Session:「Perception in Visualization 1」

Animated Edge Textures in Node-Link Diagrams: a Design Space and Initial Evaluation

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173761

論文アブストラクト: Network edge data attributes are usually encoded using color, opacity, stroke thickness and stroke pattern, or some combination thereof. In addition to these static variables, it is also possible to animate dynamic particles flowing along the edges. This opens a larger design space of animated edge textures, featuring additional visual encodings that have potential not only in terms of visual mapping capacity but also playfulness and aesthetics. Such animated edge textures have been used in several commercial and design-oriented visualizations, but to our knowledge almost always in a relatively ad hoc manner. We introduce a design space and Web-based framework for generating animated edge textures, and report on an initial evaluation of particle properties - particle speed, pattern and frequency - in terms of visual perception.

日本語のまとめ:

ノードとエッジで構成されるデータの可視化において,エッジに沿って粒子が移動するアニメーションテクスチャの活用を議論した.テクスチャの属性(頻度,スピード,パターン)のうち,パターンの違いがテクスチャの違いの識別に有効であることが示された.

Graphical Perception of Continuous Quantitative Maps: the Effects of Spatial Frequency and Colormap Design

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173846

論文アブストラクト: 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 understudies, 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.

日本語のまとめ:

地理データの可視化における空間周波数とカラーマッピングの影響を調査した.数量の判断,階調の知覚,パターンの知覚に関する3種類の実験を通して,空間周波数に関わらず色相の変化量を最大化すべき,といった指針を示した.

Somewhere Over the Rainbow: An Empirical Assessment of Quantitative Colormaps

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174172

論文アブストラクト: An essential goal of quantitative color encoding is the accurate mapping of perceptual dimensions of color to the logical structure of data. Prior research identifies weaknesses of 'rainbow' colormaps and advocates for ramping in luminance, while recent work contributes multi-hue colormaps generated using perceptually-uniform color models. We contribute a comparative analysis of different colormap types, with a focus on comparing single- and multi-hue schemes. We present a suite of experiments in which subjects perform relative distance judgments among color triplets drawn systematically from each of four single-hue and five multi-hue colormaps. We characterize speed and accuracy across each colormap, and identify conditions that degrade performance. We also find that a combination of perceptual color space and color naming measures more accurately predict user performance than either alone, though the overall accuracy is poor. Based on these results, we distill recommendations on how to design more effective color encodings for scalar data.

日本語のまとめ:

スカラー値の可視化における最適なカラーマッピングを調査.提示された2色の刺激のうち基準刺激に近い色を選択するタスクを通して,選択所要時間とエラー率を検討した.その結果,複数の色相を用いた均等色空間にもとづくマッピングが有効,といった指針を示した.

Value-Suppressing Uncertainty Palettes

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174216

論文アブストラクト: Understanding uncertainty is critical for many analytical tasks. One common approach is to encode data values and uncertainty values independently, using two visual variables. These resulting bivariate maps can be difficult to interpret, and interference between visual channels can reduce the discriminability of marks. To address this issue, we contribute Value-Suppressing Uncertainty Palettes (VSUPs). VSUPs allocate larger ranges of a visual channel to data when uncertainty is low, and smaller ranges when uncertainty is high. This non-uniform budgeting of the visual channels makes more economical use of the limited visual encoding space when uncertainty is low, and encourages more cautious decision-making when uncertainty is high. We demonstrate several examples of VSUPs, and present a crowdsourced evaluation showing that, compared to traditional bivariate maps, VSUPs encourage people to more heavily weight uncertainty information in decision-making tasks.

日本語のまとめ:

不確かさを含む値の可視化におけるカラーマッピング手法を提案.不確かさが高いほど可視化値の区分け数を削減するという手法.可視化事例を示すとともに,クラウドソーシングにもとづく評価を行った.意思決定におけるリスク評価の側面からも議論.