What do good speeches and good data visualisation have in common? More than you may think.

好的演講和好的數據可視化有什么共同點？ 超出您的想象。

Aristotle — the founding father of all things public speaking — believed that the job of an orator was to discover the best available means of persuasion. That includes, first, defining all the arguments that can be made for and against a given proposition, then selecting those that will hold most sway with the audience and communicating them in the best possible manner.

亞里斯多德(Aristotle)是所有公開演講的奠基人，他認為演說家的工作是發現最佳的說服手段。 其中包括，首先，定義可以支持和反對給定命題的所有論據，然后選擇最能與聽眾保持聯系的論點，并以最佳方式進行交流。

Does this sound familiar? To me, an orator’s work seems very similar to that of data visualisation designer’s. We explore data to find patterns and insights that will be useful for the audience, and then communicate them in a visual way.

這聽起來很熟悉嗎？ 在我看來，演說者的作品與數據可視化設計師的作品非常相似。 我們探索數據以找到對受眾有用的模式和見解，然后以視覺方式進行交流。

How can this parallel improve our thinking about data design? In this article, I’ll explore nine foundational principles from speaking in public and explain how they can help you improve your data work.

這種并行方式如何改善我們對數據設計的思考？ 在本文中，我將從公開演講中探索九個基本原則，并解釋它們如何幫助您改善數據工作。

1 /建立信任 (1/ Build Trust)

At the centre of Aristotle’s approach to speechmaking is the concept called ethos. Ethos is essentially answering the question, why should I trust you?

亞里斯多德演說方法的中心是名為ethos的概念。 Ethos本質上是在回答這個問題， 為什么我應該信任您？

If I were to give a talk on data visualisation, I’d start by introducing myself. I’d talk about my experience in the field and probably show some of my work. My posture, tone of voice and gestures would reflect confidence. All this would demonstrate that I have expertise on the matter. You’ll be more compelled to listen to me after I show you I know what I’m talking about.

如果我要談數據可視化，我首先要自我介紹。 我將談論自己在該領域的經驗，并可能展示一些我的工作。 我的姿勢，語氣和手勢會反映出自信。 所有這些都表明我對此事有專門知識。 在我告訴你我知道我在說什么之后，你會更被迫聽我講話。

See what I’m getting at? Ethos is the foundation on which your relationship with the audience is built.

明白我在說什么嗎？ 精神是您與聽眾建立關系的基礎。

In data visualisation, trust is also crucial, although it’s created in a different manner. Andy Kirk dedicated an important part of his book to trustworthiness. As he discusses, one way to show the reader they can trust you is to link to the data sources and put forward any assumptions they should know about. A good example of this is Datawrapper’s coronavirus charts where all the caveats in the data are clearly stated.

在數據可視化中，信任也是至關重要的，盡管它是以不同的方式創建的。 安迪·柯克(Andy Kirk)將書中的重要部分獻給了誠信。 正如他所討論的那樣，向讀者表明他們可以信任您的一種方法是鏈接到數據源，并提出他們應該知道的所有假設。 Datawrapper的冠狀病毒圖表就是一個很好的例子，其中清楚說明了數據中的所有警告。

Another way to gain your audience’s trust is to pay (a lot of) attention to detail. That means you should consider every single word and dot in your chart: align all elements, remove unnecessary clutter, format the tooltips and much more. Take the graph from FiveThirtyEight below — isn’t it flawless? That’s what you should aim for, too.

獲得聽眾信任的另一種方法是(非常)注重細節。 這意味著您應該考慮圖表中的每個單詞和點：對齊所有元素，消除不必要的混亂，設置工具提示的格式等等。 從下面的FiveThirtyEight中獲取圖表-完美無缺嗎？ 這也是您的目標。

If you design with ethos in mind, the audience will trust you. Do it consistently, and you will build a longstanding professional reputation.

