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NetImmerse - Evaluating User Experience in Immersive Network Exploration

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Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Health, Operations Management, and Design (HCII 2022)

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Abstract

The increasing amount of interconnected data has given rise to a need among researchers and practitioners to develop new approaches to visualizing network structures. The intricacy of such structures vastly exceeds the capacity of most conventional approaches to network visualization in terms of dimensional and resolution restrictions, as they are mostly presented as two-dimensional with on a limited size screen. An additional limitation of traditional network visualization tools from a human–computer interaction standpoint is the limited interaction itself where immersion and “deep-diving” into high-dimensional data is not possible. We built NetImmerse, an application to visualize network data in a virtual environment with the ability to overview, zoom, and request details on-demand. Within the virtual space, users can either walk around the 3D data representation or rotate and move the representation using the two controllers. We tested the application with users and simulated a representative use case. NetImmerse enabled the participants to gain accurate insights based on the defined task. Participants indicated a PU of 5.25 and a PEOU of 5.46. We believe that NetImmerse is an engaging platform for multi-dimensional data exploration and may result in better insights and enhanced network data exploration.

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References

  1. www.graphviz.org/

  2. www.cytoscape.org/

  3. www.gephi.org/

  4. Arsiwalla, X.D., et al.: Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction. Front. Neuroinform. 9, 2 (2015)

    Article  Google Scholar 

  5. Barabási, A.L., Gulbahce, N., Loscalzo, J.: Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 12(1), 56–68 (2011)

    Article  Google Scholar 

  6. Barabási, A.L., et al.: Network Science. Cambridge University Press, Cambridge (2016)

    MATH  Google Scholar 

  7. Betella, A., et al.: Understanding large network datasets through embodied interaction in virtual reality. In: Proceedings of the 2014 Virtual Reality International Conference, pp. 1–7 (2014)

    Google Scholar 

  8. Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.U.: Complex networks: structure and dynamics. Phys. Rep. 424(4–5), 175–308 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  9. Bramlet, M., Wang, K., Clemons, A., Speidel, N.C., Lavalle, S.M., Kesavadas, T.: Virtual reality visualization of patient specific heart model. J. Cardiovasc. Magn. Reson. 18(422), 1–2 (2016)

    Google Scholar 

  10. Calì, C., et al.: Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues. J. Comparat. Neurol. 524(1), 23–38 (2016)

    Article  Google Scholar 

  11. Cleveland, W.S., McGill, R.: Graphical perception: theory, experimentation, and application to the development of graphical methods. J. Am. Stat. Assoc. 79(387), 531–554 (1984)

    Article  Google Scholar 

  12. Deering, M.F.: HoloSketch: a virtual reality sketching/animation tool. ACM Trans. Comput.-Hum. Interact. (TOCHI) 2(3), 220–238 (1995)

    Article  Google Scholar 

  13. Drogemuller, A., Cunningham, A., Walsh, J., Cordeil, M., Ross, W., Thomas, B.: Evaluating navigation techniques for 3D graph visualizations in virtual reality. In: 2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA), pp. 1–10. IEEE (2018)

    Google Scholar 

  14. Drogemuller, A., Cunningham, A., Walsh, J., Ross, W., Thomas, B.H.: VRige: exploring social network interactions in immersive virtual environments. In: Proceedings of the International Symposium on Big Data Visual Analytics (BDVA). IEEE, NJ, USA (2017)

    Google Scholar 

  15. Ens, B., et al.: Grand challenges in immersive analytics. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1–17 (2021)

    Google Scholar 

  16. Fonnet, A., Prie, Y.: Survey of immersive analytics. IEEE Trans. Vis. Comput. Graph. 27, 2101–2122 (2019)

    Article  Google Scholar 

  17. Heer, J., Bostock, M.: Crowdsourcing graphical perception: using mechanical turk to assess visualization design. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 203–212 (2010)

