Data visualization is a great way to celebrate our favorite pieces of art as well as reveal connections and ideas that were previously invisible. More importantly, it’s a fun way to connect things we love — visualizing data and kicking up our feet for a movie night. All week, Nightingale is exploring the intersections between data visualization and all kinds of entertainment.

数据可视化是庆祝我们最喜欢的艺术品以及揭示以前不可见的联系和想法的好方法。 更重要的是，这是连接我们喜欢的事物的一种有趣方式-可视化数据并为电影之夜踢起脚来。 整个晚上，夜莺都在探索 数据可视化与各种娱乐之间 的 交集 。

From the sensational Tiger King, to the meme-inspiring Ancient Aliens, to the hypnotic Blue Planet, to the [cathartically?] disastrous Fyre, documentaries are a mainstream, pop-culture vehicle for “truth-telling” and nonfiction storytelling.

f光盘煽情虎王 ，为“讲真话”和非小说评书梅梅，鼓舞人心的远古外星人 ，到催眠蓝色星球 ，到[cathartically？]灾难性Fyre，纪录片是一个主流，流行文化的载体。

Anecdotally, it feels like lately I’m more likely to be recommended a documentary on a topic versus a book or even a podcast. Not only are they doing increasingly well at the box office, documentaries have increasingly captured more of the share of content we consume from the big screen — from less than 2% of all films and TV series 50 years ago to 20% last year.

有趣的是，最近觉得我更有可能被推荐为关于主题的纪录片，而不是书甚至是播客。 他们不仅在票房上表现越来越好，而且纪录片也越来越多地捕获了我们从大屏幕上消费的内容份额–从50年前所有电影和电视连续剧中的不到2％到去年的20％。

Documentaries are the natural byproduct of our love of motion picture storytelling expressed during the information age. Documentary producer Dan Cogan, whose company has produced or funded over a hundred documentaries, said, “We are in the Golden Age of documentary film making. … There has never been as great storytelling in nonfiction film as there is today.”

纪录片是我们在信息时代表达对电影故事的热爱的自然副产品。 纪录片制作人丹·科根(Dan Cogan)制作或资助了一百多部纪录片， 他说 ：“我们正处于纪录片制作的黄金时代。 ……在非虚构电影中，从来没有像今天这样伟大的故事讲述。”

We get to learn while enjoying all the things we love about fiction narratives: edge-of-our-seat intrigue, obsession over mystery, teary-eyed redemption arcs, comedic tragedies.

我们在学习的同时享受着关于小说叙事的所有热爱：我们的边缘阴谋，对神秘的迷恋，眼泪的救赎弧，喜剧悲剧。

What a wonderful time to learn.

多么美好的学习时间。

While I’d love to wax poetic on documentary narratives, this piece is really about the similarity to data storytelling: both arts are informing via narrative.

尽管我很想在纪录片叙事上增添诗意，但这篇文章实际上是关于数据叙事的相似之处：两种艺术都通过叙事来传达信息。

Given the rising interest in documentary as a medium that so artfully marries learning and story, it makes sense that similar demands would fall on the “data” world. Our users and audiences aren’t satisfied with facts—they desire entertainment, exposition, intrigue.

鉴于人们对纪录片作为一种巧妙地结合学习和故事的媒体的兴趣日益浓厚，因此类似的需求将落在“数据”世界上是有道理的。 我们的用户和观众对事实不满意-他们渴望娱乐，展示和阴谋。

We crave the form of meaning that only stories can deliver. It’s not enough to know something, we want to experience it through the perspective of a narrator and characters.

我们渴望只有故事才能传达的意义形式。 仅仅了解某件事是不够的，我们希望通过叙述者和角色的视角来体验它。

Along with the rise of documentaries, we can follow the rise of “data storytelling.” Since 2011, Google searches for the phrase “data storytelling” have dramatically increased (with a noteworthy acceleration in 2015 after Cole Nussbaumer Knaflic published her discipline-defining title, Storytelling with Data).

