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  • It feels like we're all suffering

    目前看起來,

  • from information overload or data glut.

    我們正在承受資訊的過度氾濫。

  • And the good news is there might be an easy solution to that,

    好消息是,現在有一個簡單的方式,

  • and that's using our eyes more.

    讓我們能有效的理解這些資訊。

  • So, visualizing information, so that we can see

    在視覺化資訊中,

  • the patterns and connections that matter

    我們能瞭解資料的模式與關連性,

  • and then designing that information so it makes more sense,

    資訊經過設計,會讓資訊更有意義,

  • or it tells a story,

    甚至陳述某個故事,

  • or allows us to focus only on the information that's important.

    或是引領我們專注在資料的重點上。

  • Failing that, visualized information can just look really cool.

    視覺化資訊可不僅僅是看起來很酷炫的東西。

  • So, let's see.

    讓我們一起來看看。

  • This is the $Billion Dollar o-Gram,

    這是"十億美元圖表(Billion Dollar Gram)",

  • and this image arose

    這張圖是在與媒體界接觸了

  • out of frustration I had

    各種以十億美元為單位的事件後,

  • with the reporting of billion-dollar amounts in the press.

    讓我感到沮喪的情形下,所繪製出來的。

  • That is, they're meaningless without context:

    然而,沒有內容,數字就沒有意義。

  • 500 billion for this pipeline,

    輸油管花了5千億美金。

  • 20 billion for this war.

    戰爭花了2百億美金。

  • It doesn't make any sense, so the only way to understand it

    為了體會這些金額大小的意義,我們只能透過

  • is visually and relatively.

    視覺化還有相對性。

  • So I scraped a load of reported figures

    所以,我從各種不同的來源

  • from various news outlets

    蒐集了許多相關報導的數字,

  • and then scaled the boxes according to those amounts.

    然後根據數字設定格子大小。

  • And the colors here represent the motivation behind the money.

    而顏色代表的是使用這些金錢的動機。

  • So purple is "fighting,"

    像紫色是戰爭,

  • and red is "giving money away," and green is "profiteering."

    紅色是贈送,綠色是收益。

  • And what you can see straight away

    這樣就讓各位能直接了解

  • is you start to have a different relationship to the numbers.

    這些數字之間的差異。

  • You can literally see them.

    讓各位能更快的了解。

  • But more importantly, you start to see

    但更重要的是,

  • patterns and connections between numbers

    這能讓各位發現,在過去各種報導中,

  • that would otherwise be scattered across multiple news reports.

    這些數字間未被提起的模式與關連性。

  • Let me point out some that I really like.

    讓我來告訴各位其中隱藏的事實。

  • This is OPEC's revenue, this green box here --

    這塊綠色是OPEC(石油輸出國組織)的總收益,

  • 780 billion a year.

    一年7800億美金。

  • And this little pixel in the corner -- three billion --

    右下角這一小塊,30億美金,

  • that's their climate change fund.

    是該組織投資的氣候變遷基金。

  • Americans, incredibly generous people --

    而極度慷慨的美國人,

  • over 300 billion a year, donated to charity every year,

    每年做慈善的金額都超過3000億美金,

  • compared with the amount of foreign aid

    相較於其他前17大工業國,

  • given by the top 17 industrialized nations

    它們每年所捐增的總額

  • at 120 billion.

    也不過1200億美金。

  • Then of course,

    當然,

  • the Iraq War, predicted to cost just 60 billion

    伊拉克戰爭,在2003年時,

  • back in 2003.

    預計只需要花600億美金。

  • And it mushroomed slightly. Afghanistan and Iraq mushroomed now

    這數字後來爆增。阿富汗/伊拉克戰爭目前開銷

  • to 3,000 billion.

    已經來到3兆美金。

  • So now it's great

    非常龐大的數字,

  • because now we have this texture, and we can add numbers to it as well.

    因為我們有前車之鑑,這個數字也會再往上調整。

  • So we could say, well, a new figure comes out ... let's see African debt.

    讓我們看另一個新的數字... 非洲的負債。

  • How much of this diagram do you think might be taken up

    各位猜猜非洲各國的負債中

  • by the debt that Africa owes to the West?

    西方國家持有多少?

  • Let's take a look.

    讓我們看看。

  • So there it is:

    來了,

  • 227 billion is what Africa owes.