如果你在考慮風氣設計，觀眾會相信你。 始終如一地做，您將建立長期的專業聲譽。

2 /示教，移動，愉悅 (2/ Teach, Move, Delight)

In public speaking, the presenter can have one of three objectives — to teach, to move or to delight. Sal Kahn taught about online education in his 2011 TED talk. Martin Luther King Jr. inspired the country to take action against racial injustice in his 1963 I Have a Dream speech. President Obama entertained in his 2016 White House Correspondents Dinner address, most famous for its mic drop moment.

在公開演講中，演講者可以實現三個目標之一：教學，移動或取悅。 薩爾·卡恩(Sal Kahn)在2011年的TED演講中講授了在線教育。 小馬丁·路德·金(Martin Luther King Jr.)在1963年的《 我有一個夢想》演講中，啟發該國采取行動打擊種族歧視。 奧巴馬總統在2016年白宮記者晚宴上致辭，該講話最著名的是麥克風掉落時刻。

In data visualisation, the same three objectives apply. You may be teaching the audience about a topic or a chart type that’s unfamiliar to them (see this chord diagram breakdown by Nadieh Bremer). You may be trying to move them to take action (see this visualisation by David Borczuk). Or you may purely want to entertain with a playful visual (see My Fallen Kingdom by Judit Bekker).

在數據可視化中，適用相同的三個目標。 您可能正在向聽眾講授他們不熟悉的主題或圖表類型(請參閱Nadieh Bremer的和弦圖細目分類 )。 您可能正在嘗試使它們采取行動(請參閱David Borczuk的可視化內容)。 或者，您可能純粹是想以有趣的視覺效果來娛樂(請參見Judit Bekker的《 我墮落的王國》 )。

Why is this important? If you define the objective at the start of the design process, it can guide you in choosing content. For example, if your aim is to move the audience to action, how will you present the problem? How will you show it’s relevant to them? How will you frame the conclusion?

為什么這很重要？ 如果您在設計過程開始時就定義了目標，那么它可以指導您選擇內容。 例如，如果您的目標是使聽眾采取行動，那么您將如何提出問題？ 您如何證明它與他們相關？ 您將如何得出結論？

3 /連接點 (3/ Connect the Dots)

Once your objective is clear, you can define a through-line. If it’s the first time you’re hearing this term, you’re not the only one. The concept of a through-line is common in theatre plays, films and novels; I believe it was first introduced in public speaking by the team at TED.

明確目標后，即可定義一條直通路線 。 如果這是您第一次聽到這個詞，那您不是唯一的一個。 直通線的概念在戲劇，電影和小說中很常見。 我相信它是TED團隊在公開演講中首次引入的。

So what’s a through-line? It’s your core message, the take-away you’d like the audience to go home with. It’s the connecting theme that ties together each narrative element of your work. Chris Anderson — the head of TED — cites two examples in his book. The first one is the start of a talk without a through-line:

那么什么是直通電話？ 這是您的核心信息，是觀眾希望帶回家的外賣食品。 這是將您作品的每個敘事元素聯系在一起的主題 。 TED的負責人克里斯安德森(Chris Anderson)在書中列舉了兩個例子。 第一個是沒有直通電話的談話的開始：

I want to share with you some experiences I had during my recent trip to Cape Town, and then make a few observations about life on the road…

我想與您分享我最近在開普敦旅行期間的一些經驗，然后對旅途中的生活進行一些觀察……

And the second one is the same opening, rephrased:

第二個是相同的開頭，改寫為：

On my recent trip to Cape Town, I learned something new about strangers–when you can trust them, and when you definitely can’t. Let me share with you two very different experiences I had. . .

在最近的開普敦旅行中，我了解了一些陌生人的新知識-什么時候可以信任他們，什么時候絕對不能信任他們。 讓我與您分享我所經歷的兩種截然不同的經歷。 。 。

The message is much clearer in the second opening, isn’t it?

