TED2009
Tim Berners-Lee: The next web
Tim Berners-Lee 談網絡的未來
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二十年前，Tim Berners-Lee 發明了網際網路，而他接下來的計劃是，建立一個開放的連結數據庫，使它得以處理數據，如同網絡處理文字、圖像、影片一般： 解開數據，並且重新塑造我們對它的共同使用模式。
Tim Berners-Lee - Inventor
Tim Berners-Lee invented the World Wide Web. He leads the World Wide Web Consortium (W3C), overseeing the Web's standards and development. Full bio
Tim Berners-Lee invented the World Wide Web. He leads the World Wide Web Consortium (W3C), overseeing the Web's standards and development. Full bio
Double-click the English transcript below to play the video.
00:18
Time flies.
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光陰似箭
00:20
It's actually almost 20 years ago
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差不多是20年前
00:22
when I wanted to reframe the way we use information,
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當我想重新構造我們使用資訊
00:26
the way we work together: I invented the World Wide Web.
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共同工作方式的時候 - 我發明了網際網路
00:29
Now, 20 years on, at TED,
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20年過去了，現在，在TED
00:32
I want to ask your help in a new reframing.
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我請求你們幫助建立一個新的架構
00:37
So going back to 1989,
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回到1989年
00:41
I wrote a memo suggesting the global hypertext system.
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我在備忘錄中建議，使用一種全球的超連結系統
00:44
Nobody really did anything with it, pretty much.
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幾乎沒有什麼人在真正用它
00:47
But 18 months later -- this is how innovation happens --
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但是，18個月後 - 革新就是這麼開始的
00:51
18 months later, my boss said I could do it on the side,
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18個月後，老闆說，我可以兼職做這件事
00:55
as a sort of a play project,
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做一種遊戲性的計劃
00:57
kick the tires of a new computer we'd got.
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就當試用我們新買來的電腦
00:59
And so he gave me the time to code it up.
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他給了我些時間寫代碼
01:02
So I basically roughed out what HTML should look like:
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我草擬了下HTML應該是什麼樣子
01:07
hypertext protocol, HTTP;
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超文件傳輸協定 - HTTP -
01:10
the idea of URLs, these names for things
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關於URLs 的想法 - 這些事物的名稱
01:13
which started with HTTP.
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都是以HTTP開頭命名的
01:15
I wrote the code and put it out there.
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我完成了代碼並發佈出來。
01:17
Why did I do it?
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我為什麼要這麼做?
01:19
Well, it was basically frustration.
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這是一個充滿挫敗感的過程
01:21
I was frustrated -- I was working as a software engineer
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我感到很挫敗 - 因為我作為一個軟體工程師
01:25
in this huge, very exciting lab,
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在這個令人興奮的超大實驗室中工作
01:27
lots of people coming from all over the world.
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很多人從世界各地來到這裡
01:29
They brought all sorts of different computers with them.
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他們的電腦各不相同
01:32
They had all sorts of different data formats,
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資料格式各不相同
01:35
all sorts, all kinds of documentation systems.
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檔案系統各不相同
01:37
So that, in all that diversity,
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所以，這其中有很大的差異性
01:40
if I wanted to figure out how to build something
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如果我想建立一點點東西
01:42
out of a bit of this and a bit of this,
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在這些差異性很大的電腦上
01:44
everything I looked into, I had to connect to some new machine,
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每一項我找到的資料，我不得不連接到一些新的機器
01:48
I had to learn to run some new program,
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運行一些新的程式
01:50
I would find the information I wanted in some new data format.
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以便我能在新的資料格式中找到我需要的資訊
01:55
And these were all incompatible.
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而這些都是不相容的
01:57
It was just very frustrating.
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這非常令人沮喪
01:59
The frustration was all this unlocked potential.
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這種挫敗感卻正顯示出這個專案的潛力所在
02:01
In fact, on all these discs there were documents.
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事實上，過去這些磁片裡全都是檔案
02:04
So if you just imagined them all
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所以如果你僅僅把他們
02:07
being part of some big, virtual documentation system in the sky,
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想像成天空中某些大型虛擬檔案系統的一部分
02:12
say on the Internet,
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比如在網際網路上
02:14
then life would be so much easier.