    目前非洲各國的負債金額是2270億美金。

  • And the recent financial crisis,

    而最近的金融風暴....

  • how much of this diagram might that figure take up?

    各位認為這個數字的色塊是怎樣?

  • What has that cost the world? Let's take a look at that.

    這個事件造成的成本是多少?讓我們來瞧瞧。

  • Dooosh -- Which I think is the appropriate sound effect

    夭壽。這大概是最適合的形容詞了。

  • for that much money:

    這麼大一筆的數字。

  • 11,900 billion.

    11兆9000億美金。

  • So, by visualizing this information,

    所以,資訊透過視覺化,

  • we turned it into a landscape

    資訊會呈現為圖像,

  • that you can explore with your eyes,

    你就能用眼睛尋找蛛絲馬跡,

  • a kind of map really, a sort of information map.

    就像是某種資訊地圖。

  • And when you're lost in information,

    當你被大量資訊迷惑時,

  • an information map is kind of useful.

    這種資訊地圖就能派上用場。

  • So I want to show you another landscape now.

    現在,我要給各位看看另一種圖像。

  • We need to imagine what a landscape

    各位想像一下,

  • of the world's fears might look like.

    把世界上令人驚恐的事件,用圖形表示會是怎樣。

  • Let's take a look.

    讓我們來看看。

  • This is Mountains Out of Molehills,

    這圖叫"小題大作(mountains out of mole hills)",

  • a timeline of global media panic.

    這張圖是全球媒體造成恐慌的時間軸。

  • (Laughter)

    (笑)

  • So, I'll label this for you in a second.

    讓我很快的講解一下圖表。

  • But the height here, I want to point out,

    色塊的高低起伏,

  • is the intensity of certain fears

    是指某特定事件

  • as reported in the media.

    在某時段被媒體報導的強度。

  • Let me point them out.

    讓我為各位說明顏色的意義。

  • So this, swine flu -- pink.

    粉紅色的是豬流感。

  • Bird flu.

    這是禽流感。

  • SARS -- brownish here. Remember that one?

    SARS,是這個淡褐色的,

  • The millennium bug,

    這是千禧蟲事件,

  • terrible disaster.

    可怕的電腦病毒。

  • These little green peaks

    這些小小的綠色部分,

  • are asteroid collisions.

    是小行星撞擊地球的消息。

  • (Laughter)

    (笑)

  • And in summer, here, killer wasps.

    這是今年夏天的殺人峰事件。

  • (Laughter)

    (笑)

  • So these are what our fears look like

    這些是從媒體開始報導到結束之間

  • over time in our media.

    對這些事件報導的程度。

  • But what I love -- and I'm a journalist --

    因為我是個記者,

  • and what I love is finding hidden patterns; I love being a data detective.

    所以我喜歡尋找那隱藏的模式,我喜歡當個資料偵探。

  • And there's a very interesting and odd pattern hidden in this data

    資料中總是隱藏著有趣且古怪的模式,

  • that you can only see when you visualize it.

    除了把資料視覺化,不然根本沒辦法發覺。

  • Let me highlight it for you.

    讓我為各位點出這些地方。

  • See this line, this is a landscape for violent video games.

    紅色部分,是針對暴力電玩的報導強度。

  • As you can see, there's a kind of odd, regular pattern in the data,

    各位可以看到,有點奇怪,資料出現了一些規律,

  • twin peaks every year.

    每年的報導都出現2次尖峰。

  • If we look closer, we see those peaks occur

    若我們仔細看,我們能發現這2次尖峰,

  • at the same month every year.

    都是發生在特定的月份。

  • Why?

    為什麼?

  • Well, November, Christmas video games come out,

    因為耶誕節前,電玩遊戲會紛紛在11月推出,

  • and there may well be an upsurge in the concern about their content.

    所以很多媒體就會針對這些遊戲內容做出評論。

  • But April isn't a particularly massive month

    但四月對電玩業者而言,

  • for video games.

    又不是什麼重要的月份。

  • Why April?

    為什麼四月也會這樣?

  • Well, in April 1999 was the Columbine shooting,

    因為1999年4月發生了科倫拜校園槍擊事件,

  • and since then, that fear

    從那時候開始,

  • has been remembered by the media

    這件事情就被媒體銘記,

  • and echoes through the group mind gradually through the year.