    Google Scholar 

  18. Kenderdine, S., Nicholson, J.K., Mason, I.: Modeling people and populations: exploring medical visualization through immersive interactive virtual environments. In: Metabolic Phenotyping in Personalized and Public Healthcare, pp. 333–367. Elsevier (2016)

    Google Scholar 

  19. Knoke, D., Yang, S.: Social Network Analysis. Sage Publications, Thousand Oaks (2019)

    Google Scholar 

  20. Kotlarek, J., et al.: A study of mental maps in immersive network visualization. In: 2020 IEEE Pacific Visualization Symposium (PacificVis), pp. 1–10. IEEE (2020)

    Google Scholar 

  21. Kraus, M., et al.: Immersive analytics with abstract 3D visualizations: a survey. In: Computer Graphics Forum. Wiley Online Library (2021)

    Google Scholar 

  22. Kraus, M., Klein, K., Fuchs, J., Keim, D.A., Schreiber, F., Sedlmair, M.: The value of immersive visualization. IEEE Comput. Graph. Appl. 41(4), 125–132 (2021)

    Article  Google Scholar 

  23. Kuznetsov, M., et al.: The immersive graph genome explorer: navigating genomics in immersive virtual reality. In: 2021 IEEE 9th International Conference on Serious Games and Applications for Health (SeGAH), pp. 1–8. IEEE (2021)

    Google Scholar 

  24. Kwon, O.H., Crnovrsanin, T., Ma, K.L.: What would a graph look like in this layout? A machine learning approach to large graph visualization. IEEE Trans. Vis. Comput. Graph. 24(1), 478–488 (2017)

    Article  Google Scholar 

  25. Lee, B., Plaisant, C., Parr, C.S., Fekete, J.D., Henry, N.: Task taxonomy for graph visualization. In: Proceedings of the 2006 AVI Workshop on BEyond Time and Errors: Novel Evaluation Methods for Information Visualization, pp. 1–5 (2006)

    Google Scholar 

  26. Marangunić, N., Granić, A.: Technology acceptance model: a literature review from 1986 to 2013. Univ. Access Inf. Soc. 14(1), 81–95 (2014). https://doi.org/10.1007/s10209-014-0348-1

    Article  Google Scholar 

  27. McGhee, J., Thompson-Butel, A.G., Faux, S., Bou-Haidar, P., Bailey, J.: The fantastic voyage: an arts-led approach to 3D virtual reality visualization of clinical stroke data. In: Proceedings of the 8th International Symposium on Visual Information Communication and Interaction, pp. 69–74 (2015)

    Google Scholar 

  28. McIntire, J.P., Havig, P.R., Geiselman, E.E.: Stereoscopic 3D displays and human performance: a comprehensive review. Displays 35(1), 18–26 (2014)

    Article  Google Scholar 

  29. Millais, P., Jones, S.L., Kelly, R.: Exploring data in virtual reality: comparisons with 2D data visualizations. In: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–6 (2018)

    Google Scholar 

  30. Moody, J., McFarland, D., Bender-deMoll, S.: Dynamic network visualization. Am. J. Sociol. 110(4), 1206–1241 (2005)

    Article  Google Scholar 

  31. Munzner, T.: Process and pitfalls in writing information visualization research papers. In: Kerren, A., Stasko, J.T., Fekete, J.-D., North, C. (eds.) Information Visualization. LNCS, vol. 4950, pp. 134–153. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70956-5_6

    Chapter  Google Scholar 

  32. Noel, S., Jajodia, S.: Managing attack graph complexity through visual hierarchical aggregation. In: Proceedings of the 2004 ACM Workshop on Visualization and Data Mining for Computer Security, pp. 109–118 (2004)

    Google Scholar 

  33. Pirch, S., et al.: The VRNetzer platform enables interactive network analysis in virtual reality. Nat. Commun. 12(1), 1–14 (2021)

    Article  Google Scholar 

  34. Royston, S., DeFanti, C., Perlin, K.: A collaborative untethered virtual reality environment for interactive social network visualization. arXiv preprint arXiv:1604.08239 (2016)

