It feels like we're all suffering from information overload or data glut. And the good news is there might be an easy solution to that, and that's using our eyes more. So, visualizing information, so that we can see the patterns and connections that matter and then designing that information so it makes more sense, or it tells a story, or allows us to focus only on the information that's important. Failing that, visualized information can just look really cool.
目前看起來, 我們正在承受資訊的過度氾濫。 好消息是,現在有一個簡單的方式, 讓我們能有效的理解這些資訊。 在視覺化資訊中, 我們能瞭解資料的模式與關連性, 資訊經過設計,會讓資訊更有意義, 甚至陳述某個故事, 或是引領我們專注在資料的重點上。 視覺化資訊可不僅僅是看起來很酷炫的東西。
So, let's see. This is the $Billion Dollar o-Gram, and this image arose out of frustration I had with the reporting of billion-dollar amounts in the press. That is, they're meaningless without context: 500 billion for this pipeline, 20 billion for this war. It doesn't make any sense, so the only way to understand it is visually and relatively. So I scraped a load of reported figures from various news outlets and then scaled the boxes according to those amounts. And the colors here represent the motivation behind the money. So purple is "fighting," and red is "giving money away," and green is "profiteering." And what you can see straight away is you start to have a different relationship to the numbers. You can literally see them. But more importantly, you start to see patterns and connections between numbers that would otherwise be scattered across multiple news reports.
讓我們一起來看看。 這是"十億美元圖表(Billion Dollar Gram)", 這張圖是在與媒體界接觸了 各種以十億美元為單位的事件後, 讓我感到沮喪的情形下,所繪製出來的。 然而,沒有內容,數字就沒有意義。 輸油管花了5千億美金。 戰爭花了2百億美金。 為了體會這些金額大小的意義,我們只能透過 視覺化還有相對性。 所以,我從各種不同的來源 蒐集了許多相關報導的數字, 然後根據數字設定格子大小。 而顏色代表的是使用這些金錢的動機。 像紫色是戰爭, 紅色是贈送,綠色是收益。 這樣就讓各位能直接了解 這些數字之間的差異。 讓各位能更快的了解。 但更重要的是, 這能讓各位發現,在過去各種報導中, 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. This is OPEC's revenue, this green box here -- 780 billion a year. And this little pixel in the corner -- three billion -- that's their climate change fund. Americans, incredibly generous people -- over 300 billion a year, donated to charity every year, compared with the amount of foreign aid given by the top 17 industrialized nations at 120 billion. Then of course, the Iraq War, predicted to cost just 60 billion back in 2003. And it mushroomed slightly. Afghanistan and Iraq mushroomed now to 3,000 billion. So now it's great because now we have this texture, and we can add numbers to it as well. So we could say, well, a new figure comes out ... let's see African debt. How much of this diagram do you think might be taken up by the debt that Africa owes to the West? Let's take a look. So there it is: 227 billion is what Africa owes. And the recent financial crisis, how much of this diagram might that figure take up? What has that cost the world? Let's take a look at that. Dooosh -- Which I think is the appropriate sound effect for that much money: 11,900 billion. So, by visualizing this information, we turned it into a landscape that you can explore with your eyes, a kind of map really, a sort of information map. And when you're lost in information, an information map is kind of useful.
讓我來告訴各位其中隱藏的事實。 這塊綠色是OPEC(石油輸出國組織)的總收益, 一年7800億美金。 右下角這一小塊,30億美金, 是該組織投資的氣候變遷基金。 而極度慷慨的美國人, 每年做慈善的金額都超過3000億美金, 相較於其他前17大工業國, 它們每年所捐增的總額 也不過1200億美金。 當然, 伊拉克戰爭,在2003年時, 預計只需要花600億美金。 這數字後來爆增。阿富汗/伊拉克戰爭目前開銷 已經來到3兆美金。 非常龐大的數字, 因為我們有前車之鑑,這個數字也會再往上調整。 讓我們看另一個新的數字... 非洲的負債。 各位猜猜非洲各國的負債中 西方國家持有多少? 讓我們看看。 來了, 目前非洲各國的負債金額是2270億美金。 而最近的金融風暴.... 各位認為這個數字的色塊是怎樣? 這個事件造成的成本是多少?讓我們來瞧瞧。 夭壽。這大概是最適合的形容詞了。 這麼大一筆的數字。 11兆9000億美金。 所以,資訊透過視覺化, 資訊會呈現為圖像, 你就能用眼睛尋找蛛絲馬跡, 就像是某種資訊地圖。 當你被大量資訊迷惑時, 這種資訊地圖就能派上用場。
So I want to show you another landscape now. We need to imagine what a landscape of the world's fears might look like. Let's take a look. This is Mountains Out of Molehills, a timeline of global media panic. (Laughter) So, I'll label this for you in a second. But the height here, I want to point out, is the intensity of certain fears as reported in the media. Let me point them out. So this, swine flu -- pink. Bird flu. SARS -- brownish here. Remember that one? The millennium bug, terrible disaster. These little green peaks are asteroid collisions. (Laughter) And in summer, here, killer wasps.