    並在每年的這個時候重新報導。

  • You have retrospectives, anniversaries,

    像是回顧展、周年紀念日、

  • court cases, even copy-cat shootings,

    法庭案件、甚至有模仿的槍擊事件,

  • all pushing that fear into the agenda.

    這些助力讓此事件一再的被報導。

  • And there's another pattern here as well. Can you spot it?

    這裡面其實還有一個模式,各位注意到了嗎?

  • See that gap there? There's a gap,

    看到這個缺口了嗎?

  • and it affects all the other stories.

    這個大缺口是其他事件所導致的。

  • Why is there a gap there?

    是什麼事件?

  • You see where it starts? September 2001,

    這缺口從什麼時候開始的? 2001年9月。

  • when we had something very real

    因為這個時間點

  • to be scared about.

    我們有個最令人驚悚的(911)事件。

  • So, I've been working as a data journalist for about a year,

    我作為資料記者大約已經一年的時間。

  • and I keep hearing a phrase

    這期間我常聽到一句話

  • all the time, which is this:

    這句話就是:

  • "Data is the new oil."

    "資料是種新石油"

  • Data is the kind of ubiquitous resource

    資料就像是某種普遍的資源,

  • that we can shape to provide new innovations and new insights,

    我們可以使之塑形,以提供我們新思想跟新洞察,

  • and it's all around us, and it can be mined very easily.

    這種資源就在我們身邊,非常容易取得。

  • It's not a particularly great metaphor in these times,

    現在這時間點,是不太適合把資料比喻成石油,

  • especially if you live around the Gulf of Mexico,

    尤其是如果你住在墨西哥灣附近的話,

  • but I would, perhaps, adapt this metaphor slightly,

    但其實我只對這種比方贊同一點點,

  • and I would say that data is the new soil.

    我認為,"資料是一種新土壤"。

  • Because for me, it feels like a fertile, creative medium.

    對我來說,資料就像是一種肥沃、有創造力的媒介。

  • Over the years, online,

    過去幾年,

  • we've laid down

    我們已經在網路上

  • a huge amount of information and data,

    放置了非常大量的資訊和資料,

  • and we irrigate it with networks and connectivity,

    我們利用網路和連結灌溉它們,

  • and it's been worked and tilled by unpaid workers and governments.

    透過政府和網路志工在這上面不斷耕種。

  • And, all right, I'm kind of milking the metaphor a little bit.

    喔,對啦,我也可以用擠奶作為譬喻。

  • But it's a really fertile medium,

    這是非常豐沃的媒介,

  • and it feels like visualizations, infographics, data visualizations,

    形象、圖表資料、視覺化資料,

  • they feel like flowers blooming from this medium.

    都像是從這媒介中,生長出來的茂盛花海。

  • But if you look at it directly,

    不過,若直接觀看資料圖表,

  • it's just a lot of numbers and disconnected facts.

    看起來就像一堆數字,和一堆不相干的事件。

  • But if you start working with it and playing with it in a certain way,

    如果將這些資訊用特別的方式整理一下,

  • interesting things can appear and different patterns can be revealed.

    有趣的事情就會浮現,各式各樣的模式就會顯露出來了。

  • Let me show you this.

    讓我示範給各位看。

  • Can you guess what this data set is?

    各位能猜到這些資料在陳述什麼嗎?

  • What rises twice a year,

    1年內會出現2次尖峰,

  • once in Easter

    一次是在復活節(3、4月),

  • and then two weeks before Christmas,

    另一次是聖誕節的前2周,

  • has a mini peak every Monday,

    而每星期的星期一都會有一次小高峰,

  • and then flattens out over the summer?

    然後在夏天的時候特別平穩。

  • I'll take answers.

    有人要猜猜看嗎?

  • (Audience: Chocolate.) David McCandless: Chocolate.

    觀眾:巧克力。

  • You might want to get some chocolate in.

    這跟巧克力有一點點相關。

  • Any other guesses?

    有其他答案嗎?

  • (Audience: Shopping.) DM: Shopping.

    觀眾:購物。

  • Yeah, retail therapy might help.

    購物也許能紓緩這件事。

  • (Audience: Sick leave.)

    觀眾:請病假。

  • DM: Sick leave. Yeah, you'll definitely want to take some time off.

    請病假。對,這時候會想要休息一下。

  • Shall we see?