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生活就會簡單得多
02:16
Well, once you've had an idea like that it kind of gets under your skin
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這樣，一旦你有了這樣的想法
02:20
and even if people don't read your memo --
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即使人們並沒有讀到你的備忘錄
02:22
actually he did, it was found after he died, his copy.
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事實上他讀到了，因為在他死後，在他的備份草稿中
02:25
He had written, "Vague, but exciting," in pencil, in the corner.
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他用鉛筆在角落寫到“模糊，但是令人興奮”。
02:28
(Laughter)
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（笑聲）
02:30
But in general it was difficult -- it was really difficult to explain
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但一般情況下，很難有這樣的想法 – 的確很難解釋
02:34
what the web was like.
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網路是什麼樣的
02:36
It's difficult to explain to people now that it was difficult then.
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現在都很難向人們解釋，更別提當初了
02:38
But then -- OK, when TED started, there was no web
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但是，當 TED 開始時，那時沒有網路
02:41
so things like "click" didn't have the same meaning.
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所以像“點選”這樣的事情含義是不同的
02:44
I can show somebody a piece of hypertext,
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我現在可以向某人展示一大堆超連結
02:46
a page which has got links,
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某個包含連結的網頁
02:48
and we click on the link and bing -- there'll be another hypertext page.
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我們點選一個連結，然後叮 -- 就會轉到另一個超連結的頁面
02:52
Not impressive.
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沒什麼令人印象深刻的
02:54
You know, we've seen that -- we've got things on hypertext on CD-ROMs.
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我們已經見到，通過超連結找到CD-ROMs中的內容
02:57
What was difficult was to get them to imagine:
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困難的是把它們想像出來
03:00
so, imagine that that link could have gone
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所以，想像那個連結可以到
03:04
to virtually any document you could imagine.
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任何實際的你能想像得到的文件
03:07
Alright, that is the leap that was very difficult for people to make.
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好的，這個跳躍對於人們是很難做到的
03:11
Well, some people did.
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然而，一些人做到了
03:13
So yeah, it was difficult to explain, but there was a grassroots movement.
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儘管很難解釋，但是這是一場草根運動
03:17
And that is what has made it most fun.
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這正是使它好玩的地方
03:21
That has been the most exciting thing,
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也是最令人激動人心的事情
03:23
not the technology, not the things people have done with it,
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不是技術，不是人們用它所做的東西
03:25
but actually the community, the spirit of all these people
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而是實際的交流，所有這些人的思想彙聚
03:27
getting together, sending the emails.
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在一起，發送電子郵件
03:29
That's what it was like then.
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這是那時的情況
03:31
Do you know what? It's funny, but right now it's kind of like that again.
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你知道嗎?有趣的是，現在跟那時候又有點像了
03:34
I asked everybody, more or less, to put their documents --
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我問每一個人，他們或多或少都發佈過文檔
03:36
I said, "Could you put your documents on this web thing?"
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我說“你能把你的文檔放到網路上嗎？”
03:39
And you did.
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然後，你做了
03:42
Thanks.
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謝謝
03:43
It's been a blast, hasn't it?
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這已經是一種風潮，不是嗎?
03:45
I mean, it has been quite interesting
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我的意思是，它已經非常有趣
03:47
because we've found out that the things that happen with the web
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因為我們發現，網路上發生的事情似乎
03:49
really sort of blow us away.
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已經把我們吹到了一邊
03:51
They're much more than we'd originally imagined
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現在它的功能得比我們想像的還多
03:53
when we put together the little, initial website
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最初的設計只是想把檔案湊在一起
03:55
that we started off with.
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在我們最初開始使用網路時
03:57
Now, I want you to put your data on the web.
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現在我想讓你把你的資料放在網上
04:00
Turns out that there is still huge unlocked potential.
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原來這還是有許多未釋放的潛力
04:04
There is still a huge frustration
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也有很大的挫敗感
04:06
that people have because we haven't got data on the web as data.
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因為我們從網上得到的資料不是我們想要的資料
04:10
What do you mean, "data"? What's the difference -- documents, data?
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你說的數據是什麼？數據和文件之間有什麼區別？
04:12
Well, documents you read, OK?
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文件檔是你閱讀的東西
04:15
More or less, you read them, you can follow links from them, and that's it.
