ABOUT THE SPEAKER
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.

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.

More profile about the speaker
Tim Berners-Lee | Speaker | TED.com
TED2009

Tim Berners-Lee: The next web

蒂牧泊纳思-李 谈下一代网络

Filmed:
1,638,798 views

20年前,蒂牧泊纳思-李 发明了万维网。在他的下一个项目中,他正在建立一个开放的、将大量文档、图片、视频建成关联数据:释放我们的数据,重新构建我们使用数据的方式。
- 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

Double-click the English transcript below to play the video.

00:18
Time flies苍蝇.
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光阴似箭
00:20
It's actually其实 almost几乎 20 years年份 ago
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差不多是20年前
00:22
when I wanted to reframe重构 the way we use information信息,
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当我想重新构造我们使用信息
00:26
the way we work together一起: I invented发明 the World世界 Wide Web卷筒纸.
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协同工作方式的时候 - 我发明了万维网
00:29
Now, 20 years年份 on, at TEDTED,
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20年过去了,现在,在TED
00:32
I want to ask your help in a new reframing重新定义.
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我请求你们帮助创建新的架构
00:37
So going back to 1989,
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回到1989年
00:41
I wrote a memo备忘录 suggesting提示 the global全球 hypertext超文本 system系统.
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我在备忘录中建议使用一种全球的超链接系统
00:44
Nobody没有人 really did anything with it, pretty漂亮 much.
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几乎没有什么人在真正用它
00:47
But 18 months个月 later后来 -- this is how innovation革新 happens发生 --
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但是,18个月后 - 革新就是这么开始的
00:51
18 months个月 later后来, my boss老板 said I could do it on the side,
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18个月后,老板说,我可以兼职做这件事
00:55
as a sort分类 of a play project项目,
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做一种游戏性质的项目
00:57
kick the tires轮胎 of a new computer电脑 we'd星期三 got.
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就拿我们新买来的电脑
00:59
And so he gave me the time to code it up.
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他给了我些时间写代码实现
01:02
So I basically基本上 roughed粗暴对待 out what HTMLHTML should look like:
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我草拟了下HTML应该是什么样子
01:07
hypertext超文本 protocol协议, HTTPHTTP;
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超文本协议 - HTTP -
01:10
the idea理念 of URLs网址, these names for things
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关于URLs 的想法 - 事物的名称
01:13
which哪一个 started开始 with HTTPHTTP.
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这些事物都是以HTTP开头命名的
01:15
I wrote the code and put it out there.
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我完成了代码并发布出来。
01:17
Why did I do it?
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我为什么要这么做?
01:19
Well, it was basically基本上 frustration挫折.
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这是一个充满挫败感的过程
01:21
I was frustrated受挫 -- I was working加工 as a software软件 engineer工程师
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我感到很挫败 - 因为我作为名软件工程师
01:25
in this huge巨大, very exciting扣人心弦 lab实验室,
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工作在这个令人兴奋的超大的实验室中
01:27
lots of people coming未来 from all over the world世界.
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很多人从世界各地来到这里
01:29
They brought all sorts排序 of different不同 computers电脑 with them.
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他们的电脑各不相同
01:32
They had all sorts排序 of different不同 data数据 formats格式,
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数据格式各不相同
01:35
all sorts排序, all kinds of documentation文件 systems系统.
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文件系统各不相同
01:37
So that, in all that diversity多样,
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所以,这其中有很大的差异性
01:40
if I wanted to figure数字 out how to build建立 something
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如果我想建立一点点东西
01:42
out of a bit of this and a bit of this,
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在这些差异性很大的电脑上
01:44
everything I looked看着 into, I had to connect to some new machine,
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我要找一些数据,我不得不连接到一些新的机器
01:48
I had to learn学习 to run some new program程序,
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运行一些新的程序
01:50
I would find the information信息 I wanted in some new data数据 format格式.
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以便我能在新的数据格式中找到一些信息
01:55
And these were all incompatible不相容.
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这些都是不兼容的
01:57
It was just very frustrating泄气.
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这非常令人沮丧
01:59
The frustration挫折 was all this unlocked解锁 potential潜在.
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这种挫败感却正显示出这个项目的潜力所在
02:01
In fact事实, on all these discs光盘 there were documents文件.
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事实上,这些磁盘里全是文件
02:04
So if you just imagined想象 them all
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所以如果你仅仅把他们
02:07
being存在 part部分 of some big, virtual虚拟 documentation文件 system系统 in the sky天空,
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想象成天空中某些大型虚拟文件系统的一部分
02:12
say on the Internet互联网,
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比如Internet
02:14
then life would be so much easier更轻松.
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生活就会简单得多
02:16
Well, once一旦 you've had an idea理念 like that it kind of gets得到 under your skin皮肤
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这样,一旦你有了这样的想法
02:20
and even if people don't read your memo备忘录 --
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即使人们并没有读到你的备忘录
02:22
actually其实 he did, it was found发现 after he died死亡, his copy复制.