    答案揭曉摟。

  • (Laughter)

    (分手潮---資料來源:Facebook的狀態更新)

  • (Applause)

    (掌聲)

  • So, the information guru Lee Byron and myself,

    Lee Byron和我一起做這項統計,

  • we scraped 10,000 status Facebook updates

    我們抓了1萬筆Facebook上的個人狀態,

  • for the phrase "break-up" and "broken-up"

    關鍵字是"分手",

  • and this is the pattern we found --

    然後我們發現了這個模式,

  • people clearing out for Spring Break,

    春假前先分手(才能玩樂)

  • (Laughter)

    (笑)

  • coming out of very bad weekends on a Monday,

    在度過了幾個糟糕週末後的星期一,

  • being single over the summer,

    然後單身渡過整個夏天。

  • and then the lowest day of the year, of course: Christmas Day.

    接下來是一整年分手數的最低點,聖誕節。

  • Who would do that?

    誰會在這時候分手阿?

  • So there's a titanic amount of data out there now,

    現在我們有許多的數據,

  • unprecedented.

    是前所未有的。

  • But if you ask the right kind of question,

    不過,若你的質疑正確,

  • or you work it in the right kind of way,

    或是你蒐集正確的資料,

  • interesting things can emerge.

    有趣的事情就會跑出來。

  • So information is beautiful. Data is beautiful.

    資訊是美麗的,資料是美麗的。

  • I wonder if I could make my life beautiful.

    我希望將我的人生弄的很美麗。

  • And here's my visual C.V.

    這是我的"視覺履歷"(visual C.V)。

  • I'm not quite sure I've succeeded.

    我不太確定是否成功了。

  • Pretty blocky, the colors aren't that great.

    上色的小方塊。顏色不是這麼好看。

  • But I wanted to convey something to you.

    但我想傳達一些訊息給各位。

  • I started as a programmer,

    我第一份工作是程式設計師,

  • and then I worked as a writer for many years, about 20 years,

    然後我當作家大約20年,

  • in print, online and then in advertising,

    作品出版後,我又進了廣告業,

  • and only recently have I started designing.

    直到最近我才開始從事設計。

  • And I've never been to design school.

    我從未接受設計方面的教育。

  • I've never studied art or anything.

    也從來沒學過任何美術學科。

  • I just kind of learned through doing.

    我透過實作來學習。

  • And when I started designing,

    當我開始從事設計的時候,

  • I discovered an odd thing about myself.

    我就發現自己有些怪怪的。

  • I already knew how to design,

    雖然我已經知道該如何設計,

  • but it wasn't like I was amazingly brilliant at it,

    但是結果並不如我想像中的令人驚奇,

  • but more like I was sensitive

    而我對某些元素相當敏感,

  • to the ideas of grids and space

    像是方格、空間、

  • and alignment and typography.

    直線對齊、排版設計。

  • It's almost like being exposed

    可能是因為

  • to all this media over the years

    我過去這幾年都在媒體界工作

  • had instilled a kind of dormant design literacy in me.

    而那類型的設計素養就被深植在腦中。

  • And I don't feel like I'm unique.

    我不覺得我是獨一無二的。

  • I feel that everyday, all of us now

    我只是感覺到,人們每天

  • are being blasted by information design.

    都被資訊設計(information design)所轟炸。

  • It's being poured into our eyes through the Web,

    透過網頁不斷注入到我們的眼睛裡,

  • and we're all visualizers now;

    我們都善於在腦海中想像,

  • we're all demanding a visual aspect

    因此我們需要將資訊

  • to our information.

    呈現為視覺化的面貌。

  • There's something almost quite magical about visual information.

    視覺資訊有一些地方是很不可思議的。

  • It's effortless, it literally pours in.

    它很簡單,確實地融入我們。

  • And if you're navigating a dense information jungle,

    若你想引領人們在濃密的資訊叢林中航行,

  • coming across a beautiful graphic

    透過華麗的圖像

  • or a lovely data visualization,

    或是美麗的視覺化資訊,

  • it's a relief, it's like coming across a clearing in the jungle.

    那就輕鬆多了,這就變成像是通過叢林中的空地。

  • I was curious about this, so it led me

    我對這方面的知識相當好奇,

  • to the work of a Danish physicist

    因此我與一位丹麥物理學家合作

  • called Tor Norretranders,

    他叫Tor Norretranders,

  • and he converted the bandwidth of the senses into computer terms.

    他將人的感官寬帶轉換成電腦用語。

  • So here we go. This is your senses,

    開始了,這是你的感官,

  • pouring into your senses every second.

