Color LinesView:AnApproach toVisualization of Families of Function Graphs

Fig. 1. Visualization of radiation (CPM values) along the Tokio-Fukushima highway.Abstract-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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“…To resolve overplotting in the time graph, they use a so-called time band display (similar to [18,24]) with coloring based on class intervals.…”

Section: Related Workmentioning

confidence: 99%

Stacking-Based Visualization of Trajectory Attribute Data

Tominski

Schumann

Andrienko

2012

IEEE Trans. Visual. Comput. Graphics

263

135

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“…The idea is similar to the original colorlines used to depict curves [13]. The width of a line section indicates the duration of an event, while the color again corresponds to the area of an event.…”

Section: Timed Event Sequencesmentioning

confidence: 99%

ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

et al. 2016

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Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis challenging, due to data size and complexity. We present an integrated solution for interactive visual analysis and exploration of events along trajectories data. Our approach supports analysis of event sequences at three different levels of abstraction, namely spatial, temporal, and events themselves. Customized views as well as standard views are combined to form a coordinated multiple views system. In addition to trajectories and events, we include onthe-fly derived data in the analysis. We evaluate our integrated solution using the IEEE VAST 2015 Challenge data set. A successful detection and characterization of malicious activity indicate the usefulness and efficiency of the presented approach.

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“…The concept of multiple linked views [Rob07] for integration of spatial and non‐spatial information is widely explored in a diverse set of application areas, e.g., medicine [MMH*13], bioinformatics [WRH*09, LSKS10], and geographic information systems [ZTM*13]. Techniques for brushing and linking of function sets are presented in previous works [MGKH07, Kon12]. Information‐based registration and fusion of data of different modalities is discussed by Haidacher et al [Hai11, HBKG08].…”

Section: Related Workmentioning

confidence: 99%

InSpectr: Multi‐Modal Exploration, Visualization, and Analysis of Spectral Data

Amirkhanov

Fröhler

Kastner

et al. 2014

Computer Graphics Forum

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This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high‐resolution X‐ray computed tomography (XCT) for structural characterization and low‐resolution X‐ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non‐spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie‐chart glyphs show elemental composition in 2D slice‐views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie‐chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real‐world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided.

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Color LinesView:AnApproach toVisualization of Families of Function Graphs

Cited by 10 publications

References 6 publications

Stacking-Based Visualization of Trajectory Attribute Data

Stacking-Based Visualization of Trajectory Attribute Data

ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

InSpectr: Multi‐Modal Exploration, Visualization, and Analysis of Spectral Data

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