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
Visualization System Requirements for Data Processing Pipeline Design and Optimization
TL;DR: This article presents a new characterization of the requirements for pipeline design and optimization, based on both a review of the literature and first-hand assessment of eight application case studies, and identifies seven future challenges for visualization research that are not met by the capabilities of today's systems.
Journal ArticleDOI
A scalable cyberinfrastructure solution to support big data management and multivariate visualization of time-series sensor observation data
TL;DR: This work expects this work to make a major contribution to both the visualization building block development in cyberinfrastructure research and the advancement of visual presentation and analysis of sensor data in domain sciences.
Journal ArticleDOI
Challenges and strategies for the visual exploration of complex environmental data
Carolin Helbig,Doris Dransch,Michael Böttinger,Colin W. Devey,Antonie Haas,Mario Hlawitschka,Claudia Kuenzer,Karsten Rink,Christian Schäfer-Neth,Gerik Scheuermann,Tom Kwasnitschka,Andrea Unger +11 more
TL;DR: It is argued visual data exploration should become a common analytics approach in Earth system science due to its potential for analysis and interpretation of large and complex spatio-temporal data and significantly facilitates insight into environmental data and derivation of knowledge from it.
DissertationDOI
Exploratory search in time-oriented primary data
TL;DR: This thesis expects that ES will have a tremendous impact on data-driven research for many research fields, and presents a reference workflow for the design and the application of ESS for time-oriented primary data.
Posted Content
Deep Learning Multidimensional Projections.
TL;DR: The approach generates projections with similar characteristics as the learned ones, is computationally two to four orders of magnitude faster than existing projection methods, has no complex-to-set user parameters, handles out-of-sample data in a stable manner, and can be used to learn any projection technique.
References
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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.