    你的感官時時刻刻都在接受資訊。

  • Your sense of sight is the fastest.

    視覺對資訊的反應是最快的。

  • It has the same bandwidth as a computer network.

    就像是電腦寬頻網路的速度。

  • Then you have touch, which is about the speed of a USB key.

    然後是觸覺,大概像USB傳輸的速度。

  • And then you have hearing and smell,

    接下來才是你的聽覺和嗅覺,

  • which has the throughput of a hard disk.

    這就像硬碟的存取速度。

  • And then you have poor old taste,

    然後是緩慢的味覺,

  • which is like barely the throughput of a pocket calculator.

    它的反應速度大概就像計算機的存取速度。

  • And that little square in the corner, a naught .7 percent,

    在角落有個小方塊,大概佔感官的0.7%,

  • that's the amount we're actually aware of.

    這是我們真正的意識。

  • So a lot of your vision --

    你透過眼睛接受的大量資訊,

  • the bulk of it is visual, and it's pouring in.

    像圖中的大方塊般龐大,不停的灌入。

  • It's unconscious.

    這過程是無意識的。

  • The eye is exquisitely sensitive

    而且眼睛對於圖形的顏色、形狀、組合模式,

  • to patterns in variations in color, shape and pattern.

    是非常敏感的。

  • It loves them, and it calls them beautiful.

    眼睛喜愛這些圖形,認為它們很美麗。

  • It's the language of the eye.

    這是眼睛的語言。

  • If you combine the language of the eye with the language of the mind,

    若你把眼睛和心靈的語言組合起來,

  • which is about words and numbers and concepts,

    這二者都針對文字、數字、概念的陳述,

  • you start speaking two languages simultaneously,

    你便能同時述說二種語言,

  • each enhancing the other.

    就能增加兩者的感受。

  • So, you have the eye, and then you drop in the concepts.

    所以,用眼睛看某事物時,心裡就會出現概念。

  • And that whole thing -- it's two languages

    而這整個過程,是因為

  • both working at the same time.

    這二種語言同時運作的關係。

  • So we can use this new kind of language, if you like,

    若你願意,我們能用另一種新語言,

  • to alter our perspective or change our views.

    這種語言可以改變我們的認知和觀點。

  • Let me ask you a simple question

    讓我問各位一個簡單的問題,

  • with a really simple answer:

    只需要簡短的答案。

  • Who has the biggest military budget?

    哪個國家的軍事預算最高?

  • It's got to be America, right?

    就是美國了,對吧?

  • Massive. 609 billion in 2008 --

    非常龐大的數字。2008年的6090億..

  • 607, rather.

    更正,是6070億。

  • So massive, in fact, that it can contain

    實際上,這麼大的數字,

  • all the other military budgets in the world inside itself.

    可以吃下全世界其他國家軍事預算的總和。

  • Gobble, gobble, gobble, gobble, gobble.

    幾乎吃個精光。

  • Now, you can see Africa's total debt there

    我們用非洲國家的總負債(中間方塊)

  • and the U.K. budget deficit for reference.

    和英國預算赤字(右側方塊)做個比較。

  • So that might well chime

    這應該也符合

  • with your view that America

    各位對美國的看法,

  • is a sort of warmongering military machine,

    像是好戰者、戰爭機器、

  • out to overpower the world

    企圖征服世界、

  • with its huge industrial-military complex.

    大號的軍事工業複合體(industrial-military complex)。

  • But is it true that America has the biggest military budget?

    但是美國真的是擁有最高國防預算的國家嗎?

  • Because America is an incredibly rich country.

    因為美國是個非常富有的國家。

  • In fact, it's so massively rich

    事實上,美國的富有程度,

  • that it can contain the four other

    能包含世界上

  • top industrialized nations' economies

    前4大工業國家的經濟產值

  • inside itself, it's so vastly rich.

    實在是非常富有。

  • So its military budget is bound to be enormous.

    所以這樣的國家,軍事預算自然就龐大。

  • So, to be fair and to alter our perspective,

    要從公平的角度,來調整我們的認知,

  • we have to bring in another data set,

    我們得要有另一套資料來分析,

  • and that data set is GDP, or the country's earnings.

    這套資料就是GDP,或說是一國的收入。

  • Who has the biggest budget as a proportion of GDP?