随着纪录片的兴起，我们可以追随“数据故事讲述”的兴起。 2011年以来，谷歌搜索短语“数据说话”有大幅提升(与科尔NUSSBAUMER Knaflic后，在2015年一个值得注意的加速出版了她的纪律定义标题， 讲故事用数据 )。

What might have once been a buzzword is now codified into a sought-out skill set. Nussbaumer’s book was followed by this book and this book and this book and this book and this book and this book and this book and this book and I’m sure others that aren’t waving their hands at the top of Amazon’s search algorithm. Storytelling, UX, and information design was a track at this year’s DataVizLive conference. It’s long been a criteria for judging in Tableau Conference’s IronViz competition.

曾经曾经是一个流行语的东西现在被编入了一个备受追捧的技能组。 紧接着Nussbaumer的书， 这本书 ， 这本书 ， 这本书 ， 这本书 ， 这本书 ， 这本书 ， 这本书 ， 这本书以及这本书 ，我敢肯定，其他人不会在Amazon搜索算法的顶部挥舞自己的双手。 讲故事，用户体验和信息设计是今年DataVizLive会议的主题。 长期以来，Tableau Conference的IronViz竞赛一直是评判标准。

Data storytelling isn’t a trendy buzzword, it’s a preference in how we consume information and how we learn.

数据讲故事并不是一个时髦的流行语，它是我们如何消费信息和学习方式的首选。

Don’t give me a chart—give me a story.

不要给我一张图表，而是给我一个故事。

So we’ve seen a parallel in the rise of the documentary and data storytelling, both crafts that pair information with narrative, insights with entertainment.

因此，我们看到了纪录片和数据讲故事的兴起，两者都将信息与叙事，洞察力与娱乐结合在一起。

Although both crafts are currently very prevalent, documentaries have been at this game for a lot longer. While identifying the “first” documentary requires navigating some academic arguments on genre, the consensus is that the ethnographic Nanook of the North, by Robert Flaherty, was the first—in 1922.

尽管目前两种Craft.io都很流行，但纪录片在这场比赛中已经存在了很长时间。 同时确定了“第一”的纪录片，需要导航流派一些学术争论，共识是，人种学北方的纳努克 ，由罗伯特·弗莱厄蒂，是先于1922年。

Fast forward nearly a century: Nussbaumer’s groundbreaking book Storytelling with Data came out in 2015. Of course people were pairing narratives with data before that book, but it feels pretty clear that as a practiced and disciplined craft, documentaries are our elder.

快进近一个世纪：努斯鲍姆(Nussbaumer)开创性的书《讲故事与数据》于2015年问世。当然，人们在那本书之前将叙述与数据配对，但很显然，纪录片是我们的老练纪律。

And, just as our elders can say “Oh, I’ve solved that before, just try this,” documentaries can show us a number of techniques we can use to marry information and narratives.

而且，就像我们的长辈可以说：“哦，以前我已经解决了，只需尝试一下即可。 ”纪录片可以向我们展示许多可用于结合信息和叙述的技术。

中立的神话 (The myth of neutrality)

Documentaries—especially observational documentaries—create a sense of truth about what we’re seeing, especially when the film crew are “invisible.” This isn’t just true of documentaries, it’s true of a lot of video.

纪录片，尤其是观察片 纪录片-使我们对所看到的事物有一种真实感，尤其是当摄制组是“隐形的”时。 这不仅适用于纪录片，还适用于许多视频。

However, filmmaker choice guides what we see. Editing determines the order in which we see things and what we don’t see. Things like music and filmography impact the value we place on what we’re seeing (for example, the same interaction between two people could be perceived as positive or negative, depending on the background music).

但是，制片人的选择将指导我们所看到的。 编辑决定了我们看到事物的顺序和看不到事物的顺序。 诸如音乐和电影摄影之类的事物会影响我们对所看到事物的重视(例如，取决于背景音乐，两个人之间相同的互动可能会被感知为正面或负面)。

On the more malicious end, Nanook of the North intentionally staged the narrative to portray the Inuits in a negative and subhuman light. Much of what we saw of the protagonist, Nanook (whose actual name was Allakariallak), is distorted or fabricated. Many of Flaherty’s directorial decisions played into colonial voyeurism, forcing real people to fit into a Euro-American narrative of Indigenous people.