現在,我要給各位看看另一種圖像。 各位想像一下, 把世界上令人驚恐的事件,用圖形表示會是怎樣。 讓我們來看看。 這圖叫"小題大作(mountains out of mole hills)", 這張圖是全球媒體造成恐慌的時間軸。 (笑) 讓我很快的講解一下圖表。 色塊的高低起伏, 是指某特定事件 在某時段被媒體報導的強度。 讓我為各位說明顏色的意義。 粉紅色的是豬流感。 這是禽流感。 SARS,是這個淡褐色的, 這是千禧蟲事件, 可怕的電腦病毒。 這些小小的綠色部分, 是小行星撞擊地球的消息。 (笑) 這是今年夏天的殺人峰事件。
(Laughter)
(笑)
So these are what our fears look like over time in our media. But what I love -- and I'm a journalist -- and what I love is finding hidden patterns; I love being a data detective. And there's a very interesting and odd pattern hidden in this data that you can only see when you visualize it. Let me highlight it for you. See this line, this is a landscape for violent video games. As you can see, there's a kind of odd, regular pattern in the data, twin peaks every year. If we look closer, we see those peaks occur at the same month every year. Why? Well, November, Christmas video games come out, and there may well be an upsurge in the concern about their content. But April isn't a particularly massive month for video games. Why April? Well, in April 1999 was the Columbine shooting, and since then, that fear has been remembered by the media and echoes through the group mind gradually through the year. You have retrospectives, anniversaries, court cases, even copy-cat shootings, all pushing that fear into the agenda. And there's another pattern here as well. Can you spot it? See that gap there? There's a gap, and it affects all the other stories. Why is there a gap there? You see where it starts? September 2001, when we had something very real to be scared about.
這些是從媒體開始報導到結束之間 對這些事件報導的程度。 因為我是個記者, 所以我喜歡尋找那隱藏的模式,我喜歡當個資料偵探。 資料中總是隱藏著有趣且古怪的模式, 除了把資料視覺化,不然根本沒辦法發覺。 讓我為各位點出這些地方。 紅色部分,是針對暴力電玩的報導強度。 各位可以看到,有點奇怪,資料出現了一些規律, 每年的報導都出現2次尖峰。 若我們仔細看,我們能發現這2次尖峰, 都是發生在特定的月份。 為什麼? 因為耶誕節前,電玩遊戲會紛紛在11月推出, 所以很多媒體就會針對這些遊戲內容做出評論。 但四月對電玩業者而言, 又不是什麼重要的月份。 為什麼四月也會這樣? 因為1999年4月發生了科倫拜校園槍擊事件, 從那時候開始, 這件事情就被媒體銘記, 並在每年的這個時候重新報導。 像是回顧展、周年紀念日、 法庭案件、甚至有模仿的槍擊事件, 這些助力讓此事件一再的被報導。 這裡面其實還有一個模式,各位注意到了嗎? 看到這個缺口了嗎? 這個大缺口是其他事件所導致的。 是什麼事件? 這缺口從什麼時候開始的? 2001年9月。 因為這個時間點 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, and I keep hearing a phrase all the time, which is this: "Data is the new oil." Data is the kind of ubiquitous resource that we can shape to provide new innovations and new insights, and it's all around us, and it can be mined very easily. It's not a particularly great metaphor in these times, especially if you live around the Gulf of Mexico, but I would, perhaps, adapt this metaphor slightly, and I would say that data is the new soil. Because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments. And, all right, I'm kind of milking the metaphor a little bit. But it's a really fertile medium, and it feels like visualizations, infographics, data visualizations, they feel like flowers blooming from this medium. But if you look at it directly, it's just a lot of numbers and disconnected facts. But if you start working with it and playing with it in a certain way, interesting things can appear and different patterns can be revealed.
