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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A bricolage-style exploratory scenario analysis to manage uncertainty in socio-environmental systems modeling: investigating integrated water management options
TL;DR: The reasoning and steps behind a bricolage-style exploratory scenario analysis are described, which can be crafted by pragmatically and strategically combining different methods and practices, to raise awareness of the value of sharing this kind of analysis process, and motivate further work to improve sharing of know-how aboutbricolage in practice.
Journal ArticleDOI
An Interactive Data Visualization Framework for Exploring Geospatial Environmental Datasets and Model Predictions
TL;DR: A web-based interactive data visualization framework, the Interactive Catchment Explorer (ICE), for exploring environmental datasets and model outputs and provides a highly interactive user experience for discovering spatial patterns, evaluating relationships between variables and identifying specific locations using multivariate criteria.
Proceedings ArticleDOI
Towards a Visual Approach for Representing Analytical Provenance in Exploration Processes
TL;DR: In this article, the authors present an approach based on the concept of chained views to support the incremental exploration of large, multidimensional datasets, which is called MGExplorer (Multidimensional Graph Explorer).
Visual Abstractions for Analyzing Uncertain Multidimensional Data
TL;DR: This thesis provides means to explore higher dimensional scalar fields and ensembles of shapes and Scalar fields in two or three dimensions by utilizing GPU acceleration, which allow the user to discover data sets interactively.
Journal ArticleDOI
Association Rules-Based Multivariate Analysis and Visualization of Spatiotemporal Climate Data
TL;DR: This work presents an interactive heuristic visualization system that supports climate scientists and the public in their exploration and analysis of atmospheric phenomena of interest and provides techniques for identifying multivariate correlation and for better understanding the driving factors of climate phenomena.
References
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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.