Colormaps for Shaded Surfaces: Stepped vs Smooth.

It is common in scientific visualization for one 2D scalar field variable to be colormapped and draped onto a shaded surface representing a second variable displayed as a height field. The experiments reported here investigate the properties that make a colormap suitable for this application; specifically, how much colormap accuracy is lost because of draping and shading as well as the degree to which the colormap impacts the perception of surface shape. A new task is used to evaluate surface shape perception; it involves study participants clicking on the peaks of hills and the bottoms of valleys in the display. The results provided surprisingly little support for the hypothesis that colormaps varying greatly in luminance impacted surface shape perception more than those that are close to isoluminant. Stepped colormaps proved to be more accurately read. However, stepped colormaps also interfered much more with the perception of surface shape. The implication of these results are that when selecting a colormap to be used for draping, careful consideration should be given to which of the two variables is more important, the one represented by the shaded surface, or the one which is colormapped and draped. All replication and reproducibility material is available at http://osf.io/4huqy.

Deep dives and high tissue density increase mean dive costs in California sea lions (Zalophus californianus).

Diving is central to the foraging strategies of many marine mammals and seabirds. Still, the effect of dive depth on foraging cost remains elusive because energy expenditure is difficult to measure at fine temporal scales in wild animals. We used depth and acceleration data from eight lactating California sea lions (Zalophus californianus) to model body density and investigate the effect of dive depth and tissue density on rates of energy expenditure. We calculated body density in 5 s intervals from the rate of gliding descent. We modeled body density across depth in each dive, revealing high tissue densities and diving lung volumes (DLVs). DLV increased with dive depth in four individuals. We used the buoyancy calculated from dive-specific body-density models and drag calculated from swim speed to estimate metabolic power and cost of transport in 5 s intervals during descents and ascents. Deeper dives required greater mean power for round-trip vertical transit, especially in individuals with higher tissue density. These trends likely follow from increased mean swim speed and buoyant hinderance that increasingly outweighs buoyant aid in deeper dives. This suggests that deep diving is either a 'high-cost, high-reward' strategy or an energetically expensive option to access prey when prey in shallow waters are limited, and that poor body condition may increase the energetic costs of deep diving. These results add to our mechanistic understanding of how foraging strategy and body condition affect energy expenditure in wild breath-hold divers.

Rainbow Colormaps Are Not All Bad.

Some 15 years ago, Visualization Viewpoints published an influential article titled Rainbow Color Map (Still) Considered Harmful (Borland and Taylor, 2007). The paper argued that the "rainbow colormap's characteristics of confusing the viewer, obscuring the data and actively misleading interpretation make it a poor choice for visualization." Subsequent articles often repeat and extend these arguments, so much so that avoiding rainbow colormaps, along with their derivatives, has become dogma in the visualization community. Despite this loud and persistent recommendation, scientists continue to use rainbow colormaps. Have we failed to communicate our message, or do rainbow colormaps offer advantages that have not been fully appreciated? We argue that rainbow colormaps have properties that are underappreciated by existing design conventions. We explore key critiques of the rainbow in the context of recent research to understand where and how rainbows might be misunderstood. Choosing a colormap is a complex task, and rainbow colormaps can be useful for selected applications.

2022 VGTC Visualization Lifetime Achievement Award.

Presents the recipient of the 2022 VGTC Visualization Lifetime Achievement Award.

Measuring and Modeling the Feature Detection Threshold Functions of Colormaps.

Pseudocoloring is one of the most common techniques used in scientific visualization. To apply pseudocoloring to a scalar field, the field value at each point is represented using one of a sequence of colors (called a colormap). One of the principles applied in generating colormaps is uniformity and previously the main method for determining uniformity has been the application of uniform color spaces. In this paper we present a new method for evaluating the feature detection threshold function across a colormap. The method is used in crowdsourced studies for the direct evaluation of nine colormaps for three feature sizes. The results are used to test the hypothesis that a uniform color space (CIELAB) will accurately model colormapped feature detection thresholds compared to a model where the chromaticity components have reduced weights. The hypothesis that feature detection can be predicted solely on the basis of luminance is also tested. The results reject both hypotheses and we demonstrate how reduced weights on the green-red and blue-yellow terms of the CIELAB color space creates a more accurate model when the task is the detection of smaller features in colormapped data. Both the method itself and modified CIELAB can be used in colormap design and evaluation.

The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps.

A myriad of design rules for what constitutes a "good" colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation. In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.

Hairy Slices: Evaluating the Perceptual Effectiveness of Cutting Plane Glyphs for 3D Vector Fields.