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事实上他读到了,因为在他死后,在他的草稿拷贝中
02:25
He had written书面, "Vague模糊, but exciting扣人心弦," in pencil铅笔, in the corner.
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他用铅笔在角落写到“模糊,但是令人兴奋”。
02:28
(Laughter笑声)
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(笑声)
02:30
But in general一般 it was difficult -- it was really difficult to explain说明
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但一般情况下,很难有这样的想法 – 的确很难解释
02:34
what the web卷筒纸 was like.
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网络是什么样的
02:36
It's difficult to explain说明 to people now that it was difficult then.
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现在都很难向人们解释,更别提当初了
02:38
But then -- OK, when TEDTED started开始, there was no web卷筒纸
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但是 - 对,当TED开始时,那时没有网络
02:41
so things like "click点击" didn't have the same相同 meaning含义.
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所以像点击这样的事情含义是不同的
02:44
I can show显示 somebody a piece of hypertext超文本,
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我现在可以向某人展示一大堆超链接
02:46
a page which哪一个 has got links链接,
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某个包含链接的网页
02:48
and we click点击 on the link链接 and bing -- there'll有会 be another另一个 hypertext超文本 page.
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我们点击一个链接,然后bing -- 就会转到另一个超链接的页面
02:52
Not impressive有声有色.
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没什么令人印象深刻的
02:54
You know, we've我们已经 seen看到 that -- we've我们已经 got things on hypertext超文本 on CD-ROMs光盘.
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我们已经见到,通过超链接找到CD-ROMs中的内容
02:57
What was difficult was to get them to imagine想像:
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困难的是把它们想象出来
03:00
so, imagine想像 that that link链接 could have gone走了
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所以,想象那个链接可以到
03:04
to virtually实质上 any document文件 you could imagine想像.
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任何实际的你能想象得到的文件
03:07
Alright好的, that is the leap飞跃 that was very difficult for people to make.
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好的,这个跳跃对于人们是很难做到的
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说明, but there was a grassroots基层 movement运动.
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尽管很难解释,但是这是一场草根运动
03:17
And that is what has made制作 it most fun开玩笑.
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这正是使它好玩的地方
03:21
That has been the most exciting扣人心弦 thing,
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也是最令人激动人心的事情
03:23
not the technology技术, not the things people have doneDONE with it,
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不是技术,不是人们用它所做的东西
03:25
but actually其实 the community社区, the spirit精神 of all these people
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而是实际的交流,所有这些人的思想汇聚
03:27
getting得到 together一起, sending发出 the emails电子邮件.
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在一起,发送电子邮件
03:29
That's what it was like then.
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这是那时的情况
03:31
Do you know what? It's funny滑稽, but right now it's kind of like that again.
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你知道吗?有趣的是,现在跟那时候又有点像了
03:34
I asked everybody每个人, more or less, to put their documents文件 --
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我问每一个人,他们或多或少都发布过文档
03:36
I said, "Could you put your documents文件 on this web卷筒纸 thing?"
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我说“你能把你的文档放到网络上吗?”
03:39
And you did.
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然后,你做了
03:42
Thanks谢谢.
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谢谢
03:43
It's been a blast爆破, hasn't有没有 it?
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这已经是一场疾风,不是吗?
03:45
I mean, it has been quite相当 interesting有趣
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我的意思是,它已经非常有趣
03:47
because we've我们已经 found发现 out that the things that happen发生 with the web卷筒纸
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因为我们发现,网络上发生的事情似乎
03:49
really sort分类 of blow打击 us away.
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已经把我们吹到了一边
03:51
They're much more than we'd星期三 originally本来 imagined想象
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现在它的功能得比我们想象的还多
03:53
when we put together一起 the little, initial初始 website网站
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最初的设计只是想把文档放在一起
03:55
that we started开始 off with.
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在我们最初开始使用网络时
03:57
Now, I want you to put your data数据 on the web卷筒纸.
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现在我想让你把你的数据放在网上
04:00
Turns out that there is still huge巨大 unlocked解锁 potential潜在.
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还是有巨大的可释放潜力
04:04
There is still a huge巨大 frustration挫折
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也有很大的挫败感
04:06
that people have because we haven't没有 got data数据 on the web卷筒纸 as data数据.
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因为我们从网上得到的数据不是我们想要的数据
04:10
What do you mean, "data数据"? What's the difference区别 -- documents文件, data数据?
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你说的数据是什么?文档和数据之间有什么区别?
04:12
Well, documents文件 you read, OK?
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文档是你阅读的东西
04:15
More or less, you read them, you can follow跟随 links链接 from them, and that's it.