我作為資料記者大約已經一年的時間。 這期間我常聽到一句話 這句話就是: "資料是種新石油" 資料就像是某種普遍的資源, 我們可以使之塑形,以提供我們新思想跟新洞察, 這種資源就在我們身邊,非常容易取得。 現在這時間點,是不太適合把資料比喻成石油, 尤其是如果你住在墨西哥灣附近的話, 但其實我只對這種比方贊同一點點, 我認為,"資料是一種新土壤"。 對我來說,資料就像是一種肥沃、有創造力的媒介。 過去幾年, 我們已經在網路上 放置了非常大量的資訊和資料, 我們利用網路和連結灌溉它們, 透過政府和網路志工在這上面不斷耕種。 喔,對啦,我也可以用擠奶作為譬喻。 這是非常豐沃的媒介, 形象、圖表資料、視覺化資料, 都像是從這媒介中,生長出來的茂盛花海。 不過,若直接觀看資料圖表, 看起來就像一堆數字,和一堆不相干的事件。 如果將這些資訊用特別的方式整理一下, 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. Can you guess what this data set is? What rises twice a year, once in Easter and then two weeks before Christmas, has a mini peak every Monday, and then flattens out over the summer? I'll take answers. (Audience: Chocolate.) David McCandless: Chocolate. You might want to get some chocolate in. Any other guesses? (Audience: Shopping.) DM: Shopping. Yeah, retail therapy might help. (Audience: Sick leave.) DM: Sick leave. Yeah, you'll definitely want to take some time off. Shall we see?
讓我示範給各位看。 各位能猜到這些資料在陳述什麼嗎? 1年內會出現2次尖峰, 一次是在復活節(3、4月), 另一次是聖誕節的前2周, 而每星期的星期一都會有一次小高峰, 然後在夏天的時候特別平穩。 有人要猜猜看嗎? 觀眾:巧克力。 這跟巧克力有一點點相關。 有其他答案嗎? 觀眾:購物。 購物也許能紓緩這件事。 觀眾:請病假。 請病假。對,這時候會想要休息一下。 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, we scraped 10,000 status Facebook updates for the phrase "break-up" and "broken-up" and this is the pattern we found -- people clearing out for Spring Break, (Laughter) coming out of very bad weekends on a Monday, being single over the summer, and then the lowest day of the year, of course: Christmas Day. Who would do that? So there's a titanic amount of data out there now, unprecedented. But if you ask the right kind of question, or you work it in the right kind of way, interesting things can emerge.
Lee Byron和我一起做這項統計, 我們抓了1萬筆Facebook上的個人狀態, 關鍵字是"分手", 然後我們發現了這個模式, 春假前先分手(才能玩樂) (笑) 在度過了幾個糟糕週末後的星期一, 然後單身渡過整個夏天。 接下來是一整年分手數的最低點,聖誕節。 誰會在這時候分手阿? 現在我們有許多的數據, 是前所未有的。 不過,若你的質疑正確, 或是你蒐集正確的資料, 有趣的事情就會跑出來。
So information is beautiful. Data is beautiful. I wonder if I could make my life beautiful. And here's my visual C.V. I'm not quite sure I've succeeded. Pretty blocky, the colors aren't that great. But I wanted to convey something to you. I started as a programmer, and then I worked as a writer for many years, about 20 years, in print, online and then in advertising, and only recently have I started designing. And I've never been to design school. I've never studied art or anything. I just kind of learned through doing. And when I started designing, I discovered an odd thing about myself. I already knew how to design, but it wasn't like I was amazingly brilliant at it, but more like I was sensitive to the ideas of grids and space and alignment and typography. It's almost like being exposed to all this media over the years had instilled a kind of dormant design literacy in me. And I don't feel like I'm unique.
