Journal ArticleDOI
Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey
Johannes Kehrer,Helwig Hauser +1 more
Reads0
Chats0
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
More filters
Towards Interactive Definition of Fast Surrogate Models for Geochemical Simulations Using Visual Analysis
TL;DR: It is argued that Visual Analysis has a prominent role to play for facilitating this process of accelerating geochemical simulation by surrogate models and a strategy for approaching it with Visual Analysis is outlined.
Journal Article
Transformation of Spatial Structure of Ion Trajectories into Iconic Representation
TL;DR: An iconic representation technique have been developed to transform a vector series from two-dimensional line graph in order to visualize the orientation, direction and magnitude of ion trajectories in three-dimensional space.
Journal ArticleDOI
Improved N-dimensional data visualization from hyper-radial values:
TL;DR: This research adapts and extends hyper-radial visualization, a technique used to visualize Pareto fronts in multi-objective optimizations, to become an n-dimensional visualization tool.
Journal ArticleDOI
Interactive Visual Analysis of Structure-borne Noise Data
TL;DR: In this article , an interactive visual exploration and analysis of high-dimensional, spectral data from noise simulation can facilitate design improvements in the context of conflicting criteria, i.e., noise from vibrating mechanical parts.
Journal ArticleDOI
Are We There Yet? A Roadmap of Network Visualization from Surveys to Task Taxonomies
TL;DR: In this paper , the authors present a meta-survey of recent surveys and task taxonomies published in the context of network visualization, focusing on increasingly challenging problems, such as visualizing dynamic, complex, multivariate, and geospatial networked data.
References
More filters
Book
Self-Organizing Maps
TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Journal ArticleDOI
The Elements of Statistical Learning
TL;DR: Chapter 11 includes more case studies in other areas, ranging from manufacturing to marketing research, and a detailed comparison with other diagnostic tools, such as logistic regression and tree-based methods.
Journal ArticleDOI
A Computer Movie Simulating Urban Growth in the Detroit Region
TL;DR: A Computer Movie Simulating Urban Growth in the Detroit Region as discussed by the authors was made to simulate urban growth in the city of Detroit, Michigan, United States of America, 1970, 1970.