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或多或少，你都讀過，你可以追蹤他們的連結，就是這樣
04:18
Data -- you can do all kinds of stuff with a computer.
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數據—你可以通過一台電腦使用各種資料
04:20
Who was here or has otherwise seen Hans Rosling's talk?
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誰在這裡或者其他地方聽過漢斯羅素令的演講?
04:26
One of the great -- yes a lot of people have seen it --
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一個偉大的 – 很多人已經看過了 –
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one of the great TED Talks.
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一個偉大的TED演講
04:32
Hans put up this presentation
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漢斯在他的演說中
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in which he showed, for various different countries, in various different colors --
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使用不同的顏色表示不同的國家
04:39
he showed income levels on one axis
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他在一個軸上顯示收入水準
04:42
and he showed infant mortality, and he shot this thing animated through time.
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同時他用動畫按年份顯示嬰兒死亡率
04:45
So, he'd taken this data and made a presentation
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他使用這些資料完成了一場演講，
04:49
which just shattered a lot of myths that people had
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這個演講打破了很多人
04:52
about the economics in the developing world.
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對發展中國家經濟的神話
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He put up a slide a little bit like this.
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他展示了一個類似的幻燈片
04:58
It had underground all the data
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數據都被埋在地下
05:00
OK, data is brown and boxy and boring,
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對，資料是這些棕色的、無趣的四方盒子
05:03
and that's how we think of it, isn't it?
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我們就是這樣看待資料的，不是嗎？
05:05
Because data you can't naturally use by itself
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因為，你不能漫無目的地使用資料
05:08
But in fact, data drives a huge amount of what happens in our lives
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但事實上，資料驅動了我們的生活
05:12
and it happens because somebody takes that data and does something with it.
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因為某些人使用了資料並且做了些事情
05:15
In this case, Hans had put the data together
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在這個例子中，漢斯將資料放到了一起
05:17
he had found from all kinds of United Nations websites and things.
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漢斯在聯合國網站找到各種資料和事物
05:22
He had put it together,
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他把資料放到了一起
05:24
combined it into something more interesting than the original pieces
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將它們組合起來使之比原始資料有趣得多
05:27
and then he'd put it into this software,
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然後把資料放到這個軟體中
05:32
which I think his son developed, originally,
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這個軟體好像原本是他兒子開發的
05:34
and produces this wonderful presentation.
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最終他做出了這個美妙的簡報
05:37
And Hans made a point
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最後漢斯說道
05:39
of saying, "Look, it's really important to have a lot of data."
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“瞧，有大量的資料是非常重要的”
05:43
And I was happy to see that at the party last night
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我高興地看到在昨天的晚會上
05:46
that he was still saying, very forcibly, "It's really important to have a lot of data."
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他仍然強烈地表示“有大量資料是非常重要的”
05:50
So I want us now to think about
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現在我想讓大家想的是
05:52
not just two pieces of data being connected, or six like he did,
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不僅僅是兩條資料間的連接，或者像他所說的那樣六條資料
05:56
but I want to think about a world where everybody has put data on the web
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而是這個世界上任何人
06:01
and so virtually everything you can imagine is on the web
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都把資料和可以虛擬化的一切內容放到網路上
06:03
and then calling that linked data.
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然後把它們稱為關聯資料
06:05
The technology is linked data, and it's extremely simple.
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這個技術就是關聯資料，它是極其簡單的
06:07
If you want to put something on the web there are three rules:
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如果你想把什麼東西放在網路，有三條規則
06:11
first thing is that those HTTP names --
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第一條規則是，需要有HTTP的名字
06:14
those things that start with "http:" --
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那些東西要以http：開頭
06:16
we're using them not just for documents now,
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我們現在不僅對文件檔這樣用
06:20
we're using them for things that the documents are about.
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對文件檔描述的事物也這樣用
06:22
We're using them for people, we're using them for places,
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我們對人物、地點
06:24
we're using them for your products, we're using them for events.
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產品，事件等都這樣用
06:28
All kinds of conceptual things, they have names now that start with HTTP.