資訊是美麗的,資料是美麗的。 我希望將我的人生弄的很美麗。 這是我的"視覺履歷"(visual C.V)。 我不太確定是否成功了。 上色的小方塊。顏色不是這麼好看。 但我想傳達一些訊息給各位。 我第一份工作是程式設計師, 然後我當作家大約20年, 作品出版後,我又進了廣告業, 直到最近我才開始從事設計。 我從未接受設計方面的教育。 也從來沒學過任何美術學科。 我透過實作來學習。 當我開始從事設計的時候, 我就發現自己有些怪怪的。 雖然我已經知道該如何設計, 但是結果並不如我想像中的令人驚奇, 而我對某些元素相當敏感, 像是方格、空間、 直線對齊、排版設計。 可能是因為 我過去這幾年都在媒體界工作 而那類型的設計素養就被深植在腦中。 我不覺得我是獨一無二的。
I feel that everyday, all of us now are being blasted by information design. It's being poured into our eyes through the Web, and we're all visualizers now; we're all demanding a visual aspect to our information. There's something almost quite magical about visual information. It's effortless, it literally pours in. And if you're navigating a dense information jungle, coming across a beautiful graphic or a lovely data visualization, it's a relief, it's like coming across a clearing in the jungle. I was curious about this, so it led me to the work of a Danish physicist called Tor Norretranders, and he converted the bandwidth of the senses into computer terms.
我只是感覺到,人們每天 都被資訊設計(information design)所轟炸。 透過網頁不斷注入到我們的眼睛裡, 我們都善於在腦海中想像, 因此我們需要將資訊 呈現為視覺化的面貌。 視覺資訊有一些地方是很不可思議的。 它很簡單,確實地融入我們。 若你想引領人們在濃密的資訊叢林中航行, 透過華麗的圖像 或是美麗的視覺化資訊, 那就輕鬆多了,這就變成像是通過叢林中的空地。 我對這方面的知識相當好奇, 因此我與一位丹麥物理學家合作 他叫Tor Norretranders, 他將人的感官寬帶轉換成電腦用語。
So here we go. This is your senses, pouring into your senses every second. Your sense of sight is the fastest. It has the same bandwidth as a computer network. Then you have touch, which is about the speed of a USB key. And then you have hearing and smell, which has the throughput of a hard disk. And then you have poor old taste, which is like barely the throughput of a pocket calculator. And that little square in the corner, a naught .7 percent, that's the amount we're actually aware of. So a lot of your vision -- the bulk of it is visual, and it's pouring in. It's unconscious. The eye is exquisitely sensitive to patterns in variations in color, shape and pattern. It loves them, and it calls them beautiful. It's the language of the eye. If you combine the language of the eye with the language of the mind, which is about words and numbers and concepts, you start speaking two languages simultaneously, each enhancing the other. So, you have the eye, and then you drop in the concepts. And that whole thing -- it's two languages both working at the same time.
開始了,這是你的感官, 你的感官時時刻刻都在接受資訊。 視覺對資訊的反應是最快的。 就像是電腦寬頻網路的速度。 然後是觸覺,大概像USB傳輸的速度。 接下來才是你的聽覺和嗅覺, 這就像硬碟的存取速度。 然後是緩慢的味覺, 它的反應速度大概就像計算機的存取速度。 在角落有個小方塊,大概佔感官的0.7%, 這是我們真正的意識。 你透過眼睛接受的大量資訊, 像圖中的大方塊般龐大,不停的灌入。 這過程是無意識的。 而且眼睛對於圖形的顏色、形狀、組合模式, 是非常敏感的。 眼睛喜愛這些圖形,認為它們很美麗。 這是眼睛的語言。 若你把眼睛和心靈的語言組合起來, 這二者都針對文字、數字、概念的陳述, 你便能同時述說二種語言, 就能增加兩者的感受。 所以,用眼睛看某事物時,心裡就會出現概念。 而這整個過程,是因為 這二種語言同時運作的關係。
So we can use this new kind of language, if you like, to alter our perspective or change our views. Let me ask you a simple question with a really simple answer: Who has the biggest military budget? It's got to be America, right? Massive. 609 billion in 2008 -- 607, rather. So massive, in fact, that it can contain all the other military budgets in the world inside itself. Gobble, gobble, gobble, gobble, gobble. Now, you can see Africa's total debt there and the U.K. budget deficit for reference. So that might well chime with your view that America is a sort of warmongering military machine, out to overpower the world with its huge industrial-military complex. But is it true that America has the biggest military budget? Because America is an incredibly rich country. In fact, it's so massively rich that it can contain the four other top industrialized nations' economies inside itself, it's so vastly rich. So its military budget is bound to be enormous. So, to be fair and to alter our perspective, we have to bring in another data set, and that data set is GDP, or the country's earnings. Who has the biggest budget as a proportion of GDP? Let's have a look. That changes the picture considerably. Other countries pop into view that you, perhaps, weren't considering, and American drops into eighth.