在更为恶意的方面， 北方的纳诺克(Nanook)故意上演了叙事，以消极的，不合人类的眼光描绘了因纽特人 。 我们看到的主角Nanook(实际上的名字是Allakariallak)的大部分内容都是失真的或虚构的。 弗莱厄蒂(Flaherty)的许多导演决定都导致了殖民窥淫癖，迫使真实的人融入了欧美人对土著人的叙述中。

Yet providing an “unbiased” recording of reality isn’t possible (this isn’t to justify Flaherty’s colonialist narrative—our biases can certainly be intentional and malicious). In the literary version of social science’s Observer Effect, simply bringing a camera into an environment changes the behavior of the subject being filmed. In addition, some environments can’t be filmed as they are, and so observing “truth” may require modifying the environment. Nanook of the North provides another example here, as the filmmakers rebuilt the igloo as a three-walled structure to accommodate the large cameras. Giving viewers a glimpse of the living conditions inside an igloo required modifying the igloo itself.

但是，不可能提供“无偏见”的现实记录(这不能证明弗莱厄蒂的殖民主义叙述是正当的-我们的偏见肯定是故意的和恶意的)。 在社会科学的《 观察者效应》的文学版本中，仅将相机带入环境即可改变被摄对​​象的行为。 此外，某些环境无法照原样拍摄，因此观察“真实”可能需要修改环境。 北方的纳诺克(Nanook)在这里提供了另一个例子，电影制片人将冰屋重建为三层结构，以容纳大型相机 。 要让观众瞥见冰屋内部的生活条件，就需要修改冰屋本身。

Much of this holds true for data storytelling. As analysts, we navigate similar decisions as documentary filmmakers. Filmmakers choose what to observe, we choose what data to analyze. Filmmakers choose their camera lens, we choose our analytic technique. Filmmakers edit out material and rearrange sequences, we choose which data to filter out and the ordering of our insights. Filmmakers choose music, images, fonts—so do we.

对于数据讲故事，这大部分适用。 作为分析师，我们与纪录片制片人一样会做出类似的决定。 电影制片人选择观察的内容，我们选择分析的数据。 电影摄制者选择他们的相机镜头，我们选择分析技术。 电影制片人剪辑出材料并重新排列序列，我们选择要过滤的数据以及洞察力的顺序。 电影制片人选择音乐，图像，字体，我们也是。

As analysts, we have to admit that we rebuild igloos, too.

作为分析师，我们必须承认我们也重建了冰屋。

There’s no such thing as a neutral documentary, and there’s no such thing as a neutral data story. Documentaries have been thinking about this far longer than we have, and it seems like perhaps a critical first question we can bring to the wisdom of our elder craft.

没有中立的纪录片，也没有中立的数据故事。 纪录片思考这个问题的时间比我们思考的时间长得多 ，似乎我们可以将这个古老Craft.io的智慧带入一个至关重要的第一个问题。

旁白和旁白 (Voice-overs and narration)

One of my biggest turn-offs in data storytelling are walls of text. Like a real wall, a large body of text can prevent your audience from accessing your message, especially when used up-front. I find myself skimming the first few lines, then either skipping the rest or just closing the page altogether. Here’s one of the worst examples, from my own portfolio:

文字叙事是我最大的数据叙事之一 。 就像一堵真实的墙一样，大量的文字可能会阻止听众访问您的消息，尤其是在预先使用时。 我发现自己浏览了前几行，然后跳过了其余几行，或者只是完全关闭了页面。 这是我自己的投资组合中最糟糕的例子之一：

Meanwhile, just this past weekend I was watching a documentary. About two minutes in, I found myself bored and distracted as a narrator paced around a set, rambling through a tedious exposition. I turned the documentary off.

同时，就在过去的一个周末，我正在观看纪录片。 大约两分钟后，我发现自己感到无聊和分心，因为一个解说员在一个布景中徘徊，漫步在一个乏味的展览中。 我关闭了纪录片。

Instead I turned on Cosmos: A Spacetime Odyssey. From the moment the studio logo disappeared, I was greeted with stunning images of beautiful landscapes, paired with a tribute Carl Sagan quote. The camera zoomed in to that landscape to find the narrator, Neil deGrasse Tyson, who provided me with a 14-second introductory exposition packed with intrigue and mystery. I was hooked as Tyson’s voice-overs elegantly explained the wondrous high-definition images I witnessed.

