程阳：数据可视化，用色彩佐证观点的专家思维

 

How To Use Color To Prove Your Point, From A Data Viz Expert

 

The importance of color theory is a well-explored topic in art and design. But what about when it comes to information design?

 

 

 

http://www.fastcodesign.com/3062182/how-to-use-color-to-prove-your-point-from-a-data-viz-expert

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Meg Miller

Meg Miller is an assistant editor at Co.Design covering art, technology, and design.

http://www.fastcodesign.com/user/meg-miller

 

 

 

When working with large amounts of data, precision is key. The same is true of the art of data visualization: size, shape, shade, hue—the tiniest details of a visualization can radically alter how information is perceived and understood.

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当与大量数据打交道时，准确是关键。这对于数据可视化艺术来说也是一样：大小、形状、阴影和色彩——可视化中微小的细节会彻底改变信息的感知和理解方式。

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Which is why color is an important aspect to consider (read: obsess over) when it comes to information design. "The overarching lesson for data design is that the color is there to help you understand the data," says Maureen Stone a color expert and research manager at the data visualization company Tableau. "It's there as a visual cue for what the data means. So I always tell designers the first thing they need to do is figure out what is the color doing? What is its function?"

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在信息设计中色彩为什么如此重要？“数据设计的第一课说的就是色彩是帮助理解数据的工具，” Maureen Stone说道，她是数据可视化企业Tableau的一位色彩专家以及研究经理，“色彩是揭示数据意义的视觉提示，所以我经常告诉设计者们他们要做的第一件事就是指出颜色代表的意义及其功能。”

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Stone's job is to work with information designers at Tableau to create and chose the best colors for data visualizations. She runs a lab within the R&D arm of the company that is dedicated to researching color specifically as it relates to data. Lately, they've been applying their color research to creating the color palette options in the latest version of the company's data viz software, Tableau 10.0.

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Stone的工作是与Tableau的信息设计师一起来创造和选择数据可视化的最佳色彩。她在公司的研发部门创立了一个实验室，专门用来研究色彩的专用性以及与数据的关系。后来，他们将研究成果运用到公司最新版的数据可视化软件Tableau 10.0中，设计并加入了调色板选项。

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When I ask Stone over the phone what type of function color might have in terms of data visualization, she points out a few common ones: Is it being used to discriminate between categories? Or is it assigning value along a scale, using different shades of the same color to indicate more or less of something? Perhaps its only function is to serve as an unassuming background color against which color-coded categories can "pop."

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当我在电话中问Stone色彩在数据可视化中会有哪些作用时，她提到了一些常见观点：它是用来区分不同的类别，还是用来赋值，以某种颜色的不同阴影来表示量的多少？也有可能它唯一的作用就是作为背景色来衬托其它分类色。

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Determining the function is a first necessary step, but that decision opens up a whole world of more specific choices that can profoundly impact how the visualization is perceived. Here are the most important considerations, according to Stone.

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判断其作用是第一步也是必要的一个步骤，然而这一步之后就会出现更多待定细节，他们对可视化效果都有着深刻影响。Stone介绍说以下是最重要的考量。

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SEMANTICS, SEMANTICS

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语义，语义！

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One of the key things to keep in mind when choosing color for a data visualization is making sure the colors are "semantically resonant," as Stone puts it, with the data they are representing. Put simply, that means that designers need to pay heed to the relationship between a color and the thing that the color is being used for.

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Stone说，当针对数据可视化选择颜色的时候，一个需要铭记在心的关键点是一定要保证色彩与其代表的数据能产生的“语义共鸣”。简单来说，设计者们要时刻留心色彩与其用处之间的关系。

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A simple example of this is a bar graph comparing the price of vegetables. Rendering the broccoli bar in green and the corn bar in yellow is consistent with our color-food associations. Switching the colors—so that broccoli is represented by yellow and corn is green—would be confusing. Another very common example hails from heat map-style graphics, like this one made by Trulia to visualize commute times, where red is associated with negative conditions and green or blue are associated with the positive. Context counts, too. If you're charting this quarter's earnings from the computer giant Apple, you'd do well to color the data gray to correspond with the brand and its shiny devices, rather than the red or green associated with the fruit.

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举个简单的例子，假设有一个用来比较蔬菜价格的条形图，用绿色代表菠菜，用黄色代表玉米，这与我们对事物和颜色的认知是一致的。若转换颜色——黄色代表菠菜而绿色代表玉米——容易产生混淆。另一个常见的例子来自于热度制图学，比如Trulia制作的交通费时的可视化图形，用红色表示交通较坏的情况，而绿色或者黄色表示较好的情况。同样，上下文语义也非常重要。假如你是在对电脑巨头企业苹果公司的季度收入作图，那么你会用灰色来表示数据，从而与其品牌和产品颜色对应，而不是那些像水果颜色的红红或绿绿。

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In heat map-style graphics, red is associated with negative conditions and green or blue are associated with the positive.via Trulia

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在热度图中，用红色往往代表较坏的情况，而绿色或者黄色表示较好的情况。via Trulia

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Some concepts, of course, aren't strongly associated with a particular color. Designers might interpret that as an opportunity for free creative reign, but Stone sees it as a chance to use data to dig deeper under the surface level of our word-color associations. As part of a research project from 2015, Stone and fellow Tableau research scientist Vidya Setlur came up with an algorithm that generates "semantically meaningful colors" by measuring color name frequencies from Google n-grams, then retrieving a representative color from Google Images.