在第二個開口中，該信息更加清晰了，不是嗎？

What would a through-line look like in data visualisation? As an example, let’s look at Ludovic Tavernier’s visual called Two Years Late. What’s his through-line? I’d phrase it something like this:

數據可視化中的直通行是什么樣的？ 舉例來說，讓我們看一下Ludovic Tavernier的視覺作品《 兩年后》 。 他的直通電話是什么？ 我會這樣說：

The human stories behind the US immigration policies.

美國移民政策背后的人間故事。

How can you craft a through-line for your own work? Define an objective first, as discussed in the previous section. Then, go deeper. What exactly are you trying to convey? What do you want your audience to remember after they’ve explored your work? Be as specific as possible, but keep the message to a single sentence.

您如何為自己的工作制作一條直通電話？ 首先定義一個目標，如上一節所述。 然后，更深入。 您到底想傳達什么？ 您的聽眾在瀏覽您的作品后想記住什么？ 盡可能具體，但將消息保持在一個句子中。

Now, when you add content to your visualisation, choose only those bits that relate to this core message. If you do so, it will be much easier for the audience to know where you’re headed. Your visual will be more focused and more impactful.

現在，當您在可視化中添加內容時，僅選擇與該核心消息相關的那些位。 如果您這樣做的話，聽眾將更容易知道您的去向。 您的視覺效果將更加集中且更具影響力。

4 /將零件放在正確的位置 (4/ Put the Parts in the Right Place)

I love this quote from Quintilian on the importance of structure:

我喜歡Quintilian所說的結構重要性：

<…> though all the limbs of a statue be cast, it is not a statue until they are united, and if, in our own bodies or those of any other animals, we were to displace or alter the position of any part, they would be but monsters, though they had the same number of parts.

<…>盡管雕像的所有四肢都被鑄造，但直到它們團結起來才成為雕像，如果在我們自己或任何其他動物的身體中，我們要替換或改變任何部位的位置，盡管零件數量相同，但它們只是怪物。

He paints quite an image, doesn’t he!

他畫的很漂亮，不是嗎！

It’s customary to divide a speech into three parts: introduction, body and conclusion. I’m sure you already know this from school. What you may not have thought of is that you can (and often should!) apply this structure to data visualisation, too.

通常將演講分為三個部分： 緒論 ， 正文和結論 。 我確定您已經從學校知道這一點。 您可能沒有想到的是，您也可以(而且經常應該！)將這種結構應用于數據可視化。

To understand how, let’s look at Ludovic Tavernier’s visualisation I introduced in the previous section.

要了解其方式，讓我們看一下我在上一節中介紹的Ludovic Tavernier的可視化。

Introduction

介紹

The objective of an introduction is to hook the audience, to incite curiosity, and to show them what the story will be about.

簡介的目的是吸引觀眾，激發好奇心，并向他們展示故事的內容。

An introduction in data visualisation can comprise the title and the subtitle, the explanatory paragraph, and perhaps the first chart that provides context in a dense visualisation or an infographic.

數據可視化的介紹可以包括標題和副標題，說明性段落，也可以包括在密集的可視化或信息圖中提供上下文的第一個圖表。

In Ludovic’s visualisation (excerpt on the left), the reader’s attention is immediately captured with the two brief stories in the map and the strong title. Then, the reader is drawn further into the topic through the touching human story in the first paragraph.

在Ludovic的可視化效果中(左側摘錄)，通過地圖中的兩個簡短故事和強標題立即抓住了讀者的注意力。 然后，通過第一段中感人的人類故事進一步吸引讀者進入該主題。

Body

身體

This is the meat of your visualisation, where you explain your message. In each part of the body, reveal something the audience doesn’t know yet, and then build on it, brick by brick.

這是您可視化的內容，您可以在其中解釋您的信息。 在身體的每個部分中，揭示觀眾尚不知道的內容，然后在其上逐塊建立。

Ludovic created three charts in the body of his visualisation (see below). He introduced three bits of information: the overall decrease in the number of accepted refugees, the situation by state and then its evolution over a longer period of time. Each of the graphs builds on the previous one, and once we’re done reading them, we understand the depth of the topic better.