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或多或少,你都读过,你可以追踪他们的链接,就是这样
04:18
Data数据 -- you can do all kinds of stuff东东 with a computer电脑.
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数据—你可以通过一台电脑使用各种数据
04:20
Who was here or has otherwise除此以外 seen看到 Hans汉斯 Rosling's罗斯林的 talk?
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谁在这里或者其他地方听过汉斯罗素玲的演讲?
04:26
One of the great -- yes a lot of people have seen看到 it --
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一个伟大的 – 很多人已经看过了 –
04:30
one of the great TEDTED Talks会谈.
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一个伟大的TED演讲
04:32
Hans汉斯 put up this presentation介绍
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汉斯在他的演示文档中
04:34
in which哪一个 he showed显示, for various各个 different不同 countries国家, in various各个 different不同 colors颜色 --
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使用不同的颜色表示不同的国家
04:39
he showed显示 income收入 levels水平 on one axis
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他在一个轴上显示收入水平
04:42
and he showed显示 infant婴儿 mortality死亡, and he shot射击 this thing animated动画 through通过 time.
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同时他用动画按年份显示婴儿死亡率
04:45
So, he'd他会 taken采取 this data数据 and made制作 a presentation介绍
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他使用这些数据完成了一场演讲,
04:49
which哪一个 just shattered破灭 a lot of myths神话 that people had
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这个演讲打破了很多人
04:52
about the economics经济学 in the developing发展 world世界.
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对发展中国家经济的神话
04:56
He put up a slide滑动 a little bit like this.
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他展示了一个类似的幻灯片
04:58
It had underground地下 all the data数据
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数据都被埋在地下
05:00
OK, data数据 is brown棕色 and boxy四四方方 and boring无聊,
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对,数据是这些棕色的、无趣的四方盒子
05:03
and that's how we think of it, isn't it?
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我们就是这样看待数据的,不是吗?
05:05
Because data数据 you can't naturally自然 use by itself本身
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因为,你不能漫无目的地使用数据
05:08
But in fact事实, data数据 drives驱动器 a huge巨大 amount of what happens发生 in our lives生活
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但事实上,数据驱动了我们的生活
05:12
and it happens发生 because somebody takes that data数据 and does something with it.
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因为某些人使用了数据并且做了些事情
05:15
In this case案件, Hans汉斯 had put the data数据 together一起
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在这个例子中,汉斯将数据放到了一起
05:17
he had found发现 from all kinds of United联合的 Nations国家 websites网站 and things.
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汉斯在美国网站找到各种数据和事物
05:22
He had put it together一起,
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他把数据放到了一起
05:24
combined结合 it into something more interesting有趣 than the original原版的 pieces
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将它们组合起来使之比原始数据有趣得多
05:27
and then he'd他会 put it into this software软件,
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然后把数据放到这个软件中
05:32
which哪一个 I think his son儿子 developed发达, originally本来,
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这个软件我觉得是他儿子开发的
05:34
and produces产生 this wonderful精彩 presentation介绍.
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最终他做出了这个美妙的演示
05:37
And Hans汉斯 made制作 a point
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最后汉斯说道
05:39
of saying, "Look, it's really important重要 to have a lot of data数据."
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“瞧,有大量的数据是非常重要的”
05:43
And I was happy快乐 to see that at the party派对 last night
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我高兴地看到在昨天的晚会上
05:46
that he was still saying, very forcibly强制, "It's really important重要 to have a lot of data数据."
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他仍然强烈地表示“有大量数据是非常重要的”
05:50
So I want us now to think about
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现在我想让大家想的是
05:52
not just two pieces of data数据 being存在 connected连接的, or six like he did,
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不仅仅是两条数据间的连接,或者像他所说的那样六条数据
05:56
but I want to think about a world世界 where everybody每个人 has put data数据 on the web卷筒纸
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而是这个世界上任何人
06:01
and so virtually实质上 everything you can imagine想像 is on the web卷筒纸
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都把数据和可以虚拟化的一切内容放到网络上
06:03
and then calling调用 that linked关联 data数据.
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然后把它们称为关联数据
06:05
The technology技术 is linked关联 data数据, and it's extremely非常 simple简单.
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这个技术就是关联数据,它是极其简单的
06:07
If you want to put something on the web卷筒纸 there are three rules规则:
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如果你想把什么东西放在网络,有三条规则
06:11
first thing is that those HTTPHTTP names --
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第一条规则是,需要有HTTP的名字
06:14
those things that start开始 with "httpHTTP:" --
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那些东西要以http:开头
06:16
we're using运用 them not just for documents文件 now,
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我们现在不仅对文档这样用
06:20
we're using运用 them for things that the documents文件 are about.
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对文档描述的事物也这样用
06:22
We're using运用 them for people, we're using运用 them for places地方,
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我们对人物、地点
06:24
we're using运用 them for your products制品, we're using运用 them for events事件.
