242 research outputs found
Analysis of biomedical data with multilevel glyphs
BACKGROUND: This paper presents multilevel data glyphs optimized for the interactive knowledge discovery and visualization of large biomedical data sets. Data glyphs are three- dimensional objects defined by multiple levels of geometric descriptions (levels of detail) combined with a mapping of data attributes to graphical elements and methods, which specify their spatial position. METHODS: In the data mapping phase, which is done by a biomedical expert, meta information about the data attributes (scale, number of distinct values) are compared with the visual capabilities of the graphical elements in order to give a feedback to the user about the correctness of the variable mapping. The spatial arrangement of glyphs is done in a dimetric view, which leads to high data density, a simplified 3D navigation and avoids perspective distortion. RESULTS: We show the usage of data glyphs in the disease analyser a visual analytics application for personalized medicine and provide an outlook to a biomedical web visualization scenario. CONCLUSIONS: Data glyphs can be successfully applied in the disease analyser for the analysis of big medical data sets. Especially the automatic validation of the data mapping, selection of subgroups within histograms and the visual comparison of the value distributions were seen by experts as an important functionality
An Empirical Evaluation of Visual Cues for 3D Flow Field Perception
Three-dimensional vector fields are common datasets throughout the sciences. They often represent physical phenomena that are largely invisible to us in the real world, like wind patterns and ocean currents. Computer-aided visualization is a powerful tool that can represent data in any way we choose through digital graphics. Visualizing 3D vector fields is inherently difficult due to issues such as visual clutter, self-occlusion, and the difficulty of providing depth cues that adequately support the perception of flow direction in 3D space. Cutting planes are often used to overcome these issues by presenting slices of data that are more cognitively manageable. The existing literature provides many techniques for visualizing the flow through these cutting planes; however, there is a lack of empirical studies focused on the underlying perceptual cues that make popular techniques successful. The most valuable depth cue for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing, but none of these cues have been fully examined in the context of flow visualization. This dissertation presents a series of quantitative human factors studies that evaluate depth and direction cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The results of the studies are distilled into a set of design guidelines to improve the effectiveness of 3D flow field visualizations, and those guidelines are implemented as an immersive, interactive 3D flow visualization proof-of-concept application
Glyph visualization: A fail-safe design scheme based on quasi-hamming distances
© 1981-2012 IEEE. In many spatial and temporal visualization applications, glyphs provide an effective means for encoding multivariate data. However, because glyphs are typically small, they are vulnerable to various perceptual errors. This article introduces the concept of a quasi-Hamming distance in the context of glyph design and examines the feasibility of estimating the quasi-Hamming distance between a pair of glyphs and the minimal Hamming distance for a glyph set. The authors demonstrate the design concept by developing a file-system event visualization that can depict the activities of multiple users
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Glyphs for exploring crowd-sourced subjective survey classification
The findings drawn from opinion survey responses are usually made by producing summary charts or conducting statistical analysis. Both involve data aggregation and filtering as exploring the unaggregated data has traditionally been impractical or error-prone for large numbers of responses. We propose the use of glyphs with parallel coordinate plots to show all survey responses in a single view and design an interactive visual analytics tool around the representation to explore the data. We use this software for a ‘photo content assessment’ survey, where 359 participants classify 900 images by seven criteria. The proposed approach allows all 8,434 responses (49,285 answers to questions in total) to be represented in a single view and helps analysts to both clean the data and understand the nature of the survey responses. We describe the construction of the survey response glyphs and the interface to the interactive visual analytics software and generalise the design principles that arise from the approach. We apply the tool to two other datasets to evaluate the technique and to confirm its wider applicability for surveys with Likert scale responses
Inviwo -- A Visualization System with Usage Abstraction Levels
The complexity of today's visualization applications demands specific
visualization systems tailored for the development of these applications.
Frequently, such systems utilize levels of abstraction to improve the
application development process, for instance by providing a data flow network
editor. Unfortunately, these abstractions result in several issues, which need
to be circumvented through an abstraction-centered system design. Often, a high
level of abstraction hides low level details, which makes it difficult to
directly access the underlying computing platform, which would be important to
achieve an optimal performance. Therefore, we propose a layer structure
developed for modern and sustainable visualization systems allowing developers
to interact with all contained abstraction levels. We refer to this interaction
capabilities as usage abstraction levels, since we target application
developers with various levels of experience. We formulate the requirements for
such a system, derive the desired architecture, and present how the concepts
have been exemplary realized within the Inviwo visualization system.
Furthermore, we address several specific challenges that arise during the
realization of such a layered architecture, such as communication between
different computing platforms, performance centered encapsulation, as well as
layer-independent development by supporting cross layer documentation and
debugging capabilities
Design Patterns for Situated Visualization in Augmented Reality
Situated visualization has become an increasingly popular research area in
the visualization community, fueled by advancements in augmented reality (AR)
technology and immersive analytics. Visualizing data in spatial proximity to
their physical referents affords new design opportunities and considerations
not present in traditional visualization, which researchers are now beginning
to explore. However, the AR research community has an extensive history of
designing graphics that are displayed in highly physical contexts. In this
work, we leverage the richness of AR research and apply it to situated
visualization. We derive design patterns which summarize common approaches of
visualizing data in situ. The design patterns are based on a survey of 293
papers published in the AR and visualization communities, as well as our own
expertise. We discuss design dimensions that help to describe both our patterns
and previous work in the literature. This discussion is accompanied by several
guidelines which explain how to apply the patterns given the constraints
imposed by the real world. We conclude by discussing future research directions
that will help establish a complete understanding of the design of situated
visualization, including the role of interactivity, tasks, and workflows.Comment: To appear in IEEE VIS 202
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