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Explorative Analysis of 2D Color Maps

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Explorative Analysis of 2D Color Maps WSCG 2015 Conference on Computer Graphics, Visualization and Computer Vision Explorative Analysis of 2D Color Maps M. Steiger*, J. Bernard*, S. Thum*, S. Mittelstädt†, M. Hutter*, D. Keim†, J. Kohlhammer* Fraunhofer IGD, Darmstadt*, University of Konstanz†, Germany ABSTRACT Color is one of the most important visual variables in information visualization. In many cases, two-dimensional information can be color-coded based on a 2D color map. A variety of color maps as well as a number of quality criteria for the use of color have been presented. The choice of the best color map depends on the analytical task users intend to perform and the design space in choosing an appropriate 2D color map is large. In this paper, we present the ColorMap-Explorer, a visual-interactive system that helps users in selecting the most appropriate 2D color map for their particular use case. ColorMap-Explorer also provides a library of many color map im- plementations that have been proposed in the scientific literature. To analyze their usefulness for different tasks, ColorMap-Explorer provides use case scenarios to allow users to obtain qualitative feedback. In addition, quan- titative metrics are provided on a global (i.e. per color map) and local (i.e. per point) scale. ColorMap-Explorer enables users to explore the strengths and weaknesses of existing as well as user-provided color maps to find the best fit for their task. Any color map can be exported to be reused in other visualization tools. The code is published as open source software, so that the visualization community can use both the color map library and the ColorMap-Explorer tool. This also allows users to contribute new implementations. Keywords explorative analysis, color maps 1 INTRODUCTION As a result, the viewer can estimate the relative similarity of high-dimensional data by comparing Color is one of the most important visual variables colors. As such, 2D color maps are appropriate for in information visualization. Depending on the prop- high-dimensional data; we do not recommend the erties of the underlying data, different types of color direct use of two data attributes as coordinates in the maps can be applied to encode data attributes visually map (cf. Wainer et al. [WF80]). in the most accurate way. Qualitative color maps al- low for the distinction between different categories of A variety of different static 2D color maps has been pre- elements. Quantitative color maps allow for an identi- sented in the past. The survey of Bernard et al. gives an fication of similar (and dissimilar) data elements with overview [BSM∗15]. The authors review quality crite- respect to a quantitative value domain. For quantita- ria and design guidelines for color maps and depict the tive color maps, the most relevant representatives are huge design space for the design and the use of static either sequential (unipolar) or diverging (bipolar). In 2D color maps. those cases where a single data variable (attribute) is encoded, a one-dimensional color ramp can be used. In order to faithfully reflect the relative pair-wise dis- tances of the original data as closely as possible, such For high-dimensional data, 2D color maps are used a 2D color map should preserve the notion of perceived to preserve similarity of the items in a visual vari- similarity in terms of color. The perceived distance be- able. Data items with more than two attributes are first tween colors should be linearly related to the geometric mapped into the two-dimensional space according to distance in both the high- and the 2-dimensional space. some transformation or projection method. The result Another quality criterion for a color map is to exploit of these upstream techniques is a mapping in 2D that the given color space, aiming for a maximum number can directly be used as position information in a 2D of distinguishable colors. In many cases the choice of color map. color maps is also made with respect to colorblindness sensitivity. For example, about 8-10 percent of the male population in Europe suffer from a color vision defi- Permission to make digital or hard copies of all or part of ciency [Alb10]. Additional requirements to color maps this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit may be based on user-centered constraints like corpo- or commercial advantage and that copies bear this notice and rate designs. In some cases, 2D color maps may also the full citation on the first page. To copy otherwise, or re- require a certain contrast against the background color publish, to post on servers or to redistribute to lists, requires so that the visual elements can be clearly identified as prior specific permission and/or a fee. such. Some other visualizations may require that text Full Papers Proceedings 151 ISBN 978-80-86943-65-7 WSCG 2015 Conference on Computer Graphics, Visualization