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产品,事件等都这样用
06:28
All kinds of conceptual概念上的 things, they have names now that start开始 with HTTPHTTP.
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所有概念化的东西现在都以HTTP开头命名
06:32
Second第二 rule规则, if I take one of these HTTPHTTP names and I look it up
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第二条规则,如果我有一个HTTP名称,然后我根据它在网络上进行查找
06:37
and I do the web卷筒纸 thing with it and I fetch the data数据
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我可以从网上获取数据
06:39
using运用 the HTTPHTTP protocol协议 from the web卷筒纸,
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通过HTTP协议
06:41
I will get back some data数据 in a standard标准 format格式
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我将得到一些标准的格式化数据
06:44
which哪一个 is kind of useful有用 data数据 that somebody might威力 like to know
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这些有用数据或许是关于人们希望了解
06:49
about that thing, about that event事件.
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某个事物或者事件的
06:51
Who's谁是 at the event事件? Whatever随你 it is about that person,
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事件的主人公是谁?关于这个人的所有信息
06:53
where they were born天生, things like that.
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他们什么时候生的,等等
06:55
So the second第二 rule规则 is I get important重要 information信息 back.
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所以,第二条规则就是我通过HTTP获得了重要的数据
06:57
Third第三 rule规则 is that when I get back that information信息
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第三条规则是,我得到的信息
07:01
it's not just got somebody's某人的 height高度 and weight重量 and when they were born天生,
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不仅仅是某人的身高、体重和出生日期
07:04
it's got relationships关系.
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还有数据间的关系
07:06
Data数据 is relationships关系.
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数据是有联系的
07:08
Interestingly有趣的是, data数据 is relationships关系.
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很有趣,数据是有联系的
07:10
This person was born天生 in Berlin柏林; Berlin柏林 is in Germany德国.
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这个人出生在柏林,柏林在德国
07:14
And when it has relationships关系, whenever每当 it expresses表达 a relationship关系
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当数据有联系时,无论何时它表现出这种联系
07:17
then the other thing that it's related有关 to
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另一件与之有联系的事物
07:20
is given特定 one of those names that starts启动 HTTPHTTP.
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就以HTTP开头命名
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天生; then
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比如,我查一个人 -- 我查他出生的城市
07:29
I can look up the region地区 it's in, and the town it's in,
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这个城市的所在区域,城市的城镇
07:32
and the population人口 of it, and so on.
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人口等等
07:35
So I can browse浏览 this stuff东东.
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这样我就能浏览这些信息
07:37
So that's it, really.
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真的,就是这样
07:39
That is linked关联 data数据.
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这就是关联数据
07:41
I wrote an article文章 entitled标题 "Linked关联 Data数据" a couple一对 of years年份 ago
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我多年前在一篇文章中给它命名为“关联数据”
07:44
and soon不久 after that, things started开始 to happen发生.
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之后不久,有些事开始发生了
07:48
The idea理念 of linked关联 data数据 is that we get lots and lots and lots
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关联数据的想法就像我们得到了很多很多
07:52
of these boxes盒子 that Hans汉斯 had,
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类似汉斯拥有的盒子
07:54
and we get lots and lots and lots of things sprouting发芽.
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很多很多的事物开始发芽生长
07:56
It's not just a whole整个 lot of other plants植物.
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它带给我们相当多的植物
07:59
It's not just a root supplying供应 a plant,
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不仅仅是一个根供给一个植物
08:01
but for each of those plants植物, whatever随你 it is --
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对于这的每一个植物,无论它是什么
08:04
a presentation介绍, an analysis分析, somebody's某人的 looking for patterns模式 in the data数据 --
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一个演示,一个分析,某些人查看数据的样式
08:07
they get to look at all the data数据
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它们都着眼于所有的数据
08:10
and they get it connected连接的 together一起,
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并且它们把数据联系起来
08:12
and the really important重要 thing about data数据
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关于数据真正重要的是
08:14
is the more things you have to connect together一起, the more powerful强大 it is.
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你把很多东西联系起来,数据就更加有价值
08:16
So, linked关联 data数据.
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所以,关联数据
08:18
The meme米姆 went out there.
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由此而来
08:20
And, pretty漂亮 soon不久 Chris克里斯 BizerBizer at the Freie柏林自由 UniversitatUniversität大学 in Berlin柏林
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很快,来自柏林自由大学的克里斯拜泽
08:24
who was one of the first people to put interesting有趣 things up,
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做为第一人把有趣的东西放在一起
08:26
he noticed注意到 that Wikipedia维基百科 --
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他注意到维基百科
08:28
you know Wikipedia维基百科, the online线上 encyclopedia百科全书
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一部在线百科全书
08:31
with lots and lots of interesting有趣 documents文件 in it.
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有很多有趣的文档
08:33
Well, in those documents文件, there are little squares广场, little boxes盒子.