    哪一國的軍事預算佔GDP最重?

  • Let's have a look.

    讓我們來瞧瞧。

  • That changes the picture considerably.

    圖形跟剛剛有很大的不同喔。

  • Other countries pop into view that you, perhaps, weren't considering,

    很多國家都跑出來了,搞不好這些國家你想都沒想過,

  • and American drops into eighth.

    美國的名次掉到第8了。

  • Now you can also do this with soldiers.

    現在我們來看看有關軍人的部份。

  • Who has the most soldiers? It's got to be China.

    誰擁有的軍人最多?應該是中國。

  • Of course, 2.1 million.

    沒錯,210萬人。

  • Again, chiming with your view

    又來了,再度符合各位的印象,

  • that China has a militarized regime

    因為中國是個軍事主義政權,

  • ready to, you know, mobilize its enormous forces.

    像是隨時要展現他們強大的武力。

  • But of course, China has an enormous population.

    但事實上,中國擁有龐大的人口。

  • So if we do the same,

    若我們做跟剛剛一樣的事,

  • we see a radically different picture.

    我們就會看到非常不一樣的圖形。

  • China drops to 124th.

    中國掉到了第124名。

  • It actually has a tiny army

    從另一種資料面來看,

  • when you take other data into consideration.

    中國的軍隊規模實在有夠小。

  • So, absolute figures, like the military budget,

    像軍事預算這種絕對數字,

  • in a connected world,

    在這互相連結的世界裡,

  • don't give you the whole picture.

    反而沒辦法讓你看到完整的事實。

  • They're not as true as they could be.

    事物的真相不如它表面所示。

  • We need relative figures that are connected to other data

    我們需要用其他資料的相關數字作比較,

  • so that we can see a fuller picture,

    這樣才能了解最完整的事實,

  • and then that can lead to us changing our perspective.

    進一步改變我們的認知。

  • As Hans Rosling, the master,

    Hans Rosling教授,

  • my master, said,

    同時也是我的老師,他說:

  • "Let the dataset change your mindset."

    "用數據改變思維"

  • And if it can do that, maybe it can also change your behavior.

    若真能改變思維,那同樣的也能改變你的行為。

  • Take a look at this one.

    各位看這裡。

  • I'm a bit of a health nut.

    我是個注重健康的人。

  • I love taking supplements and being fit,

    雖然我喜歡攝取一些營養品、健身,

  • but I can never understand what's going on in terms of evidence.

    但是我永遠搞不清楚這些東西會帶來的好處。

  • There's always conflicting evidence.

    有很多牴觸的說法。

  • Should I take vitamin C? Should I be taking wheatgrass?

    我應該攝取維他命C嗎?還是應該吃小麥草?

  • This is a visualization of all the evidence

    畫面上所呈現的圖像就是

  • for nutritional supplements.

    營養品所提供好處的圖像化。

  • This kind of diagram is called a balloon race.

    這種圖形稱為熱汽球(balloon race)。

  • So the higher up the image,

    較高的圓圈,

  • the more evidence there is for each supplement.

    是有強烈證據證明其功效的營養品。

  • And the bubbles correspond to popularity as regards to Google hits.

    而圓圈大小是對應在Google上查詢的次數。

  • So you can immediately apprehend

    這樣你就能馬上看出營養品之間,

  • the relationship between efficacy and popularity,

    效果和受歡迎程度的比較。

  • but you can also, if you grade the evidence,

    若再根據這些證據做排序,

  • do a "worth it" line.

    可以畫上一條"值得攝取(worth it)"線。

  • So supplements above this line are worth investigating,

    在這條線上的營養素是最值得探討的,

  • but only for the conditions listed below,

    它們適用於圓圈內下方小字的情況。

  • and then the supplements below the line

    而在這條線之下的營養素,

  • are perhaps not worth investigating.

    其實,並不這麼值得探討。

  • Now this image constitutes a huge amount of work.

    要弄出這張圖片可是件大工程。

  • We scraped like 1,000 studies from PubMed,

    我們從PubMed搜尋引擎中抓出一千多份的研究報告,

  • the biomedical database,

    PubMed會連到生物醫學資料庫,

  • and we compiled them and graded them all.

    然後我們將這些報告做匯整排序。

  • And it was incredibly frustrating for me

    這讓我感到非常沮喪的是,

  • because I had a book of 250 visualizations to do for my book,

    我的書需要有250張的視覺化圖像,

  • and I spent a month doing this,

    然後我花了一個月整理出這堆圈圈,

  • and I only filled two pages.