若你願意,我們能用另一種新語言, 這種語言可以改變我們的認知和觀點。 讓我問各位一個簡單的問題, 只需要簡短的答案。 哪個國家的軍事預算最高? 就是美國了,對吧? 非常龐大的數字。2008年的6090億.. 更正,是6070億。 實際上,這麼大的數字, 可以吃下全世界其他國家軍事預算的總和。 幾乎吃個精光。 我們用非洲國家的總負債(中間方塊) 和英國預算赤字(右側方塊)做個比較。 這應該也符合 各位對美國的看法, 像是好戰者、戰爭機器、 企圖征服世界、 大號的軍事工業複合體(industrial-military complex)。 但是美國真的是擁有最高國防預算的國家嗎? 因為美國是個非常富有的國家。 事實上,美國的富有程度, 能包含世界上 前4大工業國家的經濟產值 實在是非常富有。 所以這樣的國家,軍事預算自然就龐大。 要從公平的角度,來調整我們的認知, 我們得要有另一套資料來分析, 這套資料就是GDP,或說是一國的收入。 哪一國的軍事預算佔GDP最重? 讓我們來瞧瞧。 圖形跟剛剛有很大的不同喔。 很多國家都跑出來了,搞不好這些國家你想都沒想過, 美國的名次掉到第8了。
Now you can also do this with soldiers. Who has the most soldiers? It's got to be China. Of course, 2.1 million. Again, chiming with your view that China has a militarized regime ready to, you know, mobilize its enormous forces. But of course, China has an enormous population. So if we do the same, we see a radically different picture. China drops to 124th. It actually has a tiny army when you take other data into consideration. So, absolute figures, like the military budget, in a connected world, don't give you the whole picture. They're not as true as they could be.
現在我們來看看有關軍人的部份。 誰擁有的軍人最多?應該是中國。 沒錯,210萬人。 又來了,再度符合各位的印象, 因為中國是個軍事主義政權, 像是隨時要展現他們強大的武力。 但事實上,中國擁有龐大的人口。 若我們做跟剛剛一樣的事, 我們就會看到非常不一樣的圖形。 中國掉到了第124名。 從另一種資料面來看, 中國的軍隊規模實在有夠小。 像軍事預算這種絕對數字, 在這互相連結的世界裡, 反而沒辦法讓你看到完整的事實。 事物的真相不如它表面所示。
We need relative figures that are connected to other data so that we can see a fuller picture, and then that can lead to us changing our perspective. As Hans Rosling, the master, my master, said, "Let the dataset change your mindset." And if it can do that, maybe it can also change your behavior.
我們需要用其他資料的相關數字作比較, 這樣才能了解最完整的事實, 進一步改變我們的認知。 Hans Rosling教授, 同時也是我的老師,他說: "用數據改變思維" 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. I'm a bit of a health nut. I love taking supplements and being fit, but I can never understand what's going on in terms of evidence. There's always conflicting evidence. Should I take vitamin C? Should I be taking wheatgrass? This is a visualization of all the evidence for nutritional supplements. This kind of diagram is called a balloon race. So the higher up the image, the more evidence there is for each supplement. And the bubbles correspond to popularity as regards to Google hits. So you can immediately apprehend the relationship between efficacy and popularity, but you can also, if you grade the evidence, do a "worth it" line. So supplements above this line are worth investigating, but only for the conditions listed below, and then the supplements below the line are perhaps not worth investigating.
