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      Why not both? – Combining 2D maps and 3D space-time cubes for human trajectory data visualization

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      Proceedings of the 30th International BCS Human Computer Interaction Conference (HCI)

      Fusion

      11 - 15 July 2016

      Spatio-temporal data, trajectories, information visualization, visual analytics, space-time cube, 2d map, usability

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          Abstract

          Throughout the years, researchers have tried to understand dynamics and general patterns associated with human movement, e.g. in the context of urban planning, to improve the lives of citizens. To do this, it is necessary to properly analyse the spatio-temporal and the thematic properties of their trajectory data. Thematic maps, particularly 2D maps and 3D space-time cubes (STCs), are among the most common approaches to analyse and visualize these data. Previous research attests to the usefulness of these visualization techniques in different types of tasks. However, it is unlikely that the analysis of trajectories will be always limited to a specific type of task, thus, motivating additional studies to evaluate the dis/advantages of combining both techniques, within the same view/interaction context.

          In this paper, we address this specific challenge, by presenting a comparative study between three prototypes, one using a 2D map, one using a STC, and one combining both techniques, for the visualization of trajectories. Our results support previous studies’ conclusions, by showing the advantages of 2D maps and STCs for spatial and spatio-temporal tasks, respectively. They also point out towards the advantages of using both techniques together, as users seem to prefer this alternative and are able to complete different types of tasks accurately, despite the increasing complexity of the visualization.

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          Most cited references 25

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          Space, time and visual analytics

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            Space–time density of trajectories: exploring spatio-temporal patterns in movement data

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              Stacking-Based Visualization of Trajectory Attribute Data.

              Visualizing trajectory attribute data is challenging because it involves showing the trajectories in their spatio-temporal context as well as the attribute values associated with the individual points of trajectories. Previous work on trajectory visualization addresses selected aspects of this problem, but not all of them. We present a novel approach to visualizing trajectory attribute data. Our solution covers space, time, and attribute values. Based on an analysis of relevant visualization tasks, we designed the visualization solution around the principle of stacking trajectory bands. The core of our approach is a hybrid 2D/3D display. A 2D map serves as a reference for the spatial context, and the trajectories are visualized as stacked 3D trajectory bands along which attribute values are encoded by color. Time is integrated through appropriate ordering of bands and through a dynamic query mechanism that feeds temporally aggregated information to a circular time display. An additional 2D time graph shows temporal information in full detail by stacking 2D trajectory bands. Our solution is equipped with analytical and interactive mechanisms for selecting and ordering of trajectories, and adjusting the color mapping, as well as coordinated highlighting and dedicated 3D navigation. We demonstrate the usefulness of our novel visualization by three examples related to radiation surveillance, traffic analysis, and maritime navigation. User feedback obtained in a small experiment indicates that our hybrid 2D/3D solution can be operated quite well.
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                Author and article information

                Contributors
                Conference
                July 2016
                July 2016
                : 1-10
                Affiliations
                [1 ] LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal
                [2 ] INESC-ID, Instituto Superior Técnico, Universidade de Lisboa
                Article
                10.14236/ewic/HCI2016.22
                © Goncalves et al. Published by BCS Learning and Development Ltd. Proceedings British HCI 2016 - Fusion, Bournemouth, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Proceedings of the 30th International BCS Human Computer Interaction Conference
                HCI
                30
                Bournemouth University, Poole, UK
                11 - 15 July 2016
                Electronic Workshops in Computing (eWiC)
                Fusion
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Electronic Workshops in Computing

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