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所有概念化的東西現在都以HTTP開頭命名
06:32
Second rule, if I take one of these HTTP names and I look it up
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第二條規則，如果我有一個HTTP名稱，然後我根據它在網路上進行查找
06:37
and I do the web thing with it and I fetch the data
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我可以從網上獲取資料
06:39
using the HTTP protocol from the web,
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通過HTTP協議
06:41
I will get back some data in a standard format
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我將得到一些標準的格式化資料
06:44
which is kind of useful data that somebody might like to know
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這些有用資料或許是關於人們希望瞭解
06:49
about that thing, about that event.
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某個事物或者事件的
06:51
Who's at the event? Whatever it is about that person,
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事件的主人公是誰？關於這個人的所有資訊
06:53
where they were born, things like that.
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他們什麼時候出生的，等等
06:55
So the second rule is I get important information back.
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所以，第二條規則就是我通過HTTP獲得了重要的資料
06:57
Third rule is that when I get back that information
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第三條規則是，我得到的資訊
07:01
it's not just got somebody's height and weight and when they were born,
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不僅僅是某人的身高、體重和出生日期
07:04
it's got relationships.
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還有資料間的關係
07:06
Data is relationships.
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數據是有關聯的
07:08
Interestingly, data is relationships.
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很有趣，數據是有關聯的
07:10
This person was born in Berlin; Berlin is in Germany.
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這個人出生在柏林，柏林在德國
07:14
And when it has relationships, whenever it expresses a relationship
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當數據是有關聯時，無論何時它表現出這種關聯
07:17
then the other thing that it's related to
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另一件與之有關聯的事物
07:20
is given one of those names that starts HTTP.
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就以HTTP開頭命名
07:24
So, I can go ahead and look that thing up.
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所以，我可以直接去找那件事
07:26
So I look up a person -- I can look up then the city where they were born; then
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比如，我查一個人 -- 我查他出生的城市
07:29
I can look up the region it's in, and the town it's in,
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這個城市的所在區域，城市的城鎮
07:32
and the population of it, and so on.
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人口等等
07:35
So I can browse this stuff.
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這樣我就能流覽這些資訊
07:37
So that's it, really.
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真的，就是這樣
07:39
That is linked data.
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這就是關聯資料
07:41
I wrote an article entitled "Linked Data" a couple of years ago
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我多年前在一篇文章中給它命名為“關聯資料”
07:44
and soon after that, things started to happen.
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之後不久，有些事開始發生了
07:48
The idea of linked data is that we get lots and lots and lots
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關聯資料的想法就像我們得到了很多很多
07:52
of these boxes that Hans had,
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就像漢斯的那些盒子
07:54
and we get lots and lots and lots of things sprouting.
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很多很多的事物開始發芽生長
07:56
It's not just a whole lot of other plants.
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它帶給我們相當多的植物
07:59
It's not just a root supplying a plant,
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不僅僅是一個根供給一個植物
08:01
but for each of those plants, whatever it is --
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對於這的每一個植物，無論它是什麼
08:04
a presentation, an analysis, somebody's looking for patterns in the data --
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一場演說，一個分析，某些人查看數據資料的樣式
08:07
they get to look at all the data
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它們都著眼於所有的數據
08:10
and they get it connected together,
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並且它們把數據聯繫起來
08:12
and the really important thing about data
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關於數據真正重要的是
08:14
is the more things you have to connect together, the more powerful it is.
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你把很多東西聯繫起來，數據就更加有價值
08:16
So, linked data.
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所以，關聯資料
08:18
The meme went out there.
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由此而來
08:20
And, pretty soon Chris Bizer at the Freie Universitat in Berlin
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很快，來自柏林自由大學的克里斯拜澤
08:24
who was one of the first people to put interesting things up,
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做為第一人把有趣的東西放在一起
08:26
he noticed that Wikipedia --
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他注意到維琪百科
08:28
you know Wikipedia, the online encyclopedia
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一部線上百科全書
08:31
with lots and lots of interesting documents in it.
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有很多有趣的文檔
08:33
Well, in those documents, there are little squares, little boxes.
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在這些文檔中，有些小方格子和小盒子
08:37
And in most information boxes, there's data.
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在多數的資訊方格中，就有資料
08:40
So he wrote a program to take the data, extract it from Wikipedia,
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他寫了 一個程式將資料從維琪百科中提取出來
08:44
and put it into a blob of linked data
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然後將它放到關聯資料的組別中
08:46
on the web, which he called dbpedia.
