In this work, we introduce EdgeMaps as a new method for integrating the visualization of explicit and implicit
data relations. Explicit relations are specific connections between entities already present in a given dataset, while
implicit relations are derived from multidimensional data based on shared properties and similarity measures.
Many datasets include both types of relations, which are often difficult to represent together in information
visualizations. Node-link diagrams typically focus on explicit data connections, while not incorporating implicit
similarities between entities. Multi-dimensional scaling considers similarities between items, however, explicit
links between nodes are not displayed. In contrast, EdgeMaps visualize both implicit and explicit relations by
combining and complementing spatialization and graph drawing techniques. As a case study for this approach
we chose a dataset of philosophers, their interests, influences, and birthdates. By introducing the limitation of
activating only one node at a time, interesting visual patterns emerge that resemble the aesthetics of fireworks
and waves. We argue that the interactive exploration of these patterns may allow the viewer to grasp the
structure of a graph better than complex node-link visualizations.
While their importance is increasingly recognized, there remain many challenges in the development of uncertainty visualizations.
We introduce two uncertainty visualizations for 2D bidirectional vector fields: one based on a static glyph
and the other based on animated flow. These visualizations were designed for the task of understanding and interpreting
anisotropic rock property models in the domain of seismic data processing. Aspects of the implementations are discussed
relating to design, interaction, and tasks.
Excessive edge density in graphs can cause serious readability issues, which in turn can make the graphs difficult
to understand or even misleading. Recently, we introduced the idea of providing tools that offer interactive edge
bending as a method by which edge congestion can be disambiguated. We extend this direction, presenting a
new tool, Edge Plucking, which offers new interactive methods to clarify node-edge relationships. Edge Plucking
expands the number of situations in which interactive graph exploration tools can be used to address edge
congestion.
Although a number of theories and principles have been developed to guide the creation of visualizations, it is not always apparent how to apply the knowledge in these principles. We describe the application of perceptual and cognitive theories for the analysis of uncertainty visualizations. General principles from Bertin, Tufte, and Ware are outlined and then applied to the analysis of eight different uncertainty visualizations. The theories provided a useful framework for analysis of the methods, and provided insights into the strengths and weaknesses of various aspects of the visualizations.
Visual simulation can be efficiently performed using programmable graphics hardware. However, in utilizing hardware to maximize throughput, it is important not to constrain interactivity. We present a method of using the graphics hardware while maintaining full interactivity during simulation exploration. This interactivity involves: temporal exploration, data probing and modification, simulation model modification, and user defined visual metadata. Results are shown using our application for exploring a reaction-diffusion simulation.
Medical images are increasingly being examined on computer monitors. In contrast to the traditional film viewbox, the use of computer displays often involves a trade-off between the number and size of images shown and the available screen space. This paper focuses on two solutions to this problem: the thumbnail technique and the detail-in-context technique. The thumbnail technique, implemented in many current commercial medical imaging systems, presents an overview of the images in a thumbnail bar while selected images are magnified in a separate window. Our earlier work suggested the use of a detail-in-context technique which displays all images in one window utilizing multiple magnification levels. We conducted a controlled experiment to evaluate both techniques. No significant difference was found for performance and preference. However, differences were found in the interaction patterns and comments provided by the participants. The detail-in-context technique accommodated many individual strategies and offered good capabilities for comparing different images whereas the thumbnail technique strongly encouraged sequential examination of the images and allowed for high magnification factors. Given the results of this study, our research suggests new alternatives to the presentation of medical images and provides an increased understanding of the usability of existing medical image viewing methods.
This paper examines the presentation of MRI on a computer screen. In order to understand the issues involved with the diagnostic-viewing task performed by the radiologist, field observations were obtained in the traditional light screen environment. Requirement issues uncovered included: user control over grouping, size and position of images; navigation of imags and image groups; and provision of both presentation detail and presentation context. Existing presentation techniques and variations were explored in order to obtain an initial design direction to address these issues.
KEYWORDS: Visualization, Tin, Ions, Raster graphics, Information visualization, Monte Carlo methods, Visual analytics, Statistical analysis, Geographic information systems, Databases
This paper presents the creation of a visual environment for exploring landscape patterns and changes to such patterns over time. Dynamic landscape patterns can involve both spatial and temporal complexity. Exploration of spatio-temporal landscape patterns should provide the ability to view information at different scales to permit navigation of a vast amount of information in a manner that facilitates comprehension rather than confusion. One way of achieving this goal is to support selection, navigation and comparison of progressively refined segments of time and space. We have entitled this system Tardis after the time machine of Dr. Who, to emphasize the exploration of time dependent data and because our use of elastic presentation has the effect of providing more internal space than the external volume suggests. Of special concern in this research is the extent of the data and its inter- relationships that need to be understood over multiple scales, and the challenge inherent in implementing viewing methods to facilitate understanding.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.