Gary Flake: is Pivot a turning point for web exploration?

譯者: Jenny Yang 審譯者: Bill Hsiung

If I can leave you with one big idea today,

如果我今天的演講可以留給你們一個新概念，

it's that the whole of the data

那就是我們所消費的

in which we consume

資料整體是

is greater that the sum of the parts,

大於其各個部分相加的總和的。

and instead of thinking about information overload,

然而，與其擔心資訊爆炸，

what I'd like you to think about is how

不如思考一下怎樣使用

we can use information so that patterns pop

這些資訊， 使其中的規律顯現，

and we can see trends that would otherwise be invisible.

幫助我們看見原本不可見的趨勢。

So what we're looking at right here is a typical mortality chart

在這裡，我們看到的是一個典型的死亡率表，

organized by age.

根據年齡排列。

This tool that I'm using here is a little experiment.

我現在用的這個工具是一個小小的實驗，

It's called Pivot, and with Pivot what I can do

這個工具叫「樞紐」 (Pivot)， 使用「樞紐」，

is I can choose to filter in one particular cause of deaths -- say, accidents.

我可以選擇過濾出某個特殊的死因， 例如說：事故身亡。

And, right away, I see there's a different pattern that emerges.

然後，馬上我就看見一組不同的模式顯現。

This is because, in the mid-area here,

這是因爲， 中間這裡

people are at their most active,

人們處於他們最活躍的年齡，

and over here they're at their most frail.

而在這裡， 人們是最體弱多病的時候。

We can step back out again

我們可以退回來，

and then reorganize the data by cause of death,

重新根據死因來排列資料，

seeing that circulatory diseases and cancer

我們可以看到循環系統疾病和癌症

are the usual suspects, but not for everyone.

是常見的致死因素，但並不適用於每一個人。

If we go ahead and we filter by age --

如果我們繼續過濾年齡，

say 40 years or less --

比如說 40 歲以下的人群，

we see that accidents are actually

我們會發現意外事故是

the greatest cause that people have to be worried about.

人們最需要小心的殺手

And if you drill into that, it's especially the case for men.

如果你進一步挖掘， 這個準則對男人尤其適用。

So you get the idea

所以，你對這個東西有點概念了，

that viewing information, viewing data in this way,

用這種方法來瀏覽資訊、數據

is a lot like swimming

很像是在一個

in a living information info-graphic.

鮮活的資訊圖片裡游泳。

And if we can do this for raw data,

如果我們可以對原始資料這麼做，

why not do it for content as well?

爲什麼不將內容也比照辦理呢？

So what we have right here

所以，我們在這裡顯示的

is the cover of every single Sports Illustrated

是過去發表過的每一期

ever produced.

運動畫刊的封面。

It's all here; it's all on the web.

都在這裡了， 都在網路上

You can go back to your rooms and try this after my talk.

演講完，你回到飯店房間後，可以試試這個工具。

With Pivot, you can drill into a decade.

用「樞紐」, 你可以深入某一個世代，

You can drill into a particular year.

深入到具體的某一年，

You can jump right into a specific issue.

你也可以直接進入某一期。

So I'm looking at this; I see the athletes

所以當我看著這個的時候，

that have appeared in this issue, the sports.

我看到出現在該期雜誌中的各種運動以及運動員們。

I'm a Lance Armstrong fan, so I'll go ahead and I'll click on that,

我是蘭斯•阿姆斯壯迷， 所以我就點擊選取這一期，

which reveals, for me, all the issues

然後它為我展示了所有刊登過有關蘭斯•阿姆斯壯

in which Lance Armstrong's been a part of.

內容的所有期數。

(Applause)

（掌聲）

Now, if I want to just kind of take a peek at these,

現在， 如果我只是簡單的瀏覽一眼這些內容

I might think,

我可能會想

"Well, what about taking a look at all of cycling?"

「好， 那把所有有關自行車運動的期刊都找出來如何？」

So I can step back, and expand on that.

所以我可以退回去， 然後在著重在那些內容。

And I see Greg LeMond now.

現在我看到 Greg Lemond 了。

And so you get the idea that when you

你現在應該已經知道， 當你

navigate over information this way --

用這種方法在大量資訊中領航，

going narrower, broader,

你可以縮小、擴大、

backing in, backing out --

深入、淺出，

you're not searching, you're not browsing.

你不是在搜索，你也不是在瀏覽

You're doing something that's actually a little bit different.

你所做的事情跟這兩者都有些不同。

It's in between, and we think it changes

界於兩者之間， 我們認爲這改變了

the way information can be used.

資訊可以被使用的方法。

So I want to extrapolate on this idea a bit

所以我想對這個觀點做進一步的闡釋，

with something that's a little bit crazy.

是一些稍微有點瘋狂的想法。

What we're done here is we've taken every single Wikipedia page

我們在這裡所做的是，我們將每一頁維基百科，

and we reduced it down to a little summary.

縮簡成一小段摘要。

So the summary consists of just a little synopsis

這摘要只包括了一些簡介

and an icon to indicate the topical area that it comes from.

和一個顯示標題範圍來源的圖示。

I'm only showing the top 500

我這裡只顯示維基百科中

most popular Wikipedia pages right here.

最熱門的 500 頁。

But even in this limited view,

但即使在這有限的展示中，

we can do a lot of things.

