Johannes Kehrer, Helwig Hauser
Visualization and Visual Analysis of Multi-faceted Scientific Data: A Survey
IEEE Transactions on Visualization and Computer Graphics, 19(3):495-513, March 2013. [
Draft] [
Slides]
Information
- Publication Type: Journal Paper (without talk)
- Workgroup(s)/Project(s):
- Date: March 2013
- ISSN: 1077-2626
- Journal: IEEE Transactions on Visualization and Computer Graphics
- Note: Spotlight paper of the March issue of TVCG
- Number: 3
- Volume: 19
- Pages: 495 – 513
Abstract
Visualization and visual analysis play important roles in exploring, analyzing and presenting scientific data. In many disciplines, data and model scenarios are becoming multi-faceted: data are often spatio-temporal and multi-variate; they stem from different data sources (multi-modal data), from multiple simulation runs (multi-run/ensemble data), or from multi-physics simulations of interacting phenomena (multi-model 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 multi-faceted 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 multi-run and multi-model data as well as techniques that support a multitude of facets.Additional Files and Images
Weblinks
BibTeX
@article{Kehrer-2013-STAR,
title = "Visualization and Visual Analysis of Multi-faceted
Scientific Data: A Survey",
author = "Johannes Kehrer and Helwig Hauser",
year = "2013",
abstract = "Visualization and visual analysis play important roles in
exploring, analyzing and presenting scientific data. In many
disciplines, data and model scenarios are becoming
multi-faceted: data are often spatio-temporal and
multi-variate; they stem from different data sources
(multi-modal data), from multiple simulation runs
(multi-run/ensemble data), or from multi-physics simulations
of interacting phenomena (multi-model 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
multi-faceted 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
multi-run and multi-model data as well as techniques that
support a multitude of facets.",
month = mar,
issn = "1077-2626",
journal = "IEEE Transactions on Visualization and Computer Graphics",
note = "Spotlight paper of the March issue of TVCG",
number = "3",
volume = "19",
pages = "495--513",
URL = "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/",
}