618 research outputs found
A Testing Environment for Continuous Colormaps
Many computer science disciplines (e.g., combinatorial optimization, natural
language processing, and information retrieval) use standard or established
test suites for evaluating algorithms. In visualization, similar approaches
have been adopted in some areas (e.g., volume visualization), while user
testimonies and empirical studies have been the dominant means of evaluation in
most other areas, such as designing colormaps. In this paper, we propose to
establish a test suite for evaluating the design of colormaps. With such a
suite, the users can observe the effects when different continuous colormaps
are applied to planar scalar fields that may exhibit various characteristic
features, such as jumps, local extrema, ridge or valley lines, different
distributions of scalar values, different gradients, different signal
frequencies, different levels of noise, and so on. The suite also includes an
expansible collection of real-world data sets including the most popular data
for colormap testing in the visualization literature. The test suite has been
integrated into a web-based application for creating continuous colormaps
(https://ccctool.com/), facilitating close inter-operation between design and
evaluation processes. This new facility complements traditional evaluation
methods such as user testimonies and empirical studies
Data Painter: A Tool for Colormap Interaction
The choice of a mapping from data to color should involve careful consideration in order to maximize the user understanding of the underlying data. It is desirable for features within the data to be visually separable and identifiable. Current practice involves selecting a mapping from predefined colormaps or coding specific colormaps using software such as MATLAB. The purposes of this paper are to introduce interactive operations for colormaps that enable users to create more visually distinguishable pixel based visualizations, and to describe our tool, Data Painter, that provides a fast, easy to use framework for defining these color mappings. We demonstrate the use of the tool to create colormaps for various application areas and compare to existing color mapping methods. We present a new objective measure to evaluate their efficacy
Graphical Perception of Continuous Quantitative Maps: the Effects of Spatial Frequency and Colormap Design
Continuous 'pseudocolor' maps visualize how a quantitative attribute varies smoothly over space. These maps are widely used by experts and lay citizens alike for communicating scientific and geographical data. A critical challenge for designers of these maps is selecting a color scheme that is both effective and aesthetically pleasing. Although there exist empirically grounded guidelines for color choice in segmented maps (e.g., choropleths), continuous maps are significantly understudied, and their color-coding guidelines are largely based on expert opinion and design heuristics--many of these guidelines have yet to be verified experimentally. We conducted a series of crowdsourced experiments to investigate how the perception of continuous maps is affected by colormap characteristics and spatial frequency (a measure of data complexity). We find that spatial frequency significantly impacts the effectiveness of color encodes, but the precise effect is task-dependent. While rainbow schemes afforded the highest accuracy in quantity estimation irrespective of spatial complexity, divergent colormaps significantly outperformed other schemes in tasks requiring the perception of high-frequency patterns. We interpret these results in relation to current practices and devise new and more granular guidelines for color mapping in continuous maps
Web-Based Visualization of Very Large Scientific Astronomy Imagery
Visualizing and navigating through large astronomy images from a remote
location with current astronomy display tools can be a frustrating experience
in terms of speed and ergonomics, especially on mobile devices. In this paper,
we present a high performance, versatile and robust client-server system for
remote visualization and analysis of extremely large scientific images.
Applications of this work include survey image quality control, interactive
data query and exploration, citizen science, as well as public outreach. The
proposed software is entirely open source and is designed to be generic and
applicable to a variety of datasets. It provides access to floating point data
at terabyte scales, with the ability to precisely adjust image settings in
real-time. The proposed clients are light-weight, platform-independent web
applications built on standard HTML5 web technologies and compatible with both
touch and mouse-based devices. We put the system to the test and assess the
performance of the system and show that a single server can comfortably handle
more than a hundred simultaneous users accessing full precision 32 bit
astronomy data.Comment: Published in Astronomy & Computing. IIPImage server available from
http://iipimage.sourceforge.net . Visiomatic code and demos available from
http://www.visiomatic.org
Categorical colormap optimization with visualization case studies
Mapping a set of categorical values to different colors is an elementary technique in data visualization. Users of visualization software routinely rely on the default colormaps provided by a system, or colormaps suggested by software such as ColorBrewer.
In practice, users often have to select a set of colors in a semantically meaningful way (e.g., based on conventions, color metaphors,
and logological associations), and consequently would like to ensure their perceptual differentiation is optimized. In this paper, we
present an algorithmic approach for maximizing the perceptual distances among a set of given colors. We address two technical problems in optimization, i.e., (i) the phenomena of local maxima that halt the optimization too soon, and (ii) the arbitrary reassignment
of colors that leads to the loss of the original semantic association. We paid particular attention to different types of constraints that
users may wish to impose during the optimization process. To demonstrate the effectiveness of this work, we tested this technique in
two case studies. To reach out to a wider range of users, we also developed a web application called Colourmap Hospital
Categorical Colormap Optimization with Visualization Case Studies
—Mapping a set of categorical values to different colors is an elementary technique in data visualization. Users of visualization software routinely rely on the default colormaps provided by a system, or colormaps suggested by software such as ColorBrewer. In practice, users often have to select a set of colors in a semantically meaningful way (e.g., based on conventions, color metaphors, and logological associations), and consequently would like to ensure their perceptual differentiation is optimized. In this paper, we present an algorithmic approach for maximizing the perceptual distances among a set of given colors. We address two technical problems in optimization, i.e., (i) the phenomena of local maxima that halt the optimization too soon, and (ii) the arbitrary reassignment of colors that leads to the loss of the original semantic association. We paid particular attention to different types of constraints that users may wish to impose during the optimization process. To demonstrate the effectiveness of this work, we tested this technique in two case studies. To reach out to a wider range of users, we also developed a web application called Colourmap Hospital
Color Maker: a Mixed-Initiative Approach to Creating Accessible Color Maps
Quantitative data is frequently represented using color, yet designing
effective color mappings is a challenging task, requiring one to balance
perceptual standards with personal color preference. Current design tools
either overwhelm novices with complexity or offer limited customization
options. We present ColorMaker, a mixed-initiative approach for creating
colormaps. ColorMaker combines fluid user interaction with real-time
optimization to generate smooth, continuous color ramps. Users specify their
loose color preferences while leaving the algorithm to generate precise color
sequences, meeting both designer needs and established guidelines. ColorMaker
can create new colormaps, including designs accessible for people with
color-vision deficiencies, starting from scratch or with only partial input,
thus supporting ideation and iterative refinement. We show that our approach
can generate designs with similar or superior perceptual characteristics to
standard colormaps. A user study demonstrates how designers of varying skill
levels can use this tool to create custom, high-quality colormaps. ColorMaker
is available at https://colormaker.orgComment: To appear at the ACM CHI '24 Conference on Human Factors in Computing
System
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