    卻只能塞滿2頁。

  • But what it points to

    不過,這張圖點出了

  • is that visualizing information like this

    視覺化的資訊

  • is a form of knowledge compression.

    就是一種知識濃縮的型態。

  • It's a way of squeezing an enormous amount

    這種方式能夠壓縮非常大量的

  • of information and understanding

    資訊和知識

  • into a small space.

    濃縮在一起。

  • And once you've curated that data, and once you've cleaned that data,

    透過資料的搜集整頓,

  • and once it's there,

    一但完成,

  • you can do cool stuff like this.

    你也能做出這麼酷炫的東西。

  • So I converted this into an interactive app,

    我將這張圖轉換成一個互動的應用程式,

  • so I can now generate this application online --

    便產生了這個線上應用程式,

  • this is the visualization online --

    這種線上的視覺化程式,

  • and I can say, "Yeah, brilliant."

    我想說:"哇嗚,超棒的"。

  • So it spawns itself.

    這張圖能自己更新資料。

  • And then I can say, "Well, just show me the stuff

    只要我說:"我只想看

  • that affects heart health."

    會影響心臟健康的東西就好"。

  • So let's filter that out.

    點選項,程式會開始過濾。

  • So heart is filtered out, so I can see if I'm curious about that.

    有關心臟保養的營養品就出現了。

  • I think, "No, no. I don't want to take any synthetics,

    如果我想說:"喔不,我是不吃人工合成物的。

  • I just want to see plants and --

    只要告訴我

  • just show me herbs and plants. I've got all the natural ingredients."

    藥草類和植物類食品就行了,我只要天然的成分"。

  • Now this app is spawning itself

    然後這程式又會開始從資料中

  • from the data.

    過濾出想要的資訊。

  • The data is all stored in a Google Doc,

    這些資料會被儲存成Google文件,

  • and it's literally generating itself from that data.

    嚴格來說,資料會自動轉成文件檔案。

  • So the data is now alive; this is a living image,

    因此,這些資料是活的,是個活生生的圖像,

  • and I can update it in a second.

    我只需要幾秒鐘就能更新資料。

  • New evidence comes out. I just change a row on a spreadsheet.

    我只需要改變選單裡的選項,新的資料就跑出來了。

  • Doosh! Again, the image recreates itself.

    再一次,夭壽!這些圖像能自我創造。

  • So it's cool.

    它非常棒。

  • It's kind of living.

    它是活生生的。

  • But it can go beyond data,

    它超越了資料本身,

  • and it can go beyond numbers.

    它能突顯數字的涵意。

  • I like to apply information visualization

    我想要應用資料視覺化的技術

  • to ideas and concepts.

    在各種不同領域上。

  • This is a visualization

    畫面上的是

  • of the political spectrum,

    政治光譜(度量政治傾向的工具)的視覺化。

  • an attempt for me to try

    我試圖了解

  • and understand how it works

    這張圖該怎麼運作,

  • and how the ideas percolate down

    還有政府的立場

  • from government into society and culture,

    該如何滲透到社會、文化、

  • into families, into individuals, into their beliefs

    家庭、個人、甚至到個人信念,

  • and back around again in a cycle.

    然後這個影響關係會形成一個迴圈。

  • What I love about this image

    我喜歡這張圖的地方是

  • is it's made up of concepts,

    它是由許多概念所構成,

  • it explores our worldviews

    它探討了我們當今的世界觀,

  • and it helps us -- it helps me anyway --

    它能幫助我們

  • to see what others think,

    觀察到他人心裡所想,

  • to see where they're coming from.

    並觀察到這些想法從何而來。

  • And it feels just incredibly cool to do that.

    這張圖實在是太棒了。

  • What was most exciting for me

    在設計這張圖時,

  • designing this

    最令我感到興奮的是,

  • was that, when I was designing this image,

    當我正在進行設計的時候,

  • I desperately wanted this side, the left side,

    我拼老命想把左派陣營

  • to be better than the right side --

    弄得比右派陣營好(註:左派提倡自由,右派提倡集權)

  • being a journalist, a Left-leaning person --

    因為我是一位記者、一位左派人士。

  • but I couldn't, because I would have created

    但我不能這樣做,否則會出現

  • a lopsided, biased diagram.