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在这些文档中,有些小方格子和小盒子
08:37
And in most information信息 boxes盒子, there's data数据.
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在许多信息盒子中,就是数据
08:40
So he wrote a program程序 to take the data数据, extract提取 it from Wikipedia维基百科,
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他写了 一个程序将数据从维基百科中提取出来
08:44
and put it into a blobBLOB of linked关联 data数据
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然后将它放到关联数据的blob(二进制大对象)中
08:46
on the web卷筒纸, which哪一个 he called dbpediaDBpedia中.
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在网络上,被他称之为dbpedia(数据库百科)
08:49
DbpediaDBpedia中 is represented代表 by the blue蓝色 blobBLOB in the middle中间 of this slide滑动
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这张幻灯片中部蓝色的blob表示Dbpedia
08:53
and if you actually其实 go and look up Berlin柏林,
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如果你去找柏林
08:55
you'll你会 find that there are other blobs斑点 of data数据
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你会发现还有其他的数据
08:57
which哪一个 also have stuff东东 about Berlin柏林, and they're linked关联 together一起.
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也有柏林的信息,它们被联系到了一起
09:00
So if you pull the data数据 from dbpediaDBpedia中 about Berlin柏林,
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所以,如果你要从dbpedia中摘出关于柏林的数据
09:03
you'll你会 end结束 up pulling up these other things as well.
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你也最终会摘出其他内容
09:05
And the exciting扣人心弦 thing is it's starting开始 to grow增长.
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令人兴奋的事情是它正在成长
09:08
This is just the grassroots基层 stuff东东 again, OK?
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这又是一个草根做的事情,对吗?
09:10
Let's think about data数据 for a bit.
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让我们多想想数据
09:13
Data数据 comes in fact事实 in lots and lots of different不同 forms形式.
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数据实际上来源于很多很多不同的形式
09:16
Think of the diversity多样 of the web卷筒纸. It's a really important重要 thing
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想想网络的多样性,很重要的一点
09:19
that the web卷筒纸 allows允许 you to put all kinds of data数据 up there.
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网络允许你将各式各样的数据放在一起
09:22
So it is with data数据. I could talk about all kinds of data数据.
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说到数据,我能说出各种各样的数据
09:25
We could talk about government政府 data数据, enterprise企业 data数据 is really important重要,
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我们可以说政府数据,企业数据真的很重要
09:29
there's scientific科学 data数据, there's personal个人 data数据,
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还有科学数据,个人数据
09:32
there's weather天气 data数据, there's data数据 about events事件,
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天气数据,关于事件的数据
09:34
there's data数据 about talks会谈, and there's news新闻 and there's all kinds of stuff东东.
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关于谈话的数据,还有新闻和各种类似的东西
09:38
I'm just going to mention提到 a few少数 of them
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我只提到了一小部分数据
09:41
so that you get the idea理念 of the diversity多样 of it,
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你们就可以看出其多样性
09:43
so that you also see how much unlocked解锁 potential潜在.
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所以你可以看到其中的潜力
09:47
Let's start开始 with government政府 data数据.
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让我们从政府数据说起
09:49
Barack巴拉克 Obama奥巴马 said in a speech言语,
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让我们从政府数据说起
09:51
that he -- American美国 government政府 data数据 would be available可得到 on the Internet互联网
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美国的政府数据将在互联网上被应用
09:56
in accessible无障碍 formats格式.
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以一种可访问的形式
09:58
And I hope希望 that they will put it up as linked关联 data数据.
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美国的政府数据将在互联网上以一种可访问的形式被应用
10:00
That's important重要. Why is it important重要?
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这非常重要,难道不是吗?
10:02
Not just for transparency透明度, yeah transparency透明度 in government政府 is important重要,
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不仅仅是为了透明性,透明性对政府很重要
10:05
but that data数据 -- this is the data数据 from all the government政府 departments部门
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尤其是从政府部门出来的数据更重要
10:08
Think about how much of that data数据 is about how life is lived生活 in America美国.
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想想有多少关系到在美国如何生活的数据
10:13
It's actual实际 useful有用. It's got value.
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它的确很有用,很有价值
10:15
I can use it in my company公司.
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我可以把它用在我的公司
10:17
I could use it as a kid孩子 to do my homework家庭作业.
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我可以像个小孩子般把它用在我的家庭作业中
10:19
So we're talking about making制造 the place地点, making制造 the world世界 run better
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所以,我们谈论的是让世界变得更好
10:22
by making制造 this data数据 available可得到.
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通过将这些数据变得更有用
10:24
In fact事实 if you're responsible主管 -- if you know about some data数据
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事实上,如果你们在负责 - 如果你知道一些数据
10:28
in a government政府 department, often经常 you find that
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关于政府的, 你经常会发现
10:30
these people, they're very tempted动心 to keep it --
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有些人,他们会被这些数据所吸引
10:33
Hans汉斯 calls电话 it database数据库 hugging拥抱.