Ludovic在其可視化主體中創建了三個圖表(請參見下文)。 他介紹了三點信息：被接納的難民人數總體減少，各州的情況，然后是較長時期的演變。 每個圖都建立在前一個圖的基礎上，閱讀完這些圖后，我們會更好地理解主題的深度。

Conclusion

結論

This is where you summarise, provide a takeaway, add a call to action or open a bigger debate. In data design, the conclusion can take the form of a simple sentence, an action button, or even a visual.

在這里，您可以進行總結，提供總結，呼吁采取行動或展開更大的辯論。 在數據設計中，結論可以采取簡單的句子，操作按鈕甚至視覺效果的形式。

Ludovic chose to talk about the political situation in the US as a potential cause for the issues he described, leaving us with some food for thought.

盧多維奇選擇談論美國的政治局勢，這是他所描述問題的潛在原因，這使我們有了一些思考的機會。

Structuring your visual well will make it easier for the reader to navigate it and will keep them engaged. Even if you’re not making a long infographic like Ludovic, you can still work with this structure. In a smaller visual, the introduction will be the title and the subtitle, the body will be the main chart area with its annotations, and the conclusion will be the biggest call-out, highlight or note at the end.

良好地構建視覺效果將使讀者更輕松地進行導航，并使他們保持參與。 即使您沒有制作像Ludovic這樣的冗長的信息圖，您仍然可以使用此結構。 在較小的外觀中，簡介將是標題和副標題，正文將是帶有注釋的主要圖表區域，結論將是最后的最大標注，突出顯示或注釋。

As an example, see Alli Torban’s visualisation on real-estate below.

例如，請參見下面的Alli Torban房地產可視化。

5 /敲右聲 (5/ Strike the Right Tone)

Imagine a scientist defending their PhD dissertation and a mother telling a bedtime story to her toddler. How will their speeches be different? The scientist will probably use complex terms and speak in a serious voice. The mother will be more creative and playful. The ancient Greek philosophers called this decorum — adapting the style of a speech to its audience and theme.

想象一下，一位科學家為自己的博士學位論文辯護，而一位母親在給孩子講睡前故事。 他們的演講會有何不同？ 科學家可能會使用復雜的術語并以嚴肅的態度說話。 母親會變得更有創造力和頑皮。 古希臘哲學家稱之為“ 禮節” ，使演講風格適應聽眾和主題。

What’s decorum in data design? It covers your stylistic choices: colour, typefaces and illustrations. When reporting on a sensitive topic — the coronavirus pandemic, for example — it’s best to avoid rainbow colour palettes and fun fonts. You have much more freedom, though, when you work on a lighter topic with lower stakes. This is what Sarah Bartlett did with her European cities on a budget visualisation, shown at left. She used a creative typeface for the titles, many colours and icons.

數據設計中的什么禮節？ 它涵蓋了您的風格選擇：顏色，字體和插圖。 報告敏感主題時(例如，冠狀病毒大流行)，最好避免使用彩虹色調色板和有趣的字體。 但是，當您以較低的賭注從事較輕的話題時，您將擁有更多的自由。 這是莎拉·巴特利特(Sarah Bartlett) 在預算可視化中對歐洲城市所做的工作，如左圖所示。 她為標題，許多顏色和圖標使用了創新的字體。

Decorum is how your audience will decide if they can take you seriously, and if they want to engage with the visual. Don’t take it lightly!

觀眾可以通過Decorum決定他們是否可以認真對待您，以及他們是否希望與視覺互動。 不要掉以輕心！

6 /少即是多 (6/ Less is More)

As speech needs to be digested by the listener right away, short and simple words and sentences work best. You need to get your message across in as few words as possible, or, in other terms — less is more. A brilliant example is one of the most famous speeches in history, President Lincoln’s Gettysburg Address. With only 271 words, Lincoln inspired the audience and made them forget the hours of speech that came before him.

