Journal of the Korea Computer Graphics Society (한국컴퓨터그래픽스학회논문지)

Korea Computer Graphics Society (한국컴퓨터그래픽스학회)
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An Extended Reality-based Data Visualization Supporting Heterogeneous Remote Collaboration

이기종 원격협업을 지원하는 확장현실 기반 데이터 시각화

  • Hyoji Ha (Graduate School of Metaverse, Sogang University) ;
  • Hyeonwoo Kim (Graduate School of Metaverse, Sogang University) ;
  • Yongseo Kim (Graduate School of Metaverse, Sogang University) ;
  • Sanghun Park (Graduate School of Metaverse, Sogang University)
  • 하효지 (서강대학교 메타버스전문대학원) ;
  • 김현우 (서강대학교 메타버스전문대학원) ;
  • 김영서 (서강대학교 메타버스전문대학원) ;
  • 박상훈 (서강대학교 메타버스전문대학원)
  • Received : 2024.06.15
  • Accepted : 2024.07.05
  • Published : 2024.07.25
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Abstract

This study aims to develop a system that enables users employing PC and VR devices to collaboratively analyze data visualizations in a remote environment. The system provides a task-oriented node-link control interface to aid users in understanding the visualization analysis process and effectively distributing roles. Additionally, it offers a network environment where multiple users can collaborate and receive feedback on visualization analysis even when physically separated. To elucidate the collaborative analysis method implemented in the system, we designed a scenario. Furthermore, we conducted a pilot experiment to evaluate the system's usability with participants majoring in related fields. The experimental results confirmed that users can freely analyze data through easily comprehensible interface manipulations in an extended reality space, and efficiently conduct real-time collaborative analysis in a remote environment.

본 연구는 PC 및 VR 디바이스를 이용하는 사용자가 리모트 환경에서 데이터 시각화를 협업 분석할 수 있는 시스템을 개발한다. 시스템에서는 사용자들이 시각화 분석의 프로세스 이해를 돕고 역할 분담을 효과적으로 할 수 있도록 업무 지향(task-oriented) 형식의 노드-링크 제어 인터페이스(node-link control interface)를 제공한다. 또한, 다수의 사용자가 물리적으로 공간이 분리되어도 협업을 진행하여 시각화 분석의 피드백을 받을 수 있는 네트워크 환경을 제공한다. 시스템에서 진행하는 협업 분석 방식을 설명하기 위해 시나리오를 설계하였다. 그리고 관련분야 전공자를 대상으로 시스템의 사용성을 측정하는 파일럿 실험을 진행하였다. 실험 결과 확장현실 공간에서 이해하기 쉬운 형식의 인터페이스 조작을 통해 데이터를 자유롭게 분석할 수 있고, 리모트 환경에서도 실시간으로 협업 분석을 수월하게 진행할 수 있음을 확인하였다.

Keywords

Acknowledgement

이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구이고(RS-2023-00251681), 정보통신기획평가원의 대학ICT연구센터사업(RS-2023-00259099)과 메타버스융합대학원(RS-2022-00156318)의 지원으로 수행되었음.

