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
Externalising abstract mathematical models
TL;DR: The Influence Explorer and the Prosection Matrix as mentioned in this paper are interactive visualization artifacts that display the data generated by mathematical models in simple graphs which are interactively linked, which enables users to acquire insight into the complex relations embodied in the model.
Journal ArticleDOI
Multifield visualization using local statistical complexity
TL;DR: A new approach based on information theoretic concepts is introduced in this paper to detect important regions by extending the concept of local statistical complexity from finite state cellular automata to discretized (multi-)fields.
Journal ArticleDOI
Multifield-Graphs: An Approach to Visualizing Correlations in Multifield Scalar Data
TL;DR: The multifield-graph is introduced to give an overview of which multiple fields correlate and to show the strength of their correlation, and this information guides the selection of informative correlation fields for visualization.
Journal ArticleDOI
Hypermoval: interactive visual validation of regression models for real-time simulation
TL;DR: An interactive approach called HyperMoVal that is designed to support multiple tasks related to model validation, significantly accelerates the identification of regression models and increases the confidence in the overall engineering process.
Book ChapterDOI
Generalizing Focus+Context Visualization
TL;DR: A generalized definition of focus+context visualization is presented which extends its applicability also to scientific visualization and shows how different graphics resources such as space, opacity, color, etc., can be used to visually discriminate between data subsets in focus and their respective context.