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Hans称之为数据库拥抱
10:36
You hug拥抱 your database数据库, you don't want to let it go
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你拥抱你的数据库,你不会放它走
10:38
until直到 you've made制作 a beautiful美丽 website网站 for it.
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直到你为它建立了一个漂亮的网站
10:40
Well, I'd like to suggest建议 that rather --
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嗯,我想建议的是,除了建一个漂亮的网站
10:42
yes, make a beautiful美丽 website网站,
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是的,建一个漂亮的网站
10:44
who am I to say don't make a beautiful美丽 website网站?
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我没说不要建一个漂亮的网站
10:46
Make a beautiful美丽 website网站, but first
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建一个漂亮的网站,首先
10:49
give us the unadulterated纯正 data数据,
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要给我们纯粹的数据
10:52
we want the data数据.
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我们要的是数据
10:54
We want unadulterated纯正 data数据.
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我们要纯粹的数据
10:56
OK, we have to ask for raw生的 data数据 now.
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好,现在我们不得不要求原始数据了
10:59
And I'm going to ask you to practice实践 that, OK?
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我要请你们练习一下,好吗?
11:01
Can you say "raw生的"?
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请说“原始”
11:02
Audience听众: Raw生的.
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原始
11:03
Tim蒂姆 Berners-Lee伯纳斯 - 李: Can you say "data数据"?
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请说“数据”
11:04
Audience听众: Data数据.
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数据
11:05
TBLTBL: Can you say "now"?
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请说‘现在“
11:06
Audience听众: Now!
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现在
11:07
TBLTBL: Alright好的, "raw生的 data数据 now"!
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好,原始数据现在!
11:09
Audience听众: Raw生的 data数据 now!
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原始数据现在!
11:11
Practice实践 that. It's important重要 because you have no idea理念 the number of excuses借口
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这样练习是非常重要的
11:15
people come up with to hang onto their data数据
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因为你不知道那些拥有数据的人
11:17
and not give it to you, even though虽然 you've paid支付 for it as a taxpayer纳税人.
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有多少理由拒绝将数据给你,甚至你作为一个纳税人是为此付了钱的
11:21
And it's not just America美国. It's all over the world世界.
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这不仅仅存在于美国,全世界都一样
11:23
And it's not just governments政府, of course课程 -- it's enterprises企业 as well.
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也不仅仅在政府,当然也存在于企业。
11:26
So I'm just going to mention提到 a few少数 other thoughts思念 on data数据.
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我还想再谈谈关于数据的其他想法
11:29
Here we are at TEDTED, and all the time we are very conscious意识
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在TED,我们一直关注于
11:34
of the huge巨大 challenges挑战 that human人的 society社会 has right now --
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人类社会目前所面临的巨大问题
11:39
curing养护 cancer癌症, understanding理解 the brain for Alzheimer's老年痴呆症,
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癌症治疗,了解阿尔茨海默病
11:42
understanding理解 the economy经济 to make it a little bit more stable稳定,
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了解经济好让它稳定点
11:45
understanding理解 how the world世界 works作品.
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了解世界是如何运转的
11:47
The people who are going to solve解决 those -- the scientists科学家们 --
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那些致力于解决这些问题的科学家
11:49
they have half-formed半形成 ideas思路 in their head,
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他们脑海中有些还不成熟的想法
11:51
they try to communicate通信 those over the web卷筒纸.
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他们试图在网络上与他人交流
11:54
But a lot of the state of knowledge知识 of the human人的 race种族 at the moment时刻
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但是现状是很多人类的知识
11:57
is on databases数据库, often经常 sitting坐在 in their computers电脑,
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现在都在数据库中,放在他们的电脑里
12:00
and actually其实, currently目前 not shared共享.
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现在实际上也没被共享
12:03
In fact事实, I'll just go into one area --
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事实上,我就从一个方面来说明 -
12:06
if you're looking at Alzheimer's老年痴呆症, for example,
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如果你在研究阿尔茨海默病,以此为例,
12:08
drug药物 discovery发现 -- there is a whole整个 lot of linked关联 data数据 which哪一个 is just coming未来 out
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以药物发现为例 -- 这个领域具有相当多的刚刚出现的关联数据
12:11
because scientists科学家们 in that field领域 realize实现
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因为这个领域的科学家们意识到
12:13
this is a great way of getting得到 out of those silos筒仓,
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关联数据是一种很好的方法,可以帮助他们摆脱数据孤岛
12:16
because they had their genomics基因组学 data数据 in one database数据库
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因为他们在一个数据库中建立了基因图组
12:20
in one building建造, and they had their protein蛋白 data数据 in another另一个.