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显然，有部分概念并不能和某一颜色产生关联，设计者们可能会将这当做是自由发挥的好机会，但是Stone则将其视为利用数据对文字与色彩的关联进行深度挖掘的时机。在2015年的项目研究中，Stone和Tableau的研究科学家Vidya Setlur利用谷歌的n-gram来计算颜色名称出现的频率，设计了一个能够生成有语义色彩的算法，然后在谷歌图片中检索其代表色。

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An n-gram search for the word "yellow," for example, comes back with a strong association with "taxi," among others. A Google image search for taxi, meanwhile, will bring up photos of various colored taxis (some newer cabs in New York, for example, are lime green) but with a higher percentage of yellow cabs. Stone and Setlur created an algorithm that "clusters" all of those images together and comes up with the strongest color match: in this case, a bright yellow.

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举个例子，用n-gram方法搜索‘黄色’这个词，会出现与‘出租车’关联的结果。同时，用谷歌图片搜索‘出租车’，会出现各种颜色出租车的图片（比如在纽约的一些新车是石灰绿的），但其中黄色车的频率最高。Stone和Setlur设计了一个算法来对这些图片进行聚类并产生关联最强的颜色，这个时候，就是亮黄色。

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Even if you don't happen to have your own linguistic color algorithm, you can usually deduce if there is a correlation from between concept and color. It's only smart to use it.

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即时你没有你自己的语言色彩算法，你也可以自己推断语义概念与颜色之间的关系，毕竟用这个是聪明的做法。

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The graph on the left shows colors mapped out in color space. The colors that are close together, like green and yellow, are also perceptually similar.Tableau

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左边的图显示了在色彩空间中的标出的颜色，那些颜色相近的颜色，比如绿色和黄色，在感官上也是相似的。——Tableau

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BE DISCERNING

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高识别度

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When it comes to colors used for data science, you need to discriminate: The colors should be different enough from one another so that they're easy to tell apart in a visualization. When choosing colors for data, Stone maps them out using color space, or a modeling tool that shows the full range of colors. If the colors are close together in color space—green and yellow are right beside each other, for instance—they're also perceptually close. And it's best not to use two colors that are perceptually close together in a data viz.

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当色彩开始逐步被运用于数据科学中，你需要区别对待：为了能在可视化图表中精确地表达信息，不同颜色的差别应该足够明显。Stone用颜色空间或一种可以展示颜色所有范围的模型工具来为数据选择颜色。如果选中的颜色在颜色空间中非常接近——例如，绿色和黄色紧临彼此——它们仍然会让人觉得不易区分。在数据可视化中，最好不要同时用两种感觉类似的颜色。

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"What we discover is as you see colors at small sizes they become less colorful," Stone says.

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Stone说道：“我们发现，小尺度面积的颜色往往看起来不够多彩”

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One real-world example of this idea comes from a 2015 infographic showing the most comprehensive "tree of life" to date. In it, thousands of lines on a graph represent every known species on earth—from the most basic bacteria to the most complex of metazoa. To give a very detailed glance at the evolution of life in a comparatively tiny graph, the researchers behind the project seemingly chose the colors to contrast with one another. The red of bacteria is beside the blue of metazoa—two colors on the opposite ends of the color spectrum. The colors help to clarify the huge amount of data.

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关于这个想法的一个实例来自2015信息图中展示的最复杂“生命之树”的数据。在这幅信息图中，成千上万条线代表了地球上已知的生物种类——从最基础的细菌到最复杂的多细胞生物。在一个可对比的小图片中，展现了生命进化的细节。研究人员试图通过不同的颜色进行对比。代表细菌的红色挨着代表多细胞生物的蓝色——在色谱上对比强烈的两种颜色，这样的颜色对比有助于我们明确区分如此大量的数据。

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This "tree of life" graphic clarifies a large amount of data by using colors that are visually distinct from one another.via opentreeoflife.org

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“生命之树”的图表通过运用对比强烈的颜色清晰地表达了大量的数据。（来自opentreeoflife.org）

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SIZE MATTERS

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尺寸问题

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When choosing or creating color for data, Stone says it's important to remember what she calls the "paint chip effect." Logically, if you want to paint your wall a bright yellow, the color you choose is going to look much brighter once it's covering an entire room than it does on a little paint chip. Similarly, a color will look different as a tiny block on a map legend than it does covering an entire state on a map.

