Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. IncreasingLy, information visuaLization tools support such comparisons explicitLy, beyond simply aLLowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we see that all designs are assembled from the building blocks of juxtaposition, superposition and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a generaL understanding of comparative visualization and faciLitating the development of more comparative visualization tools.

Visual comparison for information visualization

Visualization can provide valuable assistance for data analysis and decision making tasks. However, how people perceive and interact with a visualization tool can strongly influence their understanding of the data as well as the system's usefulness. Human factors therefore contribute significantly to the visualization process and should play an important role in the design and evaluation of visualization tools. Several research initiatives have begun to explore human factors in visualization, particularly in perception-based design. Nonetheless, visualization work involving human factors is in its infancy, and many potentially promising areas have yet to be explored. Therefore, we aim to 1) review known methodology for doing human factors research, with specific emphasis on visualization, 2) review current human factors research in visualization to provide a basis for future investigation, and 3) identify promising areas for future research.

Human factors in visualization research

Tensor field visualization is a challenging task due in part to the multi-variate nature of individual tensor samples. Glyphs convey tensor variables by mapping the tensor eigenvectors and eigenvalues to the orientation and shape of a geometric primitive, such as a cuboid or ellipsoid. Though widespread, cuboids and ellipsoids have problems of asymmetry and visual ambiguity. Cuboids can display misleading orientation for tensors with underlying rotational symmetry. Ellipsoids differing in shape can be confused, from certain viewpoints, because of similarities in profile and shading. This paper addresses the problems of asymmetry and ambiguity with a new tunable continuum of glyphs based on superquadric surfaces. Superquadric tensor glyphs enjoy the necessary symmetry properties of ellipsoids, while also imitating cuboids and cylinders to better convey shape and orientation, where appropriate. The new glyphs are demonstrated on fields of diffusion tensors from the human brain.

Superquadric tensor glyphs

Volume rendered imagery often includes a barrage of 3D information like shape, appearance and topology of complex structures, and it thus quickly overwhelms the user. In particular, when focusing on a specific region a user cannot observe the relationship between various structures unless he has a mental picture of the entire data. In this paper we present ClearView, a GPU-based, interactive framework for texture-based volume ray-casting that allows users which do not have the visualization skills for this mental exercise to quickly obtain a picture of the data in a very intuitive and user-friendly way. ClearView is designed to enable the user to focus on particular areas in the data while preserving context information without visual clutter. ClearView does not require additional feature volumes as it derives any features in the data from image information only. A simple point-and-click interface enables the user to interactively highlight structures in the data. ClearView provides an easy to use interface to complex volumetric data as it only uses transparency in combination with a few specific shaders to convey focus and context information

ClearView: An Interactive Context Preserving Hotspot Visualization Technique

We systematically reviewed 64 user-study papers on data glyphs to help researchers and practitioners gain an informed understanding of tradeoffs in the glyph design space. The glyphs we consider are individual representations of multi-dimensional data points, often meant to be shown in small-multiple settings. Over the past 60 years many different glyph designs were proposed and many of these designs have been subjected to perceptual or comparative evaluations. Yet, a systematic overview of the types of glyphs and design variations tested, the tasks under which they were analyzed, or even the study goals and results does not yet exist. In this paper we provide such an overview by systematically sampling and tabulating the literature on data glyph studies, listing their designs, questions, data, and tasks. In addition we present a concise overview of the types of glyphs and their design characteristics analyzed by researchers in the past, and a synthesis of the study results. Based on our meta analysis of all results we further contribute a set of design implications and a discussion on open research directions.

/pdf/a-systematic-review-of-experimental-studies-on-data-glyphs-54tjux1qwt.pdf

A Systematic Review of Experimental Studies on Data Glyphs

This paper describes our recent findings in the area of using glyph shape to display one or two data dimensions in the visualization of 3D scalar and vector fields In our glyph-based visualization system, each glyph represents a data point in 3D space Visual attributes such as size, orientation, color and transparency can be mapped to data dimensions in the 3D space We are exploring the use of glyph shape as a display dimension, using superquadric superellipses as a means of supplying a parameterizable shape A basic factor in effectively using shape for quantitative visualization is determining how many (and which) superellipse shapes people can distinguish Since the superquadric shape's parameter set is not perceptually linear, we conducted a user study to which shapes people can generally distinguish The findings show that with large superellipses, about 22 separate shapes can be distinguished on average These results provide the foundation for exploring how effective superellipses may be in quantitative shape visualization

/pdf/using-shape-to-visualize-multivariate-data-2c1ua9mubr.pdf

Using shape to visualize multivariate data

This paper describes new techniques for minimally immersive visualization of 3D scalar and vector fields, and visualization of document corpora. In our glyph-based visualization system, the user interacts with the 3D volume of glyphs using a pair of button-enhanced 3D position and orientation trackers. The user may also examine the volume using an interactive lens, which is a rectangle that slices through the 3D volume and displays scalar information on its surface. A lens allows the display of scalar data in the 3D volume using a contour diagram, and a texture-based volume rendering.

Interactive lens visualization techniques

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Using shape to visualize multivariate data

Interactive lens visualization techniques