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他们在另一个数据库中建立蛋白质数据
12:23
Now, they are sticking症结 it onto -- linked关联 data数据 --
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现在,他们将基因图组和蛋白质数据形成了关联数据
12:26
and now they can ask the sort分类 of question, that you probably大概 wouldn't不会 ask,
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他们可以问排序的问题,也许你不会问
12:29
I wouldn't不会 ask -- they would.
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我不会问,但是他们会
12:31
What proteins蛋白质 are involved参与 in signal信号 transduction转导
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哪些蛋白质参与信号转导
12:33
and also related有关 to pyramidal金字塔 neurons神经元?
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并且也和锥体神经元相关?
12:35
Well, you take that mouthful一口 and you put it into Google谷歌.
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当你将这个问题放到Google上搜索
12:38
Of course课程, there's no page on the web卷筒纸 which哪一个 has answered回答 that question
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自然没有回答结果的页面
12:41
because nobody没有人 has asked that question before.
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因为之前没有人问过这样的问题
12:43
You get 223,000 hits点击 --
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虽然你得到了223,000个结果
12:45
no results结果 you can use.
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但是没有一个你用得上
12:47
You ask the linked关联 data数据 -- which哪一个 they've他们已经 now put together一起 --
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但是没有一个你用得上 -- 现在他们已经被放到了一起
12:50
32 hits点击, each of which哪一个 is a protein蛋白 which哪一个 has those properties性能
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命中32个结果,每一个结果都是与特征相关的蛋白质
12:54
and you can look at.
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并且你可以看到
12:56
The power功率 of being存在 able能够 to ask those questions问题, as a scientist科学家 --
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做为一个科学家, 询问那些问题的能力
12:59
questions问题 which哪一个 actually其实 bridge across横过 different不同 disciplines学科 --
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那些问题基本上都是跨学科的问题
13:01
is really a complete完成 sea change更改.
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是真正的C-change
13:04
It's very very important重要.
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这是非常非常重要的
13:06
Scientists科学家们 are totally完全 stymied陷入困境 at the moment时刻 --
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科学家们那时完全陷入了困境
13:08
the power功率 of the data数据 that other scientists科学家们 have collected is locked锁定 up
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因为其他科学家搜集的数据,其价值被锁起来了
13:13
and we need to get it unlocked解锁 so we can tackle滑车 those huge巨大 problems问题.
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我们需要将之解锁,以便处理那些大问题
13:16
Now if I go on like this, you'll你会 think that all the data数据 comes from huge巨大 institutions机构
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现在,如果我继续像这样讲
13:20
and has nothing to do with you.
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和你没有一点关系
13:23
But, that's not true真正.
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但是,这种想法并不对
13:25
In fact事实, data数据 is about our lives生活.
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事实上,数据关乎我们的生活
13:27
You just -- you log日志 on to your social社会 networking联网 site现场,
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你刚刚登陆了你的社会化网络站点
13:30
your favorite喜爱 one, you say, "This is my friend朋友."
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你最喜欢的一个,你说“这是我朋友”
13:32
Bing! Relationship关系. Data数据.
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叮!联系,数据
13:35
You say, "This photograph照片, it's about -- it depicts描绘 this person. "
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你说“这副照片,是这个人的”
13:38
Bing! That's data数据. Data数据, data数据, data数据.
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叮!那是数据。数据,数据,数据
13:41
Every一切 time you do things on the social社会 networking联网 site现场,
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每次你在社会化网络上做的事
13:43
the social社会 networking联网 site现场 is taking服用 data数据 and using运用 it -- re-purposing再重新考虑 it --
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社会化网络站点就获取数据并利用它
13:47
and using运用 it to make other people's人们 lives生活 more interesting有趣 on the site现场.
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重新设计数据的目的是为了让这个站点的其他人过得更有趣
13:51
But, when you go to another另一个 linked关联 data数据 site现场 --
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但是,当你上另一个关联数据网站
13:53
and let's say this is one about travel旅行,
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假设是一个旅游网站
13:56
and you say, "I want to send发送 this photo照片 to all the people in that group,"
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你说“我想把这张照片发给那个组里的所有人”
13:59
you can't get over the walls墙壁.
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但你却无法翻过这些墙
14:01
The Economist经济学家 wrote an article文章 about it, and lots of people have blogged博客 about it --
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经济学家曾经写了一篇关于这个问题的文章,并且许多人也发了相关博文表示出
14:03
tremendous巨大 frustration挫折.
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巨大的挫败感
14:04
The way to break打破 down the silos筒仓 is to get inter-operability互操作性
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打破孤岛的方式是实现互操作
14:06
between之间 social社会 networking联网 sites网站.
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在这些社交网络之间
14:08
We need to do that with linked关联 data数据.
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我们需要通过关联数据做这件事
14:10
One last type类型 of data数据 I'll talk about, maybe it's the most exciting扣人心弦.