各位看這裡。 我是個注重健康的人。 雖然我喜歡攝取一些營養品、健身, 但是我永遠搞不清楚這些東西會帶來的好處。 有很多牴觸的說法。 我應該攝取維他命C嗎?還是應該吃小麥草? 畫面上所呈現的圖像就是 營養品所提供好處的圖像化。 這種圖形稱為熱汽球(balloon race)。 較高的圓圈, 是有強烈證據證明其功效的營養品。 而圓圈大小是對應在Google上查詢的次數。 這樣你就能馬上看出營養品之間, 效果和受歡迎程度的比較。 若再根據這些證據做排序, 可以畫上一條"值得攝取(worth it)"線。 在這條線上的營養素是最值得探討的, 它們適用於圓圈內下方小字的情況。 而在這條線之下的營養素, 其實,並不這麼值得探討。
Now this image constitutes a huge amount of work. We scraped like 1,000 studies from PubMed, the biomedical database, and we compiled them and graded them all. And it was incredibly frustrating for me because I had a book of 250 visualizations to do for my book, and I spent a month doing this, and I only filled two pages. But what it points to is that visualizing information like this is a form of knowledge compression. It's a way of squeezing an enormous amount of information and understanding into a small space. And once you've curated that data, and once you've cleaned that data, and once it's there, you can do cool stuff like this.
要弄出這張圖片可是件大工程。 我們從PubMed搜尋引擎中抓出一千多份的研究報告, PubMed會連到生物醫學資料庫, 然後我們將這些報告做匯整排序。 這讓我感到非常沮喪的是, 我的書需要有250張的視覺化圖像, 然後我花了一個月整理出這堆圈圈, 卻只能塞滿2頁。 不過,這張圖點出了 視覺化的資訊 就是一種知識濃縮的型態。 這種方式能夠壓縮非常大量的 資訊和知識 濃縮在一起。 透過資料的搜集整頓, 一但完成, 你也能做出這麼酷炫的東西。
So I converted this into an interactive app, so I can now generate this application online -- this is the visualization online -- and I can say, "Yeah, brilliant." So it spawns itself. And then I can say, "Well, just show me the stuff that affects heart health." So let's filter that out. So heart is filtered out, so I can see if I'm curious about that. I think, "No, no. I don't want to take any synthetics, I just want to see plants and -- just show me herbs and plants. I've got all the natural ingredients." Now this app is spawning itself from the data. The data is all stored in a Google Doc, and it's literally generating itself from that data. So the data is now alive; this is a living image, and I can update it in a second. New evidence comes out. I just change a row on a spreadsheet. Doosh! Again, the image recreates itself. So it's cool. It's kind of living.
我將這張圖轉換成一個互動的應用程式, 便產生了這個線上應用程式, 這種線上的視覺化程式, 我想說:"哇嗚,超棒的"。 這張圖能自己更新資料。 只要我說:"我只想看 會影響心臟健康的東西就好"。 點選項,程式會開始過濾。 有關心臟保養的營養品就出現了。 如果我想說:"喔不,我是不吃人工合成物的。 只要告訴我 藥草類和植物類食品就行了,我只要天然的成分"。 然後這程式又會開始從資料中 過濾出想要的資訊。 這些資料會被儲存成Google文件, 嚴格來說,資料會自動轉成文件檔案。 因此,這些資料是活的,是個活生生的圖像, 我只需要幾秒鐘就能更新資料。 我只需要改變選單裡的選項,新的資料就跑出來了。 再一次,夭壽!這些圖像能自我創造。 它非常棒。 它是活生生的。
But it can go beyond data, and it can go beyond numbers. I like to apply information visualization to ideas and concepts. This is a visualization of the political spectrum, an attempt for me to try and understand how it works and how the ideas percolate down from government into society and culture, into families, into individuals, into their beliefs and back around again in a cycle. What I love about this image is it's made up of concepts, it explores our worldviews and it helps us -- it helps me anyway -- to see what others think, to see where they're coming from. And it feels just incredibly cool to do that.