相反，我打开了《 宇宙：时空漫游》 。 从工作室徽标消失的那一刻起，我就被美丽的风景令人惊叹的图像所吸引，并向卡尔·萨根致敬。 相机放大到那个风景，找到了叙述者尼尔·德格拉斯·泰森(Neil deGrasse Tyson)，他为我提供了14秒钟的介绍性展览，内容丰富且充满神秘感。 泰森(Tyson)的画外音优雅地解释了我所看到的奇妙的高清图像，这让我着迷了。

For a similar mastery in data storytelling, we can look to the Guardian’s 2017 “Bussed Out,” an award-winning data journalism piece about homelessness in the U.S. Journalism is a medium that typically relies on text, but from the get-go, “Bussed Out” integrates the exposition with images and animated data visualizations.

对于数据叙事的类似掌握，我们可以看一下《卫报》(Guardian)2017年的“ Bussed Out ”，这是屡获殊荣的数据新闻行业的一篇有关美国无家可归者的文章，该媒体通常依赖于文本，但从一开始就“疯了” 将博览会与图像和动画数据可视化集成在一起。

This piece really captures the essence of masterful narration as the charts fill out while I scroll through the story of individuals and society. Words live with charts, rather than just above, below, and beside them. Any lengthy bodies of text are accompanied with formatted quotes and plenty of negative space, creating openings in what might otherwise feel like walls.

当我滚动浏览个人和社会的故事时，这些图表确实充满了精湛叙事的精髓。 单词与图表一起生活，而不是仅仅在图表的上方，下方和旁边。 任何冗长的文本内容都带有带格式的引号和大量的负空格，从而在原本感觉像墙壁的地方创造了开Kong。

Too often I feel as if I’m given an instruction manual for a chart: Here’s what it shows, read it like this. “Bussed Out,” on the other hand, narrates my experience, seamlessly weaving evidence and explanation. We want to avoid being a tedious narrator, instead weaving visual voice-overs into our evidence.

我常常觉得好像给了我一张图表的使用说明书： 这是它显示的内容，像这样阅读 。 “花光了，” 另一方面，讲述我的经历，无缝地编织证据和解释。 我们希望避免成为一个乏味的叙述者，而将视觉配音编织到我们的证据中。

面试 (Interviews)

I recently checked out the Netflix reboot of Unsolved Mysteries. I nostalgically remember Robert Stack’s distinctive voice as he narrated the mystery from foggy alleys, dark churches, cemeteries, or staged dispatch centers. The new Unsolved Mysteries, though, lacks a narrator. Instead, interviews are spliced together, feeding us clues and emotions like a carefully calculated multiple course meal, each preparing us for the next. The trailer, also lacking a narrator, showcases their interviewing technique:

我最近检查了Netflix重新启动的“ 未解之谜” 。 我怀旧地记得罗伯特·斯塔克独特的声音，他讲述了在有雾的小巷，黑暗的教堂，墓地或上演的调度中心的奥秘 。 但是，新的《 未解之谜》没有叙述者。 取而代之的是，采访被拼接在一起，为我们提供了线索和情感，就像经过精心计算的多道菜一样，每一次都使我们为下一次做准备。 预告片也缺少解说员，展示了他们的采访技巧：

The difference is compelling: Whereas the original Unsolved Mysteries were intriguing and suspenseful, I found this reboot to be tragic and sad as I felt hints of the loss of the friends and family being interviewed. In the original Unsolved Mysteries, the narrator was a mediator, protecting me from the tragedy by turning it into suspense. When the narration comes directly from the friends and family, I feel much closer to the story—and the raw emotion that comes with it.

两者之间的差异令人信服：尽管原始的未解之谜令人着迷且令人生疑，但我发现这种重新启动是悲剧性的和悲伤的，因为我感到被采访的亲朋好友流连忘返。 在最初的《 未解之谜》中 ，叙述者是调解人，通过将其变成悬念来保护我免受悲剧的侵害。 当叙述直接来自朋友和家人时，我会更接近这个故事以及随之而来的原始情感。

Lisa Charlotte Rost discussed the inverse relationship between aggregation and empathy in her 2017 Open Viz presentation, A Data Point Walks Into a Bar: Designing Data for Empathy. It’s just easier to empathize with individuals we can see or hear.

