Multifield Visualization - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 99

and examine design principles and guidelines that may influence the success in
deploying such a technique.
Some may suggest that it is not common to encounter multifield datasets. In the
next chapter, Derived Fields, Zhang and Natarajan show that even with a single
input field, one can derive a multifield dataset, and there is a need for visualizing
such derived fields. They first consider the scenario of deriving additional field
data from two input fields, then discuss cases where there are more than two input
fields, and finally examine the scenario of deriving a multifield dataset from a
single input field. This chapter confirms the ubiquity of multifield data.
The next two chapters focus on the role of interaction in visualizing multifield
data. In the chapter entitled Interactive Visual Exploration and Analysis, Weber
and Hauser examine different aspects of interactive visual analysis of multifield
data, ranging from the generic show-and-brush paradigm to application-specific
paradigms where users may interact with application-specific features. In the
following chapter, Visual Exploration of Multivariate Volume Data Based on
Clustering, Linsen examines the visual analytics paradigm where analysis,
visualization, and interaction form a closed loop. In particular, Linsen examines
the attribute space in multivariate volume visualization, and the role of interactive
visual exploration in cluster-based data analysis.
The following two chapters focus on the role of feature analysis in visualizing
multifield data. In the chapter entitled Feature-Based Visualization of Multifields,
Obermaier and Peikert begin with a general discussion on feature extraction in
scientific visualization. They then provide us with definitions of multifield features
and a categorization of different feature-based visualization techniques. In the
following chapter, Feature Analysis in Multifields, Carr examines techniques for
detecting features in multifield data. In particular, Carr organizes feature analysis
techniques into categories of Scalar Features in Reduced Domains, Scalar
Features in the Range, Manifold Features, Overlapping Scalar Features, and Joint
Feature Analysis, and structure the discussions accordingly.
The last chapter, led by Laramee, captures a truly collaborative effort by this
Dagstuhl break-out group, and reflects the enthusiasm and energy that made
members of group so deeply immersed in the discussions and writings for this Part.
The chapter, which is entitled Future Challenges and Unsolved Problems in Multi-
Field Visualization, consists of an introduction by Laramee and contributions from
Carr, Chen, Hauser, Linsen, Mueller, Natarajan, Obermaier, Peikert, and Zhang. It
is a collection of proposed challenges in multifield visualization, covering a broad
range of technical aspects. This collection of challenges will no doubt influence the
future directions in this area of research.
Min Chen
University of Oxford, UK
e-mail: [e-mail]