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翻译人员: Zheng Xiao
校对人员: Halei Liu
00:18
Time flies.
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光阴似箭
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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当我想重新构造我们使用信息
00:26
the way we work together: I invented the World Wide Web.
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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 on, at TED,
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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.
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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 suggesting the global hypertext system.
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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 really did anything with it, pretty much.
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几乎没有什么人在真正用它
00:47
But 18 months later -- this is how innovation happens --
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但是,18个月后 - 革新就是这么开始的
00:51
18 months later, my boss 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 of a play project,
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做一种游戏性质的项目
00:57
kick the tires of a new computer we'd 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 roughed out what HTML should look like:
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我草拟了下HTML应该是什么样子
01:07
hypertext protocol, HTTP;
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超文本协议 - HTTP -
01:10
the idea of URLs, these names for things
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关于URLs 的想法 - 事物的名称
01:13
which started with HTTP.
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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 frustration.
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这是一个充满挫败感的过程
01:21
I was frustrated -- I was working as a software engineer
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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, very exciting lab,
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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 from all over the world.
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很多人从世界各地来到这里
01:29
They brought all sorts of different computers with them.
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他们的电脑各不相同
01:32
They had all sorts of different data formats,
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数据格式各不相同
01:35
all sorts, all kinds of documentation systems.
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文件系统各不相同
01:37
So that, in all that diversity,
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所以,这其中有很大的差异性
01:40
if I wanted to figure out how to build 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 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 to run some new program,
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运行一些新的程序
01:50
I would find the information I wanted in some new data format.
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以便我能在新的数据格式中找到一些信息
01:55
And these were all incompatible.
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这些都是不兼容的
01:57
It was just very frustrating.
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这非常令人沮丧
01:59
The frustration was all this unlocked potential.
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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, on all these discs there were documents.
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事实上,这些磁盘里全是文件
02:04
So if you just imagined them all
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所以如果你仅仅把他们
02:07
being part of some big, virtual documentation system in the sky,
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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,
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比如Internet
02:14
then life would be so much easier.
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生活就会简单得多
02:16
Well, once you've had an idea like that it kind of gets under your skin
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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 --
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即使人们并没有读到你的备忘录
02:22
actually he did, it was found after he died, his copy.
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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, "Vague, but exciting," in pencil, 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)
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(笑声)
02:30
But in general it was difficult -- it was really difficult to explain
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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 was like.
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网络是什么样的
02:36
It's difficult to explain 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 TED started, there was no web
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但是 - 对,当TED开始时,那时没有网络
02:41
so things like "click" didn't have the same meaning.
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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 somebody a piece of hypertext,
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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 has got links,
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某个包含链接的网页
02:48
and we click on the link and bing -- there'll be another hypertext 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.
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没什么令人印象深刻的
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:
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困难的是把它们想象出来
03:00
so, imagine that that link could have gone
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所以,想象那个链接可以到
03:04
to virtually any document you could imagine.
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任何实际的你能想象得到的文件
03:07
Alright, that is the leap that was very difficult for people to make.
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好的,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, but there was a grassroots movement.
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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 it most fun.
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这正是使它好玩的地方
03:21
That has been the most exciting thing,
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也是最令人激动人心的事情
03:23
not the technology, not the things people have done with it,
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不是技术,不是人们用它所做的东西
03:25
but actually the community, the spirit 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 together, sending the emails.
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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, 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, more or less, to put their documents --
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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 on this web 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.
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谢谢
03:43
It's been a blast, hasn't it?
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这已经是一场疾风,不是吗?
03:45
I mean, it has been quite interesting
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我的意思是,它已经非常有趣
03:47
because we've found out that the things that happen with the web
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因为我们发现,网络上发生的事情似乎
03:49
really sort of blow 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 originally imagined
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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 the little, initial website
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最初的设计只是想把文档放在一起
03:55
that we started 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 on the web.
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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 unlocked potential.
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还是有巨大的可释放潜力
04:04
There is still a huge frustration
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也有很大的挫败感
04:06
that people have because we haven't got data on the web as data.
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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"? What's the difference -- documents, data?
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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 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 links 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 -- you can do all kinds of stuff with a computer.
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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 seen Hans Rosling's 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 it --
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一个伟大的 – 很多人已经看过了 –
04:30
one of the great TED Talks.
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一个伟大的TED演讲
04:32
Hans put up this presentation
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汉斯在他的演示文档中
04:34
in which he showed, for various different countries, in various different colors --
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使用不同的颜色表示不同的国家
04:39
he showed income levels on one axis
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他在一个轴上显示收入水平
04:42
and he showed infant mortality, and he shot this thing animated through 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 taken this data and made a presentation
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他使用这些数据完成了一场演讲,
04:49
which just shattered a lot of myths that people had
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这个演讲打破了很多人
04:52
about the economics in the developing world.
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对发展中国家经济的神话
04:56
He put up a slide 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 all the data
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数据都被埋在地下
05:00
OK, data is brown and boxy and boring,
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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 you can't naturally use by itself
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因为,你不能漫无目的地使用数据
05:08
But in fact, data drives a huge amount of what happens in our lives
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但事实上,数据驱动了我们的生活
05:12
and it happens because somebody takes that data 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, Hans had put the data together
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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 from all kinds of United Nations websites 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,
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他把数据放到