Exploring the design space of immersive urban analytics

Article, Preprint English OPEN
Zhutian Chen ; Yifang Wang ; Tianchen Sun ; Xiang Gao ; Wei Chen ; Zhigeng Pan ; Huamin Qu ; Yingcai Wu (2017)
  • Publisher: Elsevier
  • Journal: Visual Informatics (issn: 2468-502X)
  • Related identifiers: doi: 10.1016/j.visinf.2017.11.002
  • Subject: Information technology | Computer Science - Human-Computer Interaction | Virtual/Augmented/Mixed reality | Visualization theory | Computer Science - Graphics | T58.5-58.64 | Immersive urban analytics | Urban visualizations | Information visualizations

Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft HoloLens. These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence. In this paper, we propose an theoretical model to characterize the visualizations in immersive urban analytics. Further more, based on our comprehensive and concise model, we contribute a typology of combination methods of 2D and 3D visualizations that distinguish between linked views, embedded views, and mixed views. We also propose a supporting guideline to assist users in selecting a proper view under certain circumstances by considering visual geometry and spatial distribution of the 2D and 3D visualizations. Finally, based on existing works, possible future research opportunities are explored and discussed.
  • References (28)
    28 references, page 1 of 3

    [1] D. Liu, D. Weng, Y. Li, J. Bao, Y. Zheng, H. Qu, Y. Wu, Smartadp: Visual analytics of large-scale taxi trajectories for selecting billboard locations, IEEE Transactions on Visualization and Computer Graphics.

    [2] X. Huang, Y. Zhao, C. Ma, J. Yang, X. Ye, C. Zhang, Trajgraph: A graph-based visual analytics approach to studying urban network centralities using taxi trajectory data, IEEE Transactions on Visualization and Computer Graphics.

    [3] H. Guo, Z. Wang, B. Yu, H. Zhao, X. Yuan, Tripvista: Triple perspective visual trajectory analytics and its application on microscopic tra c data at a road intersection, in: IEEE Paci c Visualization Symposium, 2011.

    [4] G. L. Andrienko, N. V. Andrienko, P. Jankowski, D. A. Keim, M. Kraak, A. M. MacEachren, S. Wrobel, Geovisual analytics for spatial decision support: Setting the research agenda, International Journal of Geographical Information Science.

    [5] Y. Zheng, W. Wu, Y. Chen, H. Qu, L. M. Ni, Visual analytics in urban computing: An overview, IEEE Transactions on Big Data.

    [6] N. Ferreira, M. Lage, H. Doraiswamy, H. T. Vo, L. Wilson, H. Werner, M. Park, C. T. Silva, Urbane: A 3D framework to support data driven decision making in urban development, in: IEEE Conference on Visual Analytics Science and Technology, 2015.

    [8] B. Bach, R. Dachselt, S. Carpendale, T. Dwyer, C. Collins, B. Lee, Immersive analytics: Exploring future interaction and visualization technologies for data analytics, in: ACM Proceedings on Interactive Surfaces and Spaces, 2016.

    [9] G. L. Andrienko, N. V. Andrienko, U. Demsar, D. Dransch, J. Dykes, S. I. Fabrikant, M. Jern, M. Kraak, H. Schumann, C. Tominski, Space, time and visual analytics, International Journal of Geographical Information Science.

    [10] T. Munzner, Visualization Analysis and Design, A.K. Peters visualization series, A K Peters, 2014.

    [11] R. Azuma, A survey of augmented reality, Presence.

  • Metrics
    No metrics available
Share - Bookmark