  35. Schroeder, K., Ajdadilish, B., Henkel, A.P., Calero Valdez, A.: Evaluation of a financial portfolio visualization using computer displays and mixed reality devices with domain experts. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–9 (2020)

    Google Scholar 

  36. Selassie, D., Heller, B., Heer, J.: Divided edge bundling for directional network data. IEEE Trans. Vis. Comput. Graph. 17(12), 2354–2363 (2011)

    Article  Google Scholar 

  37. Shneiderman, B.: The eyes have it: a task by data type taxonomy for information visualizations. In: The Craft of Information Visualization, pp. 364–371. Elsevier (2003)

    Google Scholar 

  38. Simpson, M., Zhao, J., Klippel, A.: Take a walk: evaluating movement types for data visualization in immersive virtual reality. In: Workshop on Immersive Analytics. IEEE, Vis (2017)

    Google Scholar 

  39. Smallman, H.S., John, M.S., Oonk, H.M., Cowen, M.B.: Information availability in 2D and 3D displays. IEEE Comput. Graph. Appl. 21(5), 51–57 (2001)

    Article  Google Scholar 

  40. Sorger, J., Waldner, M., Knecht, W., Arleo, A.: Immersive analytics of large dynamic networks via overview and detail navigation. In: 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), pp. 144–1447. IEEE (2019)

    Google Scholar 

  41. Strogatz, S.H.: Exploring complex networks. Nature 410(6825), 268–276 (2001)

    Article  MATH  Google Scholar 

  42. Van Wijk, J.J., Van Selow, E.R.: Cluster and calendar based visualization of time series data. In: Proceedings 1999 IEEE Symposium on Information Visualization (InfoVis 1999), pp. 4–9. IEEE (1999)

    Google Scholar 

  43. Varga, M.N., Merrison-Hort, R., Watson, P., Borisyuk, R., Livingstone, D.: Tadpole VR: virtual reality visualization of a simulated tadpole spinal cord. Virtual Reality 25(1), 1–17 (2021)

    Article  Google Scholar 

  44. Villaveces, J.M., Koti, P., Habermann, B.H.: Tools for visualization and analysis of molecular networks, pathways, and-omics data. Adv. Appl. Bioinform. Chem.: AABC 8, 11 (2015)

    Google Scholar 

  45. Ware, C., Franck, G.: 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, pp. 182–183. IEEE (1994)

    Google Scholar 

  46. Ware, C., Mitchell, P.: Visualizing graphs in three dimensions. ACM Trans. Appl. Percept. (TAP) 5(1), 1–15 (2008)

    Article  Google Scholar 

  47. Widjojo, E.A., Chinthammit, W., Engelke, U.: Virtual reality-based human-data interaction. In: 2017 International Symposium on Big Data Visual Analytics (BDVA), pp. 1–6. IEEE (2017)

    Google Scholar 

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Acknowledgement

We would like to express our appreciation to Dr Benjamin Lucas for his valuable and constructive suggestions during the planning and development phase of this research work and providing the network data used in this study.

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Authors and Affiliations

  1. Human Computer Interaction Center, RWTH Aachen, Aachen, Germany

    Kay Schröder

  2. Human Data Interaction Lab, Zuyd University of Applied Sciences, Heerlen, Netherlands

    Kay Schröder, Steffi Kohl & Batoul Ajdadilish

  3. Maastricht University, Maastricht, Netherlands

    Steffi Kohl

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  1. Kay Schröder
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  2. Steffi Kohl
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  3. Batoul Ajdadilish
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Correspondence to Kay Schröder .

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Editors and Affiliations

  1. School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

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Schröder, K., Kohl, S., Ajdadilish, B. (2022). NetImmerse - Evaluating User Experience in Immersive Network Exploration. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Health, Operations Management, and Design. HCII 2022. Lecture Notes in Computer Science, vol 13320. Springer, Cham. https://doi.org/10.1007/978-3-031-06018-2_27

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  • DOI: https://doi.org/10.1007/978-3-031-06018-2_27

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