它超越了資料本身, 它能突顯數字的涵意。 我想要應用資料視覺化的技術 在各種不同領域上。 畫面上的是 政治光譜(度量政治傾向的工具)的視覺化。 我試圖了解 這張圖該怎麼運作, 還有政府的立場 該如何滲透到社會、文化、 家庭、個人、甚至到個人信念, 然後這個影響關係會形成一個迴圈。 我喜歡這張圖的地方是 它是由許多概念所構成, 它探討了我們當今的世界觀, 它能幫助我們 觀察到他人心裡所想, 並觀察到這些想法從何而來。 這張圖實在是太棒了。
What was most exciting for me designing this was that, when I was designing this image, I desperately wanted this side, the left side, to be better than the right side -- being a journalist, a Left-leaning person -- but I couldn't, because I would have created a lopsided, biased diagram. So, in order to really create a full image, I had to honor the perspectives on the right-hand side and at the same time, uncomfortably recognize how many of those qualities were actually in me, which was very, very annoying and uncomfortable. (Laughter) But not too uncomfortable, because there's something unthreatening about seeing a political perspective, versus being told or forced to listen to one. You're capable of holding conflicting viewpoints joyously when you can see them. It's even fun to engage with them because it's visual. So that's what's exciting to me, seeing how data can change my perspective and change my mind midstream -- beautiful, lovely data.
在設計這張圖時, 最令我感到興奮的是, 當我正在進行設計的時候, 我拼老命想把左派陣營 弄得比右派陣營好(註:左派提倡自由,右派提倡集權) 因為我是一位記者、一位左派人士。 但我不能這樣做,否則會出現 一個傾斜、具有偏見的圖像。 所以,為了忠實呈現完整的圖像, 我必須要有身為右派人士的榮耀感, 然而,這過程中,我發現到自己身上 也有許多對立者的特質 這真的非常討厭和不舒服。 (笑) 其實也沒這麼誇張啦, 因為這張圖,對於觀察他人政治觀感 並不會構成太大的威脅, 相對的,還能促使人去聆聽另一方的聲音。 這是真的,當你能清楚看見對方的立場, 就會愉悅地看待衝突的觀念。 甚至樂於與對方接觸, 因為一切視覺化了。 這就是讓我感到興奮的地方, 看到這些美麗、迷人的資料 是如何改變我們的認知, 改變我們根深蒂固的觀念。
So, just to wrap up, I wanted to say that it feels to me that design is about solving problems and providing elegant solutions, and information design is about solving information problems. It feels like we have a lot of information problems in our society at the moment, from the overload and the saturation to the breakdown of trust and reliability and runaway skepticism and lack of transparency, or even just interestingness. I mean, I find information just too interesting. It has a magnetic quality that draws me in.
來做個總結, 我想說的是 我的感覺是,設計能解決問題 同時也能提供優雅的解決方案。 資訊設計 能解決資訊的問題。 此時此刻, 我們的社會上擁有許多資訊問題, 資訊的過載與飽和, 使資料的信任度和可靠性受到打擊, 引發排山倒海的質疑,透明度也大大降低, 或說失去資料的趣味性。 其實資訊是非常有趣的。 它就像具有磁性般的吸引了我。
So, visualizing information can give us a very quick solution to those kinds of problems. Even when the information is terrible, the visual can be quite beautiful. Often we can get clarity or the answer to a simple question very quickly, like this one, the recent Icelandic volcano. Which was emitting the most CO2? Was it the planes or the volcano, the grounded planes or the volcano? So we can have a look. We look at the data and we see: Yep, the volcano emitted 150,000 tons; the grounded planes would have emitted 345,000 if they were in the sky. So essentially, we had our first carbon-neutral volcano.
視覺化的資訊 能快速的針對各種問題提供解答。 即使資訊夾帶的是負面、糟糕的消息, 視覺化能讓它變的非常美麗。 同時能得到清晰的思維 同時快速的回答簡單的問題, 就像這個, 最近的冰島火山。 請問是何者排放了最多的二氧化碳? 是飛機,還是火山, 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) 我們能看見真相為何。 各位看看這資料顯示的情形, 沒錯,火山釋放了15萬噸的二氧化碳; 而這些飛機如果沒有停飛的話, 會釋放34萬5千噸的二氧化碳。 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)