References

  1. R. Liu, M. Gao, L. Wang, X. Wang, Y. Xiang, A. Zhang, J. Xia, Y. Chen, and S. Chen, "Interactive extended reality techniques in information visualization," IEEE Transactions on Human-Machine Systems, vol. 52, no. 6, pp. 1338-1351, 2022. https://doi.org/10.1109/THMS.2022.3211317
  2. C. Donalek, S. G. Djorgovski, A. Cioc, A. Wang, J. Zhang, E. Lawler, S. Yeh, A. Mahabal, M. Graham, A. Drake, et al., "Immersive and collaborative data visualization using virtual reality platforms," in 2014 IEEE International Conference on Big Data (Big Data). IEEE, 2014, pp. 609-614.
  3. B. Lee, M. Cordeil, A. Prouzeau, B. Jenny, and T. Dwyer, "A design space for data visualisation transformations between 2d and 3d in mixed-reality environments," in Proceedings of the 2022 CHI conference on human factors in computing systems, 2022, pp. 1-14.
  4. A. Prouzeau, Y. Wang, B. Ens, W. Willett, and T. Dwyer, "Corsican twin: Authoring in situ augmented reality visualisations in virtual reality," in Proceedings of the international conference on advanced visual interfaces, 2020, pp. 1-9.
  5. J. McCormack, J. C. Roberts, B. Bach, C. D. S. Freitas, T. Itoh, C. Hurter, and K. Marriott, "Multisensory immersive analytics," Immersive analytics, pp. 57-94, 2018.
  6. B. Patnaik, A. Batch, and N. Elmqvist, "Information olfactation: Harnessing scent to convey data," IEEE transactions on visualization and computer graphics, vol. 25, no. 1, pp. 726-736, 2018.
  7. M. Cordeil, A. Cunningham, B. Bach, C. Hurter, B. H. Thomas, K. Marriott, and T. Dwyer, "Iatk: An immersive analytics toolkit," in 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). IEEE, 2019, pp. 200-209.
  8. R. Sicat, J. Li, J. Choi, M. Cordeil, W.-K. Jeong, B. Bach, and H. Pfister, "Dxr: A toolkit for building immersive data visualizations," IEEE transactions on visualization and computer graphics, vol. 25, no. 1, pp. 715-725, 2018.
  9. 최준영, 정해진, 정원기, et al., "가젯암: 확장현실을 위한 손제스처 기반 대화형 데이터 시각화 시스템," Journal of the Korea Computer Graphics Society, vol. 25, no. 2, pp. 31-41, 2019.
  10. S. Dai, T. Dwyer, B. Ens, and L. Besancon, "Reaching for data: precise embodied selection-at-a-distance for immersive visualisation," in IEEE VIS, 2023.
  11. B. Lee, X. Hu, M. Cordeil, A. Prouzeau, B. Jenny, and T. Dwyer, "Shared surfaces and spaces: Collaborative data visualisation in a co-located immersive environment," IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 2, pp. 1171-1181, 2020.
  12. M. Cordeil, A. Cunningham, T. Dwyer, B. H. Thomas, and K. Marriott, "Imaxes: Immersive axes as embodied affordances for interactive multivariate data visualisation," in Proceedings of the 30th annual ACM symposium on user interface software and technology, 2017, pp. 71-83.
  13. P. Millais, S. L. Jones, and R. Kelly, "Exploring data in virtual reality: Comparisons with 2d data visualizations," in Extended abstracts of the 2018 CHI conference on human factors in computing systems, 2018, pp. 1-6.
  14. J. Chen, C. Li, S. Song, and C. Wang, "iarvis: Mobile ar based declarative information visualization authoring, exploring and sharing," in 2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR). IEEE, 2023, pp. 11-21.
  15. S. Butscher, S. Hubenschmid, J. Muller, J. Fuchs, and H. Reiterer, "Clusters, trends, and outliers: How immersive technologies can facilitate the collaborative analysis of multidimensional data," in Proceedings of the 2018 CHI conference on human factors in computing systems, 2018, pp. 1-12.
  16. A. Batch, P. W. Butcher, P. D. Ritsos, and N. Elmqvist, "Wizualization: A "hard magic" visualization system for immersive and ubiquitous analytics," IEEE Transactions on Visualization and Computer Graphics, 2023.
  17. W. Tong, M. Xia, K. K. Wong, D. A. Bowman, T.-C. Pong, H. Qu, and Y. Yang, "Towards an understanding of distributed asymmetric collaborative visualization on problem-solving," in 2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR). IEEE, 2023, pp. 387-397.
  18. R. Amar, J. Eagan, and J. Stasko, "Low-level components of analytic activity in information visualization," in IEEE Symposium on Information Visualization, 2005. INFOVIS 2005. IEEE, 2005, pp. 111-117.
  19. D. Ilett, "Shader graph," in Building Quality Shaders for Unity®: Using Shader Graphs and HLSL Shaders. Springer, 2022, pp. 81-107.
  20. B. Sewell, Blueprints visual scripting for unreal engine. Packt Publishing Ltd, 2015.
  21. J. Suemin, C. JunYoung, J. Haejin, and J. Won-Ki, "Breaking down the technical barrier: Visual programming driven dynamic immersive analytics using xrops," in IEEE VIS, 2023.
  22. A. Inselberg, "The plane with parallel coordinates," The visual computer, vol. 1, pp. 69-91, 1985. https://doi.org/10.1007/BF01898350