and Computer Vision and other overlays are legible on a canvas that is drawn downstream visualization, several views stress the color based on the color map. map against other visual variables in different example A taxonomy of different color map design criteria is scenarios. Finally, the selected color map can be ex- presented by Tominski et al. [TFS08]. According to the ported for re-use in downstream visualization tools. authors, meaningful color encodings strongly depend on the data, the task, the target user group, and the dis- play device. A fourth dimension in the problem space is the large number of static 2D color maps presented in literature. Naturally, there is no color map that is perfect with respect to all requirements. To give an ex- ample, a color map can hardly be colorblind-safe and maximize color exploitation at the same time. Visual- ization designers need to balance a trade-off between different complementary design criteria. A premature color map decision may lead to false assumptions with respect to the underlying data properties. Consequently, Figure 1: The main window of the ColorMap-Explorer: choosing a 2D color map for a visualization should be the config and info panel is placed on left side, the col- done carefully. lection of views is stored in individual tabs at the right. The Overview tab enumerates all available color maps. To the best of our knowledge, a decision support sys- tem that supports the user in making such a choice has The workflow of the ColorMap-Explorer is as follows: not yet been presented. We identify the following chal- starting with an overview of all color map implementa- lenges: tions, the user can select up to three color maps which then are put in juxtaposition. This allows for direct • R1:Visual overview of existing color maps comparison to narrow down the number of candidates with respect to the analytical task. Individual color • R2:Comparison of color maps with respect to global quantitative quality measures maps are then investigated in more detail before the best fit is identified. When the decision on the best • R3:Assessment of local properties of a color map matching color map has been made, the user can save • R4:Visual analysis of the shape of a color map with the color map as an image to disk. The user can respect to different color spaces. always move backwards and forwards in this workflow pipeline as desired. • R5:Assessment of the maximum amount of dis- cernible information that can be encoded The paper is organized as follows: In Section 2, we • R :Showing the homogeneity of perceived similarity discuss related software tools that support the user in 6 finding colors for visualization tasks. Section 3 gives • R7:Assessment of the interplay of color map with a definition of perceived color differences, before the other visual variables ColorMap-Explorer is illustrated in detail in Section 4. We show some discoveries along an example applica- We present the ColorMap-Explorer, a visual-interactive tion in Section 5. Conclusion and outlook are at the end decision support system for 2D color maps. The system of the paper in Section 6. assists visualization designers to find the best-fitting color map in this complex search space. At the mo- 2 RELATED WORK ment, it contains 22 color map implementations that were discussed in the scientific literature. Visual access Appropriate color maps for specific tasks and specific to these 2D color maps is provided in an overview visu- data properties is a well discussed topic in the litera- alization. For every color map, quantitative metrics are ture. General guidelines on selecting color maps can provided on a global (i.e. per color map) and local (i.e. be found in [RO86,War88,RTB96,Rhe00]. In addition, per point) scale. For the comparison of multiple color linear color ranges (1D) for segmentation and categori- maps, we provide a view utilizing the global measures. cal data have been discussed previously [Hea96,HB03]. A detailed analysis of local properties is provided by For two-dimensional color maps there are few guide- several views, each shedding light from a different per- lines available. The study of Wainer et al. [WF80] spective. In particular, we allow for the detailed anal- showed that encoding of two dimensional data with two ysis of a) different color channels b) local perceptual dimensional color maps is not intelligible. In contrast linearity, and c) the shape of the area in different color to this statement, Ware and Beatty [WB88] found that spaces for every color map. In order to get a first im- each additional color dimension (red, green, blue chan- pression of how the color map behaves in a targeted nel) is as effective as an additional spatial dimension Full Papers Proceedings 152 ISBN 978-80-86943-65-7 WSCG 2015 Conference on Computer Graphics, Visualization and Computer Vision in the encoding of multivariate (more than two dimen- obtained a color difference formula and different sional) data.
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