丽莎·夏洛特·罗斯特(Lisa Charlotte Rost)在她的2017年Open Viz演讲`` 数据点走进酒吧：为同理心设计数据''中讨论了聚合与同理心之间的逆向关系。 同理心更容易 与个人 ，我们可以看到或听到。

To that effect, I can still remember the first time I saw interviews paired with a data story: ProPublica’s “Losing Ground.” I stumbled across this in 2014, and I can still recall the powerful photograph of Earl Armstrong, a cattle rancher, standing in his field under a foot of water.

为此，我仍然记得我第一次看到采访与数据故事相结合的情况： ProPublica的“ 失地 ” 。 我在2014年偶然发现了这一点，至今仍能回想起牛Rancher伯爵阿姆斯特朗(Earl Armstrong)站在水底下的强大照片。

I can remember the sound of his voice from the short recording. Granted, I’ve returned to this image over and over—but that’s because of the powerful way ProPublica paired aggregated data with individual interviews. Leading up to my discovery of “Losing Ground” I had seen my share of charts and data stories about climate change and rising coastal waters, but this was the first one that really stuck in my mind.

我可以从简短的录音中记住他的声音。 诚然，我已经一遍又一遍地返回到该图像，但这是因为 ProPublica将汇总数据与个人访谈配对的强大方式。 导致我发现“失落的土地” 我看到了有关气候变化和沿海水域上升的图表和数据故事，但这是我真正想到的第一个。

Both Unsolved Mysteries and ProPublica let people tell their own story. Whenever possible, they get out from between the subjects and the audience. All too often we think of data storytelling and data humanization as “telling the stories of the people in our data,” but I’d argue that we should look for opportunities let people tell their own story, rather than assume we have the power and right to speak on their behalf. We won’t always have that opportunity, but I think it’s a powerful device we should at least try to employ.

未解之谜和ProPublica都可以让人们讲述自己的故事。 只要有可能，他们就会从主题和听众之间脱身。 我们常常认为数据叙事和数据人性化是“在数据中讲述人们的故事”，但我认为我们应该寻找机会让人们讲述自己的故事，而不是假设我们拥有力量和力量。代表他们发言的权利。 我们不会总是有这个机会，但是我认为这是我们至少应该尝试使用的强大工具。

重演 (Reenactments)

I’m a big fan of the show River Monsters — it blends my hobby of fishing with my interest in folkoristics, all tossed together with a level of excitement. The host and angler, Jeremy Wade, chases down marine monsters by following stories of bizarre and often dangerous encounters. The show alternates between interviewing and reenacting the story they are telling. For some examples, watch some of the video below (content warning: mildly graphic descriptions and images of injury and death):

我是节目《 河怪兽》的忠实拥护者，它融合了我的钓鱼爱好和对民俗学的兴趣，所有这些都使人兴奋不已。 主持人和垂钓者杰里米·韦德(Jeremy Wade)跟随奇异且经常危险的相遇故事追逐海洋怪物。 该节目在采访和重演他们讲的故事之间交替进行。 例如，请观看下面的一些视频(内容警告：轻微的图形描述以及受伤和死亡的图像)：

Forensic Files, Unsolved Mysteries, and quite a few SyFy channel mystery shows employ this technique. Of course, it helps to inject suspense into the show—but it also provides educational value to help us understand the progression of events. Often reenactments are paired with step-by-step narratives to help our imaginations materialize the story: First this happened like this, then that happened like that, and so on.

法证文件 ， 未解之谜和许多SyFy频道的谜题节目都采用了这种技术。 当然，它有助于在节目中注入悬念，但是它也提供了教育价值，可以帮助我们了解事件的进展。 通常，重演与分步叙述相结合，以帮助我们的想象力实现故事： 首先是这样的事情发生 ， 然后是那样的事情发生，依此类推。

Perhaps the most obvious parallel between reenactments in documentaries and data viz is seen in animations. A strong example comes from NYT’s “The Dangerous Flaws in Boeing’s Automated System.” This piece brilliantly combines relatively simple graphics with scrolling annotations, narrating the plane’s angle of flight so the reader can follow exactly how faulty sensors may have caused a crash. We see how sensors are supposed to work, we see the safe angles for flight and we’re given a vocabulary. Then, the animations show us what happens when a sensor provides a false reading, and the diagram makes the potential danger very clear:

