The paper describes a method for the immersive, dynamic visualization of undirected, weighted graphs. Using the Fruchterman-Reingold method, force-directed graphs are drawn in a Virtual-Reality system. The user can walk through the data, as well as move vertices using controllers, while the network display rearranges in realtime according to Newtonian physics. In addition to the physics behind the employed method, the paper explains the most pertinent computational mechanisms for its implementation, using Unity, SteamVR, and a Virtual-Reality system such as HTC Vive (the source package is made available for download). It was found that the method allows for intuitive exploration of graphs with on the order of vertices, and that dynamic extrusion of vertices and realtime readjustment of the network structure allows for developing an intuitive understanding of the relationship of a vertex to the remainder of the network. Based on this observation, possible future developments are suggested.
GibsonHFaithJVickersP.A survey of two-dimensional graph layout techniques for information visualisation. Inf Vis2013; 12(3–4): 324–357.
3.
CheongSHSiYW.Force-directed algorithms for schematic drawings and placement: a survey. Inf Vis2020; 19(1): 65–91.
4.
PavlopoulosGAPaez-EspinoDKyrpidesNC, et al. Empirical comparison of visualization tools for larger-scale network analysis. Adv Bioinformatics2017; 2017: 1278932.
5.
Motaleb FaysalMAArifuzzamanS. A comparative analysis of large-scale network visualization tools. In: 2018 IEEE international conference on big data (Big Data), Seattle, WA, 10–13 December 2018, pp.4837–4843. DOI: 10.1109/BigData.2018.8622001.
GraciaAGonzálezSRoblesV, et al. New insights into the suitability of the third dimension for visualizing multivariate/multidimensional data: a study based on loss of quality quantification. Inf Vis2016; 15(1): 3–30.
10.
ParkJLeeKHanJ.Interactive visualization of magnetic field for virtual science experiments. J Visual2016; 19(1): 129–139.
11.
HuQYuDWangS, et al. Hybrid three-dimensional representation based on panoramic images and three-dimensional models for a virtual museum: data collection, model, and visualization. Inf Vis2017; 16(2): 126–138.
12.
LochheadIMHedleyN.Modeling evacuation in institutional space: linking three-dimensional data capture, simulation, analysis, and visualization workflows for risk assessment and communication. Inf Vis2019; 18(1): 173–192.
13.
WareCFranckG.Viewing a graph in a virtual reality display is three times as good as a 2d diagram. In: Proceedings of 1994 IEEE symposium on visual languages, St. Louis, MO, 4–7 October 1994, pp.182–183. New York, NY: IEEE.
14.
DrogemullerACunninghamAWalshJ, et al. Evaluating navigation techniques for 3d graph visualizations in virtual reality. In: 2018 International symposium on big data visual and immersive analytics (BDVA), Konstanz, Germany, 17–19 October 2018, pp.1–10. New York, NY: IEEE.
15.
HalpinHZielinskiDJBradyR, et al. Exploring semantic social networks using virtual reality. In: International semantic web conference, Karlsruhe, Germany, October 26–30, 2008. Berlin, Heidelberg: Springer, pp.599–614.
16.
CapeceNErraUGrippaJ. GraphVR: A virtual reality tool for the exploration of graphs with HTC Vive system. In: 2018 22nd International conference information visualisation (IV), Fisciano, Italy, 10–13 July 2018, pp.448–453. DOI: 10.1109/iV.2018.00084.
17.
PirchSMüllerFIofinovaE, et al. The VRNetzer platform enables interactive network analysis in virtual reality. Nat Commun2021; 12(1): 2432–2514.
18.
ErraUMalandrinoDPepeL.Virtual reality interfaces for interacting with three-dimensional graphs. Int J Hum Comput Interact2019; 35(1): 75–88.
19.
KreuzerM.Interactive visualization and comparison of graphs in virtual reality. Bachelor’s Thesis, Universität Würzburg, Würzburg, Germany, 2019.
20.
SullivanPA.Graph-based data visualization in virtual reality: a comparison of user experiences. Master’s Thesis, California Polytechnic State University, San Luis Obispo, CA, 2016.
21.
Shi F and The Odum Institute. Learn about network visualization in R with data from UK faculty dataset (2008). SAGE Research Methods Datasets2019; Part 2.
22.
CsardiG.A collection of network data sets for the ‘igraph’ package. Technical report, The Comprehensive R Archive Network (CRAN), 2015.
23.
BauerWWestfallGD.University physics. New York, NY: McGraw-Hill, 2011.
DavisSNesbittKNalivaikoE.A systematic review of cybersickness. In: Proceedings of the 2014 conference on interactive entertainment, Newcastle. NSW, Australia, 2–3 December 2014, pp.1–9. New York, NY: Association for Computing Machinery.
28.
FrommelJSonntagSWeberM. Effects of controller-based locomotion on player experience in a virtual reality exploration game. In: Proceedings of the 12th international conference on the foundations of digital games, Hyannis, MA, 14–17 August 2017, pp.1–6. New York, NY: Association for Computing Machinery.
29.
YildirimC.Don’t make me sick: investigating the incidence of cybersickness in commercial virtual reality headsets. Virtual Real2020; 24(2): 231–239.
30.
StoakleyRConwayMJPauschR. Virtual reality on a WIM: interactive worlds in miniature. In: Proceedings of the SIGCHI conference on human factors in computing systems, Toronto, Canada, 26 April–1 May 2014, pp. 265–272. New York, NY: Association for Computing Machinery.
31.
WagnerJStuerzlingerWNedelL.Comparing and combining virtual hand and virtual ray pointer interactions for data manipulation in immersive analytics. IEEE Trans Vis Comput Graph2021; 27(5): 2513–2523.
32.
FreyGJurkschatAKorkutS, et al. Intuitive hand gestures for the interaction with information visualizations in virtual reality. In: JungTTom DieckMC (eds.) Augmented reality and virtual reality. Cham: Springer, 2019, pp.261–273.
33.
DrogemullerACunninghamAWalshJA, et al. Haptic and visual comprehension of a 2d graph layout through physicalisation. In: Proceedings of the 2021 CHI conference on human factors in computing systems, Yokohama, Japan, 8–13 May 2021, pp.1–16. New York, NY: Association for Computing Machinery.
34.
KnierimPKoschTSchwindV, et al. Tactile drones-providing immersive tactile feedback in virtual reality through quadcopters. In: Proceedings of the 2017 CHI conference extended abstracts on human factors in computing systems, Denver, CO, 6–11 May 2017, pp. 433–436. New York, NY: Association for Computing Machinery.
35.
AbtahiPLandryBYangJ, et al. Beyond the force: using quadcopters to appropriate objects and the environment for haptics in virtual reality. In: Proceedings of the 2019 CHI conference on human factors in computing systems, Glasgow, Scotland, 4–9 May 2019, pp.1–13. New York, NY: Association for Computing Machinery.