    一個傾斜、具有偏見的圖像。

  • So, in order to really create a full image,

    所以,為了忠實呈現完整的圖像,

  • I had to honor the perspectives on the right-hand side

    我必須要有身為右派人士的榮耀感,

  • and at the same time, uncomfortably recognize

    然而,這過程中,我發現到自己身上

  • how many of those qualities were actually in me,

    也有許多對立者的特質

  • which was very, very annoying and uncomfortable.

    這真的非常討厭和不舒服。

  • (Laughter)

    (笑)

  • But not too uncomfortable,

    其實也沒這麼誇張啦,

  • because there's something unthreatening

    因為這張圖,對於觀察他人政治觀感

  • about seeing a political perspective,

    並不會構成太大的威脅,

  • versus being told or forced to listen to one.

    相對的,還能促使人去聆聽另一方的聲音。

  • You're capable of holding conflicting viewpoints

    這是真的,當你能清楚看見對方的立場,

  • joyously when you can see them.

    就會愉悅地看待衝突的觀念。

  • It's even fun to engage with them

    甚至樂於與對方接觸,

  • because it's visual.

    因為一切視覺化了。

  • So that's what's exciting to me,

    這就是讓我感到興奮的地方,

  • seeing how data can change my perspective

    看到這些美麗、迷人的資料

  • and change my mind midstream --

    是如何改變我們的認知,

  • beautiful, lovely data.

    改變我們根深蒂固的觀念。

  • So, just to wrap up,

    來做個總結,

  • I wanted to say

    我想說的是

  • that it feels to me that design is about solving problems

    我的感覺是,設計能解決問題

  • and providing elegant solutions,

    同時也能提供優雅的解決方案。

  • and information design is about

    資訊設計

  • solving information problems.

    能解決資訊的問題。

  • It feels like we have a lot of information problems

    此時此刻,

  • in our society at the moment,

    我們的社會上擁有許多資訊問題,

  • from the overload and the saturation

    資訊的過載與飽和,

  • to the breakdown of trust and reliability

    使資料的信任度和可靠性受到打擊,

  • and runaway skepticism and lack of transparency,

    引發排山倒海的質疑,透明度也大大降低,

  • or even just interestingness.

    或說失去資料的趣味性。

  • I mean, I find information just too interesting.

    其實資訊是非常有趣的。

  • It has a magnetic quality that draws me in.

    它就像具有磁性般的吸引了我。

  • So, visualizing information

    視覺化的資訊

  • can give us a very quick solution to those kinds of problems.

    能快速的針對各種問題提供解答。

  • Even when the information is terrible,

    即使資訊夾帶的是負面、糟糕的消息,

  • the visual can be quite beautiful.

    視覺化能讓它變的非常美麗。

  • Often we can get clarity

    同時能得到清晰的思維

  • or the answer to a simple question very quickly,

    同時快速的回答簡單的問題,

  • like this one,

    就像這個,

  • the recent Icelandic volcano.

    最近的冰島火山。

  • Which was emitting the most CO2?

    請問是何者排放了最多的二氧化碳?

  • Was it the planes or the volcano,

    是飛機,還是火山,

  • the grounded planes or the volcano?

    是那些停飛的飛機還是火山?(2010/4,冰島火山爆發,造成歐洲航線大亂)

  • So we can have a look.

    我們能看見真相為何。

  • We look at the data and we see:

    各位看看這資料顯示的情形,

  • Yep, the volcano emitted 150,000 tons;

    沒錯,火山釋放了15萬噸的二氧化碳;

  • the grounded planes would have emitted

    而這些飛機如果沒有停飛的話,

  • 345,000 if they were in the sky.

    會釋放34萬5千噸的二氧化碳。

  • So essentially, we had our first carbon-neutral volcano.

    所以實際上,這是我們第一座碳中和火山。

  • (Laughter)

    (笑)

  • (Applause)

    (掌聲)

  • And that is beautiful. Thank you.

    這就是資料的美麗之處,感謝你們。

  • (Applause)

    (掌聲)

It feels like we're all suffering

目前看起來,

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B1 US TED 資料 視覺化 資訊 數字 事件

【TED】David McCandless:數據可視化之美(數據可視化之美|David McCandless) (【TED】David McCandless: The beauty of data visualization (The beauty of data visualization | David McCandless))

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    Karen Chan posted on 2021/01/14
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