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在網路上，被他稱之為dbpedia（資料庫百科）
08:49
Dbpedia is represented by the blue blob in the middle of this slide
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這張幻燈片中部藍色的blob表示Dbpedia
08:53
and if you actually go and look up Berlin,
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如果你去查詢柏林
08:55
you'll find that there are other blobs of data
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你會發現還有其他的資料
08:57
which also have stuff about Berlin, and they're linked together.
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也有柏林的資訊，它們被聯繫到了一起
09:00
So if you pull the data from dbpedia about Berlin,
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所以，如果你要從dbpedia中摘出關於柏林的資料
09:03
you'll end up pulling up these other things as well.
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你也最終會摘出其他內容
09:05
And the exciting thing is it's starting to grow.
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令人興奮的事情是它正在成長
09:08
This is just the grassroots stuff again, OK?
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這又是一個草根做的事情，對嗎？
09:10
Let's think about data for a bit.
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讓我們多想想資料
09:13
Data comes in fact in lots and lots of different forms.
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資料實際上來源於很多很多不同的形式
09:16
Think of the diversity of the web. It's a really important thing
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想想網路的多樣性，很重要的一點
09:19
that the web allows you to put all kinds of data up there.
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網路允許你將各式各樣的資料放在一起
09:22
So it is with data. I could talk about all kinds of data.
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說到資料，我能說出各種各樣的數據
09:25
We could talk about government data, enterprise data is really important,
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我們可以說政府資料，企業資料真的很重要
09:29
there's scientific data, there's personal data,
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還有科學資料，個人資料
09:32
there's weather data, there's data about events,
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天氣資料，關於事件的資料
09:34
there's data about talks, and there's news and there's all kinds of stuff.
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關於談話的資料，還有新聞和各種類似的東西
09:38
I'm just going to mention a few of them
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我只提到了一小部分資料
09:41
so that you get the idea of the diversity of it,
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你們就可以看出其多樣性
09:43
so that you also see how much unlocked potential.
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所以你可以看到其中的潛力
09:47
Let's start with government data.
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讓我們從政府資料說起
09:49
Barack Obama said in a speech,
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美國總統巴拉克歐巴馬在一場演講上表示
09:51
that he -- American government data would be available on the Internet
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美國政府的資料將在互聯網上被應用
09:56
in accessible formats.
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以一種可訪問的形式
09:58
And I hope that they will put it up as linked data.
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而我希望他們會將這些訊息以關聯資料放上去
10:00
That's important. Why is it important?
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這非常重要，難道不是嗎?
10:02
Not just for transparency, yeah transparency in government is important,
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不僅僅是為了透明性，透明性對政府很重要
10:05
but that data -- this is the data from all the government departments
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尤其是從政府部門出來的資料更重要
10:08
Think about how much of that data is about how life is lived in America.
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想想有多少關係到在美國如何生活的資料
10:13
It's actual useful. It's got value.
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它的確很有用，很有價值
10:15
I can use it in my company.
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我可以把它用在我的公司
10:17
I could use it as a kid to do my homework.
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我可以像個小孩子般把它用在我的家庭作業中
10:19
So we're talking about making the place, making the world run better
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所以，我們談論的是讓世界變得更好
10:22
by making this data available.
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通過將這些資料變得更有用
10:24
In fact if you're responsible -- if you know about some data
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事實上，如果你們在負責 - 如果你知道一些資料
10:28
in a government department, often you find that
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關於政府的， 你經常會發現
10:30
these people, they're very tempted to keep it --
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有些人，他們會被這些資料所吸引
10:33
Hans calls it database hugging.
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漢斯稱之為資料庫擁抱
10:36
You hug your database, you don't want to let it go
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你擁抱你的資料庫，你不會放它走
10:38
until you've made a beautiful website for it.
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直到你為它建立了一個漂亮的網站
10:40
Well, I'd like to suggest that rather --
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嗯，我想建議的是，除了建一個漂亮的網站
10:42
yes, make a beautiful website,
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是的，建一個漂亮的網站
10:44
who am I to say don't make a beautiful website?