我們也可以做很多事情。

Right away, we get a sense of what are the topical domains

我們馬上可以知道，哪些主題

that are most popular on Wikipedia.

在維基百科中最熱門。

I'm going to go ahead and select government.

我這裡選擇「政府」，

Now, having selected government,

選了「政府」以後，

I can now see that the Wikipedia categories

我可以看到維基百科中

that most frequently correspond to that

與之對應最頻繁的類別是，

are Time magazine People of the Year.

時代雜誌的年度風雲人物。

So this is really important because this is an insight

這真的很重要，因爲這種洞見，

that was not contained within any one Wikipedia page.

並不包含在任何維基百科的網頁中。

It's only possible to see that insight

唯一可以看出這個關係的方法是，

when you step back and look at all of them.

退後一步，縱觀全局。

Looking at one of these particular summaries,

看著這些不同摘要的其中一個，

I can then drill into the concept of

我可以接著深入探索

Time magazine Person of the Year,

時代雜誌年度風雲人物這個概念，

bringing up all of them.

把他們都帶出來。

So looking at these people,

看著這些人，

I can see that the majority come from government;

我發現他們中的多數來自政府，

some have come from natural sciences;

有些來自自然科學，

some, fewer still, have come from business --

有些，很少數，是商業人士。

there's my boss --

這是我老闆。

and one has come from music.

其中一個是音樂界人士，

And interestingly enough,

而有趣的是，

Bono is also a TED Prize winner.

Bono 也是 TED 大獎得主。

So we can go, jump, and take a look at all the TED Prize winners.

所以我們可以直接跳進去，看看所有的 TED 大獎得主。

So you see, we're navigating the web for the first time

所以你看， 我們第一次在網路上航行了，

as if it's actually a web, not from page-to-page,

好像它真的是一大張網，不是一張張的頁面，

but at a higher level of abstraction.

而是一種更高層次抽象的概念。

And so I want to show you one other thing

我還想給你們看另一樣東西，

that may catch you a little bit by surprise.

那可能會讓你覺得有點驚訝。

I'm just showing the New York Times website here.

我現在顯示的是紐約時報的網頁，

So Pivot, this application --

所以「樞紐」，這個應用程式，

I don't want to call it a browser; it's really not a browser,

我不想稱它為瀏覽器，因爲它並不是一個瀏覽器，

but you can view web pages with it --

但是你可以用它來看網頁。

and we bring that zoomable technology

我們引進了可縮放技術，

to every single web page like this.

運用到每一個網頁。

So I can step back,

所以我可以退出，

pop right back into a specific section.

快速回到一個特定的部分。

Now the reason why this is important is because,

為什麼這很重要？因為，

by virtue of just viewing web pages in this way,

這樣看網頁的好處是，

I can look at my entire browsing history

我可以將我的整個瀏覽歷史，

in the exact same way.

完整重現。

So I can drill into what I've done

所以我可以深入探索，

over specific time frames.

在過去某段時間內，我曾經做過的事。

Here, in fact, is the state

這邊所顯示的，事實上， 就在剛剛

of all the demo that I just gave.

我做過的所有的示範。

And I can sort of replay some stuff that I was looking at earlier today.

我可以重播一些今天前些時間我在搜尋的東西。

And, if I want to step back and look at everything,

而如果我想退後一步，縱觀所局，

I can slice and dice my history,

我可以層層切割我的歷史紀錄，

perhaps by my search history --

例如我的搜尋紀錄。

here, I was doing some nepotistic searching,

我在這裡做一些相關的搜尋，

looking for Bing, over here for Live Labs Pivot.

搜尋 Bing，這裡是 Live 實驗室的 Pivot。

And from these, I can drill into the web page

從那裡，我可以進入網頁，

and just launch them again.

只要再打開就可以了。

It's one metaphor repurposed multiple times,

這是同樣的原始資料，因不同目的被多次組合使用，

and in each case it makes the whole greater

而每一次的重新組合使得它

than the sum of the parts with the data.

比各個部分的總和更爲強大。

So right now, in this world,

所以， 現在， 在這個世界上

we think about data as being this curse.

我們說到數據的時候常常提到這個詛咒，

We talk about the curse of information overload.

我們會提到資訊爆炸，

We talk about drowning in data.

我們會提到淹沒在資料中。

What if we can actually turn that upside down

如果我們能夠顛覆這些想法，

and turn the web upside down,

顛覆網路世界，

so that instead of navigating from one thing to the next,

相對於一個東西連接到另一個東西，

we get used to the habit of being able to go from many things to many things,

讓我們開始來習慣從多樣向多樣的轉換，

and then being able to see the patterns

然後能夠看到

that were otherwise hidden?

隱藏其中的規律。

If we can do that, then instead of being trapped in data,

如果我們能做到，那麼，我們將不再被困於大量的資料，

we might actually extract information.

我們或許可以真的從中萃取出有用的資訊。

And, instead of dealing just with information,

而，除了單純地處理資訊，

we can tease out knowledge.

我們可以獲取知識。

And if we get the knowledge, then maybe even there's wisdom to be found.

而如果我們得到了知識， 也許我們就會找到智慧。

So with that, I thank you.

這就是我的總結， 謝謝大家。

(Applause)

（掌聲）