由于聽眾必須立即消化語音，因此簡短的單詞和句子效果最佳。 您需要用盡可能少的詞來傳達您的信息，或者換句話說， 少即是多 。 一個杰出的例子是歷史上最著名的演講之一， 林肯總統的《葛底斯堡演說》 。 林肯只有271個字，激發了聽眾的靈感，使他們忘記了面前的演講時間。

In data visualisation, the less is more principle also applies. While orators remove unnecessary words from their speech, you should remove any design elements that do not add value. Antoine de Saint Exupéry said, “Perfection is achieved not when there is nothing more to add, but when there is nothing left to take away.”

在數據可視化中，越少越多的原則也適用。 當演說者從他們的演講中刪除不必要的單詞時，您應該刪除所有不會增加價值的設計元素。 Antoine de SaintExupéry說：“完美的實現不是在沒有其他可添加的東西時，而是在沒有其他東西可以拿走時實現的。”

Keep that in mind for your next project. When you think you’re ready to publish, go through the visual again and ask yourself: is there anything else I could remove?

請記住下一個項目。 當您認為準備發布時，請再次瀏覽視覺圖并問自己： 還有什么我可以刪除的？

7 /讓它呼吸 (7/ Let It Breathe)

Think of the last time you were listening to someone who was speaking very, very fast. How did it feel? Was it difficult to follow, difficult to understand? Or was it confusing? Tiring? Now think about the opposite — the way President Obama speaks. It’s pleasant to the ear because he takes his time and pauses often.

想想您上次聽某人說話的時間非常非常快。 感覺如何？ 難以理解，難以理解嗎？ 還是令人困惑？ 累嗎 現在想想相反的事情-奧巴馬總統的講話方式。 耳朵令人愉悅，因為他會花費時間并經常停下來。

Pauses are a crucial part of any spoken expression. A speaker needs to pause so that the audience has time to digest what they’ve just heard. A pause can also give emphasis to an important part of the message.

暫停是任何口頭表達的關鍵部分。 演講者需要暫停一下，以便聽眾有時間消化自己剛才聽到的內容。 停頓也可以強調消息的重要部分。

In a data visualisation, white space is a pause. Leaving enough white — or negative — space will allow the audience to go through the visual in a calm and pleasant fashion.

在數據可視化中， 空白是一個暫停。 留出足夠的白色(或負性)空間將使觀眾以一種平靜而愉悅的方式觀看視覺效果。

Let’s illustrate this with an example. Below are two versions of the same visualisation. The version on the left is the equivalent of a fast-spoken-difficult-to-digest speech. The version on the right side, on the other hand, includes negative space that allows the visual to breathe.

讓我們用一個例子來說明。 以下是相同可視化的兩個版本。 左側的版本相當于快速語音，難以消化的語音。 另一方面，右側的版本包含負空間，可以使視覺呼吸。

It’s not easy to decide how much white space to add and where. If you need tips, graphic design techniques are your best shot. I suggest you start with this article from the Interaction Design Foundation.

決定要添加多少空白以及在何處是不容易的。 如果您需要技巧，圖形設計技術是您的最佳選擇。 我建議您從Interaction Design Foundation的這篇文章開始。

8 /大膽但不要尖叫 (8/ Be Bold, but Don’t Scream)

Think of the last time you were telling a story to a friend. Can you remember what your voice sounded like and how your body moved? You probably told most of the story in your natural voice. At a few occasions, you may have gotten excited, shouted something out, or added a swing of an arm. Those are the bold moments in the story: by changing your voice and body language, you show the listener that this is important. You can only do it sparingly, though, or you’ll overwhelm them.