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我沒說不要建一個漂亮的網站
10:46
Make a beautiful website, but first
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建一個漂亮的網站，但是首先
10:49
give us the unadulterated data,
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要給我們純粹的數據
10:52
we want the data.
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我們要的是數據
10:54
We want unadulterated data.
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我們要純粹的數據
10:56
OK, we have to ask for raw data now.
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好，現在我們不得不要求原始數據了
10:59
And I'm going to ask you to practice that, OK?
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我要請你們練習一下，好嗎？
11:01
Can you say "raw"?
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請說“原始”
11:02
Audience: Raw.
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原始
11:03
Tim Berners-Lee: Can you say "data"?
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請說“數據”
11:04
Audience: Data.
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數據
11:05
TBL: Can you say "now"?
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請說‘現在“
11:06
Audience: Now!
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現在
11:07
TBL: Alright, "raw data now"!
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好，原始數據現在！
11:09
Audience: Raw data now!
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原始數據現在！
11:11
Practice that. It's important because you have no idea the number of excuses
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這樣練習是非常重要的
11:15
people come up with to hang onto their data
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因為你不知道那些擁有數據的人
11:17
and not give it to you, even though you've paid for it as a taxpayer.
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有多少理由拒絕將數據給你，甚至你作為一個納稅人是為此付了錢的
11:21
And it's not just America. It's all over the world.
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這不僅僅存在於美國，全世界都一樣
11:23
And it's not just governments, of course -- it's enterprises as well.
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也不僅僅在政府，當然也存在於企業。
11:26
So I'm just going to mention a few other thoughts on data.
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我還想再談談關於數據的其他想法
11:29
Here we are at TED, and all the time we are very conscious
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在TED，我們一直關注於
11:34
of the huge challenges that human society has right now --
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人類社會目前所面臨的巨大問題
11:39
curing cancer, understanding the brain for Alzheimer's,
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癌症治療，瞭解阿爾茨海默病
11:42
understanding the economy to make it a little bit more stable,
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瞭解經濟好讓它穩定點
11:45
understanding how the world works.
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瞭解世界是如何運轉的
11:47
The people who are going to solve those -- the scientists --
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那些致力於解決這些問題的科學家
11:49
they have half-formed ideas in their head,
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他們腦海中有些還不成熟的想法
11:51
they try to communicate those over the web.
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他們試圖在網路上與他人交流
11:54
But a lot of the state of knowledge of the human race at the moment
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但是現狀是很多人類的知識
11:57
is on databases, often sitting in their computers,
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現在都在資料庫中，放在他們的電腦裡
12:00
and actually, currently not shared.
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現在實際上也沒被共用
12:03
In fact, I'll just go into one area --
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事實上，我就從一個方面來說明 -
12:06
if you're looking at Alzheimer's, for example,
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如果你在研究阿爾茨海默病，以此為例，
12:08
drug discovery -- there is a whole lot of linked data which is just coming out
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以藥物發現為例 -- 這個領域具有相當多的剛剛出現的關聯資料
12:11
because scientists in that field realize
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因為這個領域的科學家們意識到
12:13
this is a great way of getting out of those silos,
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關聯資料是一種很好的方法，可以説明他們擺脫資料孤島
12:16
because they had their genomics data in one database
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因為他們在一個資料庫中建立了基因圖組
12:20
in one building, and they had their protein data in another.
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他們在另一個資料庫中建立蛋白質數據
12:23
Now, they are sticking it onto -- linked data --
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現在，他們將基因圖組和蛋白質數據形成了關聯資料
12:26
and now they can ask the sort of question, that you probably wouldn't ask,
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然後他們現在可以問一些特定的問題，也許你不會問
12:29
I wouldn't ask -- they would.
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我也不會問，但是他們會
12:31
What proteins are involved in signal transduction
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哪些蛋白質參與信號轉導
12:33
and also related to pyramidal neurons?
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並且也和錐體神經元相關？
12:35
Well, you take that mouthful and you put it into Google.
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當你將這個問題放到Google上搜索
12:38
Of course, there's no page on the web which has answered that question
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自然沒有回答結果的頁面
12:41
because nobody has asked that question before.