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最后一种我将要谈到的数据,也许是最令人激动的
14:13
Before I came来了 down here, I looked看着 it up on OpenStreetMapOpenStreetMap的
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在我来这之前,我通过OpenStreetMap查找了一下
14:16
The OpenStreetMap'sOpenStreetMap的 a map地图, but it's also a Wiki维基.
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OpenStreetMap是一个地图,但同样也是一个维基
14:18
Zoom放大 in and that square广场 thing is a theater剧院 -- which哪一个 we're in right now --
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放大这个方块,这是一个剧场 -- 就是我们现在所处的地方 --
14:21
The Terrace阳台 Theater剧院. It didn't have a name名称 on it.
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特伦斯剧场(位于长滩市,加利福尼亚)。它现在还没有被标上名字
14:23
So I could go into edit编辑 mode模式, I could select选择 the theater剧院,
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所以我可以到编辑模式,选择剧场
14:25
I could add down at the bottom底部 the name名称, and I could save保存 it back.
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然后在底下填上名字,然后保存它
14:30
And now if you go back to the OpenStreetMapOpenStreetMap的. org组织,
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现在你再去访问OpenStreetMap.org
14:33
and you find this place地点, you will find that The Terrace阳台 Theater剧院 has got a name名称.
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你找到这个地方,你会发现它现在有名字了
14:36
I did that. Me!
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这都是我做的
14:38
I did that to the map地图. I just did that!
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我在地图上标的,刚刚做的
14:40
I put that up on there. Hey, you know what?
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我把它标注在那里。嗨,你知道吗
14:42
If I -- that street map地图 is all about everybody每个人 doing their bit
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如果除了我,每个人都在这个地图上标注一点
14:45
and it creates创建 an incredible难以置信 resource资源
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将会产生难以置信的资源
14:48
because everybody每个人 else其他 does theirs他们的.
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因为其他每个人都做了
14:51
And that is what linked关联 data数据 is all about.
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这就是关联数据
14:54
It's about people doing their bit
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每个人都做一点
14:57
to produce生产 a little bit, and it all connecting.
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生成一点内容,然后把它们连接起来
15:00
That's how linked关联 data数据 works作品.
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关联数据就是这样工作的
15:03
You do your bit. Everybody每个人 else其他 does theirs他们的.
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你做一些,每个人都做一些
15:07
You may可能 not have lots of data数据 which哪一个 you have yourself你自己 to put on there
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也许你的数据在关联数据中只是很小一部分
15:11
but you know to demand需求 it.
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但你知道你需要它
15:14
And we've我们已经 practiced that.
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我们已经在实践了
15:16
So, linked关联 data数据 -- it's huge巨大.
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关联数据 -- 是非常巨大的
15:20
I've only told you a very small number of things
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我只能告诉你很小一部分
15:23
There are data数据 in every一切 aspect方面 of our lives生活,
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我们生活的每个方面
15:25
every一切 aspect方面 of work and pleasure乐趣,
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工作和快乐的每个方面
15:28
and it's not just about the number of places地方 where data数据 comes,
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不管是数据出处的有多少
15:31
it's about connecting it together一起.
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关键是把它联系起来
15:34
And when you connect data数据 together一起, you get power功率
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当你把数据联系起来
15:37
in a way that doesn't happen发生 just with the web卷筒纸, with documents文件.
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你能从这样的方式中获取在网络或文档中无法获取的能量
15:40
You get this really huge巨大 power功率 out of it.
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你能从中得到巨大的能量
15:44
So, we're at the stage阶段 now
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现在我们处在一个阶段
15:47
where we have to do this -- the people who think it's a great idea理念.
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我们必须要做的阶段 -- 那些认为这是个伟大想法的人们
15:51
And all the people -- and I think there's a lot of people at TEDTED 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虽然 there's not an immediate即时 return返回 on the investment投资
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他们做事情并不是为了要使投资得到立即的回报
15:56
because it will only really pay工资 off when everybody每个人 else其他 has doneDONE it --
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因为只有当每个人都这么做了才会有所回报
15:59
they'll他们会 do it because they're the sort分类 of person who just does things
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他们将会这么做,因为他们是那类人
16:03
which哪一个 would be good if everybody每个人 else其他 did them.
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那类希望每个人都参与进来而让事情变好的人
16:06
OK, so it's called linked关联 data数据.
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OK,这就是关联数据
16:08
I want you to make it.
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我希望你参与
16:10
I want you to demand需求 it.
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我希望你需要它
16:12
And I think it's an idea理念 worth价值 spreading传播.
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我也认为这个想法值得宣扬
16:14
Thanks谢谢.
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谢谢
16:15
(Applause掌声)
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谢谢
Translated by Zheng Xiao
Reviewed by Halei Liu

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ABOUT THE SPEAKER
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.

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.

More profile about the speaker
Tim Berners-Lee | Speaker | TED.com