Three-dimensional vector fields are common datasets throughout the sciences. Visualizing these fields is inherently difficult due to issues such as visual clutter and self-occlusion. Cutting planes are often used to overcome these issues by presenting more manageable slices of data. 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. This paper presents a quantitative human factors study that evaluates static monoscopic depth and orientation cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The goal of the study was to ascertain the relative effectiveness of various techniques for portraying the direction of flow through a cutting plane at a given point, and to identify the visual cues and combinations of cues involved, and how they contribute to accurate performance. It was found that increasing the dimensionality of line-based glyphs into tubular structures enhances their ability to convey orientation through shading, and that increasing their diameter intensifies this effect. These tube-based glyphs were also less sensitive to visual clutter issues at higher densities. Adding shadows to lines was also found to increase perception of flow direction. Implications of the experimental results are discussed and extrapolated into a number of guidelines for designing more perceptually effective glyphs for 3D vector field visualizations.

Averaged Propulsive Body Acceleration (APBA) Can Be Calculated from Biologging Tags That Incorporate Gyroscopes and Accelerometers to Estimate Swimming Speed, Hydrodynamic Drag and Energy Expenditure for Steller Sea Lions.

Forces due to propulsion should approximate forces due to hydrodynamic drag for animals horizontally swimming at a constant speed with negligible buoyancy forces. Propulsive forces should also correlate with energy expenditures associated with locomotion-an important cost of foraging. As such, biologging tags containing accelerometers are being used to generate proxies for animal energy expenditures despite being unable to distinguish rotational movements from linear movements. However, recent miniaturizations of gyroscopes offer the possibility of resolving this shortcoming and obtaining better estimates of body accelerations of swimming animals. We derived accelerations using gyroscope data for swimming Steller sea lions (Eumetopias jubatus), and determined how well the measured accelerations correlated with actual swimming speeds and with theoretical drag. We also compared dive averaged dynamic body acceleration estimates that incorporate gyroscope data, with the widely used Overall Dynamic Body Acceleration (ODBA) metric, which does not use gyroscope data. Four Steller sea lions equipped with biologging tags were trained to swim alongside a boat cruising at steady speeds in the range of 4 to 10 kph. At each speed, and for each dive, we computed a measure called Gyro-Informed Dynamic Acceleration (GIDA) using a method incorporating gyroscope data with accelerometer data. We derived a new metric-Averaged Propulsive Body Acceleration (APBA), which is the average gain in speed per flipper stroke divided by mean stroke cycle duration. Our results show that the gyro-based measure (APBA) is a better predictor of speed than ODBA. We also found that APBA can estimate average thrust production during a single stroke-glide cycle, and can be used to estimate energy expended during swimming. The gyroscope-derived methods we describe should be generally applicable in swimming animals where propulsive accelerations can be clearly identified in the signal-and they should also prove useful for dead-reckoning and improving estimates of energy expenditures from locomotion.

Representing flow patterns by using streamlines with glyphs.

Most professional wind visualizations show wind speed and direction using a glyph called a wind barb in a grid pattern. Research into flow visualization has suggested that streamlines better represent flow patterns but these methods lack a key property-unlike the wind barb, they do not accurately convey the wind speed. With the goal of improving the perception of wind patterns, and at least equaling the quantitative quality of wind barbs, we designed two variations on the wind barb and designed a new quantitative glyph. All of our new designs space glyph elements along equally spaced streamlines. To evaluate these designs, we used a North American mesoscale forecast model. We tested the ability of subjects to determine direction and speed using two different densities each of three new designs as well as the classic wind barb. A second experiment evaluated how effectively each of the designs represented wind patterns. The results showed that the new design is superior to the classic, but they also showed that the classic barb can be redesigned and substantially improved. We suggest that flow patterns with integrated glyphs may have widespread application in flow visualization.

Data visualization optimization via computational modeling of perception.

We present a method for automatically evaluating and optimizing visualizations using a computational model of human vision. The method relies on a neural network simulation of early perceptual processing in the retina and primary visual cortex. The neural activity resulting from viewing flow visualizations is simulated and evaluated to produce a metric of visualization effectiveness. Visualization optimization is achieved by applying this effectiveness metric as the utility function in a hill-climbing algorithm. We apply this method to the evaluation and optimization of 2D flow visualizations, using two visualization parameterizations: streaklet-based and pixel-based. An emergent property of the streaklet-based optimization is head-to-tail streaklet alignment. It had been previously hypothesized the effectiveness of head-to-tail alignment results from the perceptual processing of the visual system, but this theory had not been computationally modeled. A second optimization using a pixel-based parameterization resulted in a LIC-like result. The implications in terms of the selection of primitives is discussed. We argue that computational models can be used for optimizing complex visualizations. In addition, we argue that they can provide a means of computationally evaluating perceptual theories of visualization, and as a method for quality control of display methods.