想想您上一次向朋友講故事的時候。 您還記得您的聲音聽起來像什么以及您的身體如何運動嗎？ 您可能以自然的聲音講述了大部分故事。 在某些情況下，您可能會感到興奮，大聲喊叫或增加了手臂的擺動。 這些就是故事中的大膽時刻：通過改變聲音和肢體語言，您可以向聽眾表明這很重要 。 但是，您只能謹慎地這樣做，否則您將不堪重負。

In a data story, you also create bold moments. One of the most common ways to do so is with colour. You use colour to make something important stand out, to draw the reader’s attention to key data points. However, the same way you don’t want to listen to a friend scream through an entire ten minute story, your data readers don’t want to be screamed at either.

在數據故事中，您還創建了大膽的時刻。 最常見的方法之一是使用顏色。 您可以使用顏色使重要的事物脫穎而出，以吸引讀者注意關鍵數據點。 但是，就像您不想聽整個十分鐘故事中的朋友的尖叫一樣，您的數據讀取器也不想被任何一個尖叫。

So how can you moderate colour usage? I like the 60–30–10 rule from interior design: 60 percent of the space should be a dominant colour, 30 percent a secondary colour and only 10 percent the accent colour. Just like in the example from FiveThirtyEight on the left.

那么如何調節顏色使用率呢？ 我喜歡室內設計的60–30–10規則：60％的空間應為主色調，30％為第二色，而僅10％為強調色。 就像左邊的FiveThirtyEight中的示例一樣。

9 /測試 (9/ Test It)

If you’ve ever made a speech or a presentation, you were probably told to practice in front of others. But what for? After working on the script on your own for a while, you get too used to it. Complicated sentences start to sound normal, and gaps in reasoning go unnoticed. Rehearsing in front of people helps fix that. You collect feedback, and then improve your speech.

如果您曾經做過演講或演示，則可能被告知要在他人面前練習。 但是，為什么呢？ 自行處理腳本一段時間后，您會逐漸習慣它。 復雜的句子開始聽起來很正常，推理中的空白也沒有引起注意。 在人們面前排練有助于解決這一問題。 您收集反饋，然后改進您的語音。

The same applies to data visualisations. You should collect at least one person’s feedback on how they perceive the visual. That person doesn’t need to be an expert — they can be your friend, your spouse or even your mom. Federica Fragapane, a famous Italian information designer, shares her creations with her mom over WhatsApp.

數據可視化也是如此。 您應該收集至少一個人對他們如何看待視覺的反饋。 該人不必是專家-他們可以是您的朋友，您的配偶甚至您的媽媽。 著名的意大利信息設計師Federica Fragapane通過WhatsApp與媽媽分享了她的創作。

The questions you ask to receive constructive criticism are important. I wrote a quick blog post that can help you get the most from that experience.

您要求接受建設性批評的問題很重要。 我寫了一篇簡短的博客文章 ，可以幫助您充分利用這種經驗。

What’s your favourite speech of all time? One of mine is Martin Luther King Jr.’s I Have a Dream. This speech still resonates and inspires us to fight racism, even though it was delivered nearly sixty years ago. Data visualisation can have the same effect. We still talk about Florence Nightingale’s revolutionary work, for instance.

您最喜歡的演講是什么？ 我的一個人是馬丁·路德·金(Martin Luther King Jr.)的《 我有一個夢想》 。 盡管這是將近六十年前的言論，但它仍然引起共鳴并激發我們與種族主義作斗爭。 數據可視化可以具有相同的效果。 例如，我們仍然談論佛羅倫薩·南丁格爾的革命性工作。

This year proved — once again—that data visuals can have a profound impact on our society. Washington Post’s coronavirus simulator was their most-read story of all time. It changed the way we understand the virus and the way we act.

今年再次證明了數據視覺可以對我們的社會產生深遠的影響。 《華盛頓郵報》的冠狀病毒模擬器是他們有史以來最受歡迎的故事。 它改變了我們了解病毒和行為的方式。

To create such impactful and long-lasting data visualisation work, imagine it as a speech. What will you teach the audience? How will you make sure your message remains memorable years from now?

要創建如此有影響力且持久的數據可視化工作，請將其想象為演講。 您將教觀眾什么？ 從現在開始，如何確保您的信息仍然令人難忘？