Journal ArticleDOI
Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey
Johannes Kehrer,Helwig Hauser +1 more
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TLDR
This survey studies existing methods for visualization and interactive visual analysis of multifaceted scientific data and suggests new solutions for multirun and multimodel data as well as techniques that support a multitude of facets.Abstract:
Visualization and visual analysis play important roles in exploring, analyzing, and presenting scientific data. In many disciplines, data and model scenarios are becoming multifaceted: data are often spatiotemporal and multivariate; they stem from different data sources (multimodal data), from multiple simulation runs (multirun/ensemble data), or from multiphysics simulations of interacting phenomena (multimodel data resulting from coupled simulation models). Also, data can be of different dimensionality or structured on various types of grids that need to be related or fused in the visualization. This heterogeneity of data characteristics presents new opportunities as well as technical challenges for visualization research. Visualization and interaction techniques are thus often combined with computational analysis. In this survey, we study existing methods for visualization and interactive visual analysis of multifaceted scientific data. Based on a thorough literature review, a categorization of approaches is proposed. We cover a wide range of fields and discuss to which degree the different challenges are matched with existing solutions for visualization and visual analysis. This leads to conclusions with respect to promising research directions, for instance, to pursue new solutions for multirun and multimodel data as well as techniques that support a multitude of facets.read more
Citations
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Journal ArticleDOI
Visualizing High-Dimensional Data: Advances in the Past Decade
TL;DR: This work provides guidance for data practitioners to navigate through a modular view of the recent advances in high-dimensional data visualization, inspiring the creation of new visualizations along the enriched visualization pipeline, and identifying future opportunities for visualization research.
Journal ArticleDOI
Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR
Nicholas J. Tustison,K. L. Shrinidhi,Max Wintermark,Christopher R. Durst,Benjamin M. Kandel,James C. Gee,Murray Grossman,Brian B. Avants +7 more
TL;DR: This work introduces a framework for supervised segmentation based on multiple modality intensity, geometry, and asymmetry feature sets that interface the supervised learning capabilities of the random forest model with regularized probabilistic segmentation using the recently developed ANTsR package.
Visualizing High-Dimensional Data: Advances in the Past Decade.
TL;DR: A comprehensive survey of advances in high-dimensional data visualization that focuses on the past decade is provided in this article, with guidance for data practitioners to navigate through a modular view of the recent advances, inspiring the creation of new visualizations along the enriched visualization pipeline, and identifying future opportunities for visualization research.
Journal ArticleDOI
Toward a Quantitative Survey of Dimension Reduction Techniques
TL;DR: This work characterize the input data space, projection techniques, and the quality of projections, by several quantitative metrics, and samples these three spaces according to these metrics, aiming at good coverage with bounded effort.
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SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations
TL;DR: This study attempts to employ visual analytics that combines the state-of-the-art mining and visualization techniques to tackle the problem of formulating solutions immediately and comparing them rapidly for billboard placements using large-scale GPS trajectory data.
References
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Proceedings ArticleDOI
Visualizing multivalued data from 2D incompressible flows using concepts from painting
TL;DR: A new visualization method for 2d flows which allows us to combine multiple data values in an image for simultaneous viewing and uses a combination of discrete and continuous visual elements arranged in multiple layers to visually represent the data.
Journal ArticleDOI
Visualization of Multi‐Variate Scientific Data
Raphael Fuchs,Helwig Hauser +1 more
TL;DR: This report discusses how different techniques take effect at specific stages of the visualization pipeline and how they apply to multi‐variate data sets being composed of scalars, vectors and tensors and provides a categorization of these techniques.
Journal ArticleDOI
Importance-driven feature enhancement in volume visualization
TL;DR: This paper presents importance-driven feature enhancement as a technique for the automatic generation of cut-away and ghosted views out of volumetric data and includes an extended discussion on several possible schemes for levels of sparseness specification.
Book ChapterDOI
Inventing Discovery Tools: Combining Information Visualization with Data Mining
TL;DR: It is claimed that a combined approach could lead to novel discovery tools that preserve user control, enable more effective exploration, and promote responsibility.
Journal ArticleDOI
Data intermixing and multi-volume rendering
Wenli Cai,Georgios Sakas +1 more
TL;DR: Three levels of data intermixing and their rendering pipelines in direct multi‐volume rendering are presented, which discriminate image level intensity inter Mixing, accumulation level opacity intermixed, and illumination model level parameter intermixer.