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因為之前沒有人問過這樣的問題
12:43
You get 223,000 hits --
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雖然你得到了223,000個結果
12:45
no results you can use.
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但是沒有一個你用得上
12:47
You ask the linked data -- which they've now put together --
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當你查詢關聯資料 -- 現在他們已經被放到了一起
12:50
32 hits, each of which is a protein which has those properties
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命中32個結果，每一個結果都是與特性相關的蛋白質
12:54
and you can look at.
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並且你可以查看
12:56
The power of being able to ask those questions, as a scientist --
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做為一個科學家， 詢問那些問題的能力
12:59
questions which actually bridge across different disciplines --
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那些問題基本上都是跨學科的問題
13:01
is really a complete sea change.
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是非常徹底的重大改變
13:04
It's very very important.
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這是非常非常重要的
13:06
Scientists are totally stymied at the moment --
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科學家們那時完全陷入了困境
13:08
the power of the data that other scientists have collected is locked up
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因為其他科學家搜集的資料，其價值被鎖起來了
13:13
and we need to get it unlocked so we can tackle those huge problems.
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我們需要將之解鎖，以便處理那些重大問題
13:16
Now if I go on like this, you'll think that all the data comes from huge institutions
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現在，如果我繼續像這樣講，你們會覺得這些數據都是從大機構得來的
13:20
and has nothing to do with you.
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和你沒有一點關係
13:23
But, that's not true.
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但是，這種想法並不對
13:25
In fact, data is about our lives.
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事實上，數據關乎我們的生活
13:27
You just -- you log on to your social networking site,
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你剛剛登陸了你的社交網站
13:30
your favorite one, you say, "This is my friend."
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你最喜歡的一個，你說“這是我朋友”
13:32
Bing! Relationship. Data.
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叮！關聯，資料
13:35
You say, "This photograph, it's about -- it depicts this person. "
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你說“這副照片，是這個人的”
13:38
Bing! That's data. Data, data, data.
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叮！那是數據。數據，數據，數據
13:41
Every time you do things on the social networking site,
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每次你在社交網站上做的事
13:43
the social networking site is taking data and using it -- re-purposing it --
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社交網站就獲取資料並利用它
13:47
and using it to make other people's lives more interesting on the site.
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重新設計資料的目的是為了讓這個網站的其他人過得更有趣
13:51
But, when you go to another linked data site --
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但是，當你上另一個關聯資料網站
13:53
and let's say this is one about travel,
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假設是一個旅遊網站
13:56
and you say, "I want to send this photo to all the people in that group,"
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你說“我想把這張照片發給那個組裡的所有人”
13:59
you can't get over the walls.
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但你卻無法翻過這些牆
14:01
The Economist wrote an article about it, and lots of people have blogged about it --
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經濟學家曾經寫了一篇關於這個問題的文章，並且許多人也發了相關部落格表示出
14:03
tremendous frustration.
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巨大的挫敗感
14:04
The way to break down the silos is to get inter-operability
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打破孤島的方式是實現交互操作
14:06
between social networking sites.
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在這些社交網站之間
14:08
We need to do that with linked data.
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我們需要通過關聯資料做這件事
14:10
One last type of data I'll talk about, maybe it's the most exciting.
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最後一種我將要談到的資料，也許是最令人激動的
14:13
Before I came down here, I looked it up on OpenStreetMap
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在我來這之前，我通過OpenStreetMap查找了一下
14:16
The OpenStreetMap's a map, but it's also a Wiki.
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OpenStreetMap是一個地圖，但同樣也是一個維琪
14:18
Zoom in and that square thing is a theater -- which we're in right now --
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放大這個方塊，這是一個劇場 -- 就是我們現在所處的地方 --
14:21
The Terrace Theater. It didn't have a name on it.
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特羅斯劇場（位於加州長灘市）。它現在還沒有被標上名字
14:23
So I could go into edit mode, I could select the theater,
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所以我可以到編輯模式，選擇劇場
14:25
I could add down at the bottom the name, and I could save it back.
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然後在底下填上名字，然後保存它
14:30
And now if you go back to the OpenStreetMap. org,
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現在你再去訪問OpenStreetMap.org
14:33
and you find this place, you will find that The Terrace Theater has got a name.
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你找到這個地方，你會發現它現在有名字了
14:36
I did that. Me!
