described in Section 3 and the paper concludes
with remarks on future research and development in Section 4.
2. NDMVR Architecture
The NDMVR (N-DiMensional Virtual Rreality) has been designed as a reusable component,
utilizing software frameworks A-Frame [4] and React.js [5]. A-Frame is used for 3D visualization and
support of various virtual and extended reality hardware and React.js optimizes its performance and
allows to make it available in a form of a reusable and customizable component. The current version
of NDMVR is available online, at [6], and it runs exclusively on a client side, in a web browser. Its
architecture can be seen in Figure 1. The top-level part is NDMVR, an npm package that can be
incorporated to virtually any web application, created in React.js. NDMVR wraps the VR Scene part,
which is responsible for rendering a 3D scene that visualizes histograms of the TH2 or TH3 type. This
is done with the help of its two sub-parts, Histogram3D and VR Camera. Histogram3D is responsible
for the VR scene with the histogram and VR Camera defines the first-person point of view for the
user. The data to be visualized as histograms are acquired in the format of the ROOT Data Analysis
Framework [7] and NDMVR uses JSROOT [8], an already existing framework for web-based
scientific data visualization, to process the data. JSROOT is also used to render a TH1 histogram of a
particular bin of the histogram, visualized in the 3D scene.
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Proceedings of the 9th International Conference "Distributed Computing and Grid Technologies in Science and
Education" (GRID'2021), Dubna, Russia, July 5-9, 2021
Figure 1. Software Architecture of NDMVR
In the current version of NDMVR, the source of the data is a file. But this will be soon
replaced with another original component, named SALSA (Scalable Adaptive Large Structures
Analysis) [9], which will provide dynamic data acquisition from multiple data sources simultaneously.
SALSA supports distributed network system that can be constructed at a level of clusters, nodes,
processes and threads, with arbitrary tree structure. Its user interface is implemented as a web service
that can connect to SALSA network and distribute tasks, such as data acquisition, to workers.
3. NDMVR Functionality and User Interface
Figure 2 shows how the user interface of NDMVR looks in a web browser when visualizing a
two-dimensional histogram. The interface has two display modes, a normal mode and a VR mode.
Figure 2. NDMVR user interface with TH2 visualization
The normal mode (Figure 2) is the default one, used when an application using NDMVR is opened in
a web browser. The 3D scene with a TH2 histogram is on the left while on the right we can see a TH1
histogram for the selected (green) bin in TH3. The right side also contains settings for the TH1 and the
TH1 is also displayed on a 2D plane behind the TH2 in the 3D scene. In the 3D scene, the user can
move freely, scroll the histogram up and down along the red and green axis and select a bin and
display its TH1. It is also possible to display help panes with detailed instructions on how to use the
visualization. Only the 3D scene is shown in the VR mode. Regarding user input, NDMVR is
optimized for standard devices (mouse and keyboard) and VR headsets (motion tracking and handheld
controllers).
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Proceedings of the 9th International Conference "Distributed Computing and Grid Technologies in Science and
Education" (GRID'2021), Dubna, Russia, July 5-9, 2021
4. Conclusion
The NDMVR component, as presented here, can be regarded a prototype and there is much
more that we have in plan. In addition to the dynamic data acquisition via the SALSA component, we
also plan several experiments. These will be performed in order to answer related research questions,
such as what are the most effective ways of data visualization in VR, whether the assumed benefits of
VR will manifest, how easy it is to use this solution and how the data visualization in VR performs on
various hardware.
5. Acknowledgement
This work has been partially supported by the Slovak Research and Development Agency
project APVV-16-0202 and by the grant no. KEGA 035TUKE-4/2019 of the Cultural and Educational
Grant Agency of the Slovak Republic, funded by the Ministry of Education, Science, Research and
Sport of the Slovak Republic.
References
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https://doi.org/10.1145/240806.240812
[2] Christian Klein-Bösing, Philipp Bhatty, Reinhard Schulz-Schaeffer, Stefan Heusler. 3D und
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Detektors am CERN-LHC: Frühjahrstagung der Deutschen Physikalischen Gesellschaft 2020 Bonn,
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[4] A-Frame framework homepage, https://aframe.io/ (accessed 25.09.2021)
[5] React.js homepage, https://reactjs.org/ (accessed 25.09.2021)
[6] NDMVR Demonstrator homepage, https://ndmspc.gitlab.io/ndmvr (accessed 25.09.2021)
[7] ROOT Data Analysis Framework homepage, https://root.cern.ch/ (accessed 25.09.2021)
[8] JSROOT homepage, https://root.cern.ch/js/ (accessed 25.09.2021)
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