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VRParaSet: A Virtual Reality Model for Visualizing Multidimensional Data

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Advances in Visual Computing (ISVC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11845))

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Abstract

Visual analytics relies heavily on two-dimensional graphical representations. Going beyond 2D is useful as we can utilize additional dimensions to present complex data sets but requires more user efforts to navigate/rotate to the appropriate views. Moreover, multidimensional visual analytics in immersed environments has not been fully explored. In this paper, we present a virtual reality model for visualizing multidimensional data in parallel coordinates, called VRParaSet. Our approach stacks polylines traveling in the similar paths between two consecutive dimensions. We anchor the lines at the vertices to reduce occlusions, offer esthetic appearance, and reveal data-based structures not evident in 2D panels or contours. The proposed model is compared to its 2D and 3D equivalences through a user study of 19 participants. The results show that the virtual reality model, while potentially useful, requires a lot of cares, especially on navigation and interaction within the virtual space.

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References

  1. Ngo, K.: A-Frame (2018). https://aframe.io/

  2. AlteredQualia: Stereoeffect (2018). http://alteredqualia.com

  3. Marcos, D., Ngo, D.G.K.: Supermedium (2018). https://www.supermedium.com/

  4. van Dam, A., Laidlaw, D.H., Simpson, R.M.: Experiments in immersive virtual reality for scientific visualization. Comput. Graphics 26, 535–555 (2002)

    Article  Google Scholar 

  5. Dang, T.N., Murray, P., Forbes, A.G.: PathwayMatrix: visualizing binary relationships between proteins in biological pathways. BMC Proc. 9(6), S3 (2015)

    Article  Google Scholar 

  6. Dang, T.N., Wilkinson, L.: ScagExplorer: exploring scatterplots by their scagnostics. In: Proceedings IEEE Pacific Visualization Symposium, PACIFICVIS 2014, pp. 73–80. IEEE Computer Society, Washington, DC, USA (2014). https://doi.org/10.1109/PacificVis.2014.42

  7. Dang, T.N., Wilkinson, L., Anand, A.: Stacking graphic elements to avoid over-plotting. IEEE Trans. Visual Comput. Graphics 16(6), 1044–1052 (2010). https://doi.org/10.1109/TVCG.2010.197

    Article  Google Scholar 

  8. Dasgupta, A., Kosara, R.: Pargnostics: screen-space metrics for parallel coordinates. IEEE Trans. Visual Comput. Graphics 16, 1017–2626 (2010)

    Article  Google Scholar 

  9. Davies, J.: Parallel sets: a visualisation technique for multidimensional categorical data (2018). https://www.jasondavies.com/parallel-sets/

  10. Donalek, C., et al.: Immersive and collaborative data visualization using virtual reality platforms. CoRR abs/1410.7670 (2014). http://arxiv.org/abs/1410.7670

  11. Dübel, S., Röhlig, M., Schumann, H., Trapp, M.: 2D and 3D presentation of spatial data: a systematic review. In: 2014 IEEE VIS International Workshop on 3DVis (3DVis), pp. 11–18, November 2014. https://doi.org/10.1109/3DVis.2014.7160094

  12. Friendly, M., Denis, D.: Milestones in the History of Thematic Cartography, Statistical Graphics, and Data Visualization: An Illustrated Chronology of Innovations. Statistical Consulting Service, York University (2008). https://books.google.com/books?id=cTjCjwEACAAJ

  13. Google: Google cardboard (2018). https://vr.google.com/cardboard/

  14. Gustafsson, M., Odd, O.: Virtual reality data visualization: concepts, technologies and more. Master’s thesis, Halmstad University (2018)

    Google Scholar 

  15. idVL, T.: Vrparallelset (2018). https://git.io/fjjDw

  16. idVL, T.: Vrparallelset aframe (2018). https://git.io/fjjDV

  17. Mboya, A.M.: Data visualization in virtual reality - a VR demo project, December 2017. https://medium.com/inborn-experience/data-visualization-in-virtual-reality-a-vr-demo-project-a31c577aaefc

  18. Metzler, K.: Experimenting with data visualization in VR, June 2018. http://ocean.sagepub.com/blog/2018/6/20/experimenting-with-data-visualization-in-vr

  19. Moran, A., Gadepally, V., Hubbell, M., Kepner, J.: Improving big data visual analytics with interactive virtual reality. In: 2015 IEEE High Performance Extreme Computing Conference (HPEC), pp. 1–6 (2015)

    Google Scholar 

  20. Mrdoob: Three.js (2018). https://threejs.org

  21. NewVantage-Partners: Big data executive survey 2017 (2017). http://newvantage.com/wp-content/uploads/2017/01/Big-Data-Executive-Survey-2017-Executive-Summary.pdf

  22. Ramette, A.: Multivariate analyses in microbial ecology. FEMS Microbiol. Ecol. 62(2), 142–160 (2007)

    Article  Google Scholar 

  23. Ribarsky, W., Bolter, J., den Bosch, A.O., van Teylingen, R.: Visualization and analysis using virtual reality. IEEE Comput. Graphics Appl. 94(1), 10–12 (2002)

    Article  Google Scholar 

  24. Singh, A., Saraswat, S., Faujdar, N.: Analyzing titanic disaster using machine learning algorithms. In: 2017 International Conference on Computing, Communication and Automation (ICCCA), pp. 406–411, May 2017. https://doi.org/10.1109/CCAA.2017.8229835

  25. Sullivan, P.: Graph-based data visualization in virtual reality: a comparison of user experiences. Master’s thesis, California Polytechnic State University (2016)

    Google Scholar 

  26. Nguyen, V.T., Hite, R., Dang, T.: Web-based virtual reality development in classroom: from learner’s perspectives. In: 2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), pp. 11–18, December 2018. https://doi.org/10.1109/AIVR.2018.00010

  27. Facebook Technologies: Oculus rift (2018). https://www.oculus.com/rift/

  28. W3C: Deviceorientation (2018). https://w3c.github.io/deviceorientation/

  29. Wilkinson, L., Anand, A., Grossman, R.: Graph-theoretic scagnostics. In: Proceedings of the IEEE Information Visualization 2005, pp. 157–164. IEEE Computer Society Press (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Texas Tech University, Lubbock, TX, 79409, USA

    Ngan V. T. Nguyen, Lino Virgen & Tommy Dang

Authors
  1. Ngan V. T. Nguyen
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  2. Lino Virgen
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  3. Tommy Dang
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Corresponding author

Correspondence to Ngan V. T. Nguyen .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. University of Nevada, Reno, NV, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Daniela Ushizima

  6. Latent AI, Palo Alto, CA, USA

    Sek Chai

  7. Texas A&M University, College Station, TX, USA

    Shinjiro Sueda

  8. Louisiana State University, Baton Rouge, LA, USA

    Xin Lin

  9. University of North Carolina at Charlotte, Charlotte, NC, USA

    Aidong Lu

  10. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Daniel Thalmann

  11. Notre Dame University, Notre Dame, IN, USA

    Chaoli Wang

  12. Bosch Research North America, Palo Alto, CA, USA

    Panpan Xu

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Nguyen, N.V.T., Virgen, L., Dang, T. (2019). VRParaSet: A Virtual Reality Model for Visualizing Multidimensional Data. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2019. Lecture Notes in Computer Science(), vol 11845. Springer, Cham. https://doi.org/10.1007/978-3-030-33723-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-33723-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33722-3

  • Online ISBN: 978-3-030-33723-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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