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当为数据选择或者适配颜色的时候，Stone认为 “粉刷碎片效应”非常重要。逻辑上，如果你想要用亮黄色的涂料粉刷墙面，粉刷整个房间将比只粉刷一小块看起来明亮很多。类似的,某种颜色在地图上被填充一小块与被填充一大片的效果也是截然不同的。

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"What we discover is as you see colors at small sizes they become less colorful," Stone says. The variable here is the color's chroma, or measurement of colorfulness by dimension. An electric blue racing stripe, for example, has a high chroma, while a muted grayish-blue has a low chroma. When used at a smaller size, the chroma for the latter would need to be increased so that it's bright enough to be distinct. The electric blue, when enlarged, would need a slightly decreased chroma so it doesn't "yell at you," as Stone puts it.

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“小尺度面积的颜色往往看起来不够多彩”Stone如是说。这里的变量是指颜色的色度，或色彩维度的评估。例如，一种电蓝色赛车条纹拥有高色度，而柔和的灰蓝色拥有低色度。当被用在小面积区域时，后者的色度需要被增强才能足够显眼地被区分。当大面积使用电蓝色时，需要稍微降低色度，才不会显得很扎眼。

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This infographic about the amount of nuclear weapons in the world is rendered in yellow, black, and white—negative colors to match a sober subject.u/drwtsn via Reddit

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这张信息图用黄色、黑色和白色表达世界上大量的核武器——这些消极的颜色可以与严肃的主题相匹配。（来自Reddit用户drwtsn）

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COLORS HAVE AFFECT

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颜色的影响

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It's no surprise that colors can evoke emotional connections—blues and purples are perceived as more pleasant than yellows, for example. Bright green can be seen as aggressive or playful. As Stone puts it, "everyone in the design realm knows that color has affect, and they have examples and rules" based on that knowledge. "One question is: Even on a bar chart, does that count?"

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颜色可以唤起情感共鸣并不奇怪——例如，蓝色和紫色比黄色使人感觉更愉快。鲜绿色使人感觉积极或欢乐。正如Stone所说，“设计领域的人都知道，颜色会对人产生影响，他们对此有很多案例和使用原则”基于这种认知，“那么，即使是一个条线图，也同样适用吗？”

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The answer, according to Stone, is yes. In conjunction with researchers at Simon Fraser University in British Columbia, Canada, she conducted a study that asked people to color bar charts so that they conveyed certain feelings, like calm, playfulness, or negativity. Their research showed certain patterns: People selected more muted colors for a calmer bar chart and brighter colors (high in chroma) for a playful chart. Meanwhile, they chose dark colors to convey negativity. Using this information to color charts in a way that is consistent with the data can emphasize the message being conveyed.

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答案是肯定的，Stone说。与加拿大西蒙菲莎大学研究者合作，Stone组织了一个调研去询问人们对条线图的感觉，比如冷静，欢乐，或消极。他们的研究结果显示：人们为平静的条线图挑选更柔和的颜色，为欢快的条线图挑选更明亮的颜色（高色度）。与此同时，他们为消极的条线图选择深颜色。运用与数据相匹配的颜色来填充图表，能强化信息的表达。

 

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Coloring a chart in a palette that induces calmness may not be as functionally important to data visualization as color distinctness or semantic correlation. But considering all of these factors together will help people absorb and understand data more easily, Stone says. Designers may think that their use of color is meaningless, but it could have emotional side effects that influence how readers understand the data. Take this infographic visualizing the number of atomic weapons in the world in a given year. The designer, Reddit user drwtsn, chose the colors yellow, black, and white—colors commonly associated with negativity—instead of a pleasant palette of mint green and robin egg blue or the bright reds or intense oranges you might associate with nuclear war.

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在调色板中为图表填色会引起镇静，也许在功能上数据可视化不一定比颜色差异性或语言关联性更重要。但是，把所有的因素考虑进去将帮助人们更容易地吸收和理解数据，Stone说。设计者或许会认为他们颜色的运用是毫无意义的，但是这会对读者理解数据产生情感方面的影响。看一下这幅关于近些年来世界上大量核武器的信息图。设计者，Reddit 的用户drwtsn,选择了黄色、黑色和白色——这些颜色通常是消极的——而不是明快的薄荷绿和灰绿蓝色或亮红色或橘红色这些可能使你联想到核战争的颜色。

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As Stone shows through her research, the fascinating science behind color theory isn't dulled by the cold mathematics of big data. Instead, it marries art and science in a way that is both functional and aesthetically pleasing.

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正如Stone通过她的研究展现的，在颜色理论背后的迷人的科学不是乏味无趣的大数据的冰冷数学，而是与艺术和科学相结合，使它既实用又美观。