Target finding with a spatially aware handheld chart display.

OBJECTIVE: The objective was to evaluate the use of a spatially aware handheld chart display in a comparison with a track-up fixed display configuration and to investigate how cognitive strategies vary when performing the task of matching chart symbols with environmental features under different display geometries and task constraints. BACKGROUND: Small-screen devices containing both accelerometers and magnetometers support the development of spatially aware handheld maps.These can be designed so that symbols representing targets in the external world appear in a perspective view determined by the orientation of the device. METHOD: A panoramic display was used to simulate a marine environment. The task involved matching targets in the scene to symbols on simulated chart displays. In Experiment I, a spatially aware handheld chart display was compared to a fixed track-up chart display. In Experiment 2, a gaze monitoring system was added and the distance between the chart display and the scene viewpoint was varied. RESULTS: All respondents were faster with the handheld device. Novices were much more accurate with the handheld device. People allocated their gaze very differently if they had to move between a map display and a view of the environment. CONCLUSION: There may be important benefits to spatially aware handheld displays in reducing errors relating to common navigation tasks. APPLICATION: Both the difficulty of spatial transformations and the allocation of attention should be considered in the design of chart displays.

Quantitative texton sequences for legible bivariate maps.

Representing bivariate scalar maps is a common but difficult visualization problem. One solution has been to use two dimensional color schemes, but the results are often hard to interpret and inaccurately read. An alternative is to use a color sequence for one variable and a texture sequence for another. This has been used, for example, in geology, but much less studied than the two dimensional color scheme, although theory suggests that it should lead to easier perceptual separation of information relating to the two variables. To make a texture sequence more clearly readable the concept of the quantitative texton sequence (QTonS) is introduced. A QTonS is defined a sequence of small graphical elements, called textons, where each texton represents a different numerical value and sets of textons can be densely displayed to produce visually differentiable textures. An experiment was carried out to compare two bivariate color coding schemes with two schemes using QTonS for one bivariate map component and a color sequence for the other. Two different key designs were investigated (a key being a sequence of colors or textures used in obtaining quantitative values from a map). The first design used two separate keys, one for each dimension, in order to measure how accurately subjects could independently estimate the underlying scalar variables. The second key design was two dimensional and intended to measure the overall integral accuracy that could be obtained. The results show that the accuracy is substantially higher for the QTonS/color sequence schemes. A hypothesis that texture/color sequence combinations are better for independent judgments of mapped quantities was supported. A second experiment probed the limits of spatial resolution for QTonSs.

Texturing of layered surfaces for optimal viewing.

This paper is a contribution to the literature on perceptually optimal visualizations of layered three-dimensional surfaces. Specifically, we develop guidelines for generating texture patterns, which, when tiled on two overlapped surfaces, minimize confusion in depth-discrimination and maximize the ability to localize distinct features. We design a parameterized texture space and explore this texture space using a "human in the loop" experimental approach. Subjects are asked to rate their ability to identify Gaussian bumps on both upper and lower surfaces of noisy terrain fields. Their ratings direct a genetic algorithm, which selectively searches the texture parameter space to find fruitful areas. Data collected from these experiments are analyzed to determine what combinations of parameters work well and to develop texture generation guidelines. Data analysis methods include ANOVA, linear discriminant analysis, decision trees, and parallel coordinates. To confirm the guidelines, we conduct a post-analysis experiment, where subjects rate textures following our guidelines against textures violating the guidelines. Across all subjects, textures following the guidelines consistently produce high rated textures on an absolute scale, and are rated higher than those that did not follow the guidelines.

An approach to the perceptual optimization of complex visualizations.

This paper proposes a new experimental framework within which evidence regarding the perceptual characteristics of a visualization method can be collected, and describes how this evidence can be explored to discover principles and insights to guide the design of perceptually near-optimal visualizations. We make the case that each of the current approaches for evaluating visualizations is limited in what it can tell us about optimal tuning and visual design. We go on to argue that our new approach is better suited to optimizing the kinds of complex visual displays that are commonly created in visualization. Our method uses human-in-the-loop experiments to selectively search through the parameter space of a visualization method, generating large databases of rated visualization solutions. Data mining is then used to extract results from the database, ranging from highly specific exemplar visualizations for a particular data set, to more broadly applicable guidelines for visualization design. We illustrate our approach using a recent study of optimal texturing for layered surfaces viewed in stereo and in motion. We show that a genetic algorithm is a valuable way of guiding the human-in-the-loop search through visualization parameter space. We also demonstrate several useful data mining methods including clustering, principal component analysis, neural networks, and statistical comparisons of functions of parameters.