动画中可以看到纪录片中的重演与数据之间最明显的相似之处。 纽约时报的“ 波音自动系统中的危险缺陷 ”就是一个很好的例子。 这篇文章巧妙地将相对简单的图形与滚动注释结合在一起，讲述了飞机的飞行角度，使读者可以准确地了解有问题的传感器可能导致坠机的原因。 我们看到了传​​感器应该如何工作，看到了飞行的安全角度，并且获得了词汇。 然后，动画向我们展示了当传感器提供错误读数时会发生什么，该图使潜在危险非常清楚：

While reenactments might bring animations to mind, there are plenty of strong static “play-by-plays” out there, such as “How the Notre Dame Cathedral Fire Spread,” another example from NYT. Static images provide us a play-by-play breakdown of how the fire began and spread, and how French firefighters sought to combat the fire. Each moment provides us with a beautifully drawn cross-section paired with photographs of the fire, allowing us to connect what our eyes saw to the hidden and vulnerable architecture.

虽然重演可能会让人想到动画，但这里有很多强大的静态“逐个播放”功能，例如“ 纽约 圣母院大教堂的火势如何蔓延 ”，这是纽约时报的另一个例子。 静态图像为我们提供了火势如何开始蔓延以及法国消防员如何扑灭大火的详细信息。 每一个瞬间都为我们提供了精美绘制的横截面以及火焰的照片，使我们能够将眼睛看到的东西与隐藏的脆弱建筑联系起来。

All too often my own tendency is to summarize events over time in a single line chart—perhaps for the above, I’d have shown some measure of fire intensity plotted at each hour. However, this reenactment parallel technique allows readers to understand what’s happening within each of those dots along a line.

我自己的趋势常常是在单个折线图中汇总随时间变化的事件-也许对于上述情况，我已经展示了每小时绘制的某种火势度量。 但是，这种重新制定并行技术使读者可以理解沿线的每个点中正在发生的事情。

We, and our readers, don’t experience time as a line—we live in a single dot at a time, a single moment. Reenactments—and the NYT team’s storytelling in this example—let me experience each dot, enabling me to contextualize the data and the insights into the narrative almost as if I was omnisciently witnessing the fire in person.

我们和我们的读者不会像排队一样体验时间，我们一次只能住一个点。 重演以及本例中的NYT团队的故事讲述-让我体验到每个点，使我能够将数据和叙述的见解上下文化，几乎就像我全神贯注地亲眼目睹火灾一样。

The few concepts I’ve outlined above are just examples. The more I dig into documentary narrative techniques, the more parallels I find to examples of excellence in data storytelling. Our mediums are different, so these parallels are never one-to-one—but the similarities are strong enough that I’m convinced we should look to the art of documentary filmmaking as our elder, with a lifetime of experience to share.

我上面概述的几个概念仅仅是示例。 我越是研究文献叙事技术，就越会发现与数据叙事卓越案例的相似之处。 我们的媒体是不同的，所以这些相似之处永远不会一对一，但相似之处足够强大，我深信我们应该以长辈的身份去欣赏纪录片电影制作艺术，并分享一生的经验。

Perhaps the most poignant opportunity to see the similarities between documentaries and data storytelling comes from a quote by five-time Emmy Award winning documentary filmmaker Ken Burns:

看到纪录片和数据故事叙述之间相似之处的最可悲的机会可能是五次获得艾美奖的纪录片导演肯·伯恩斯 ( Ken Burns) 的名言 ：

I realized very early on that the laws of storytelling also apply to the documentary. That instead of the documentary necessarily being didactic and educational and, you know, politically advocating, it could also just tell a story using the same expositional tools that a feature film would. And then you’ve got the possibility of moving people at that same level. And you have the added advantage of it being true. Steven Spielberg and I obey the same laws of storytelling. And the only difference is he can make shit up, and I can’t.

我很早就意识到讲故事的法律也适用于纪录片。 那不是纪录片一定是有说服力的和教育性的，而且从政治上讲，您知道，它也可以使用与故事片相同的展示工具来讲述一个故事。 然后，您就有可能将人们转移到同一水平。 而且您还有一个附加的优点，那就是它是真实的。 史蒂芬·斯皮尔伯格和我遵守同样的故事定律。 唯一的区别是他可以弥补，我不能。

Love y’all.

爱你们