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是我做的，是我！
14:38
I did that to the map. I just did that!
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我在地圖上標的，剛剛做的
14:40
I put that up on there. Hey, you know what?
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我把它標注在那裡。嗨，你知道嗎
14:42
If I -- that street map is all about everybody doing their bit
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如果除了我，每個人都在這個地圖上標注一點
14:45
and it creates an incredible resource
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將會產生難以置信的資源
14:48
because everybody else does theirs.
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因為其他每個人都做了
14:51
And that is what linked data is all about.
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這就是關聯資料
14:54
It's about people doing their bit
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每個人都做一點
14:57
to produce a little bit, and it all connecting.
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生成一點內容，然後把它們連接起來
15:00
That's how linked data works.
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關聯資料就是這樣工作的
15:03
You do your bit. Everybody else does theirs.
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你做一些，每個人都做一些
15:07
You may not have lots of data which you have yourself to put on there
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也許你的資料在關聯資料中只是很小一部分
15:11
but you know to demand it.
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但你知道你需要它
15:14
And we've practiced that.
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我們已經在實踐了
15:16
So, linked data -- it's huge.
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關聯資料 -- 是非常巨大的
15:20
I've only told you a very small number of things
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我只能告訴你很小一部分
15:23
There are data in every aspect of our lives,
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我們生活的每個方面
15:25
every aspect of work and pleasure,
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工作和快樂的每個方面
15:28
and it's not just about the number of places where data comes,
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不管是資料出處的有多少
15:31
it's about connecting it together.
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關鍵是把它聯繫起來
15:34
And when you connect data together, you get power
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當你把數據聯繫起來
15:37
in a way that doesn't happen just with the web, with documents.
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你能從這樣的方式中獲取在網路或文檔中無法獲取的力量
15:40
You get this really huge power out of it.
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你能從中得到巨大的力量
15:44
So, we're at the stage now
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現在我們處在一個階段
15:47
where we have to do this -- the people who think it's a great idea.
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我們必須要做的階段 -- 那些認為這是個偉大想法的人們
15:51
And all the people -- and I think there's a lot of people at TED who do things because --
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而且所有人 -- 我想在 TED 的大部分人
15:54
even though there's not an immediate return on the investment
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他們做事情並不是為了要使投資得到立即的回報
15:56
because it will only really pay off when everybody else has done it --
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因為只有當每個人都這麼做了才會有所回報
15:59
they'll do it because they're the sort of person who just does things
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他們將會這麼做，因為他們是那類人
16:03
which would be good if everybody else did them.
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那類希望每個人都參與進來而讓事情變好的人
16:06
OK, so it's called linked data.
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OK，這就是關聯資料
16:08
I want you to make it.
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我希望你參與
16:10
I want you to demand it.
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我希望你需要它
16:12
And I think it's an idea worth spreading.
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我也認為這個想法值得宣揚
16:14
Thanks.
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謝謝
16:15
(Applause)
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（掌聲）
ABOUT THE SPEAKER
Tim Berners-Lee - InventorTim Berners-Lee invented the World Wide Web. He leads the World Wide Web Consortium (W3C), overseeing the Web's standards and development.
Why you should listen
In the 1980s, scientists at CERN were asking themselves how massive, complex, collaborative projects -- like the fledgling LHC -- could be orchestrated and tracked. Tim Berners-Lee, then a contractor, answered by inventing the World Wide Web. This global system of hypertext documents, linked through the Internet, brought about a massive cultural shift ushered in by the new tech and content it made possible: AOL, eBay, Wikipedia, TED.com...
Berners-Lee is now director of the World Wide Web Consortium (W3C), which maintains standards for the Web and continues to refine its design. Recently he has envisioned a "Semantic Web" -- an evolved version of the same system that recognizes the meaning of the information it carries. He's the 3Com Founders Professor of Engineering in the School of Engineering with a joint appointment in the Department of Electrical Engineering and Computer Science at the Laboratory for Computer Science and Artificial Intelligence (CSAIL) at the MIT, where he also heads the Decentralized Information Group (DIG). He is also a Professor in the Electronics and Computer Science Department at the University of Southampton, UK.
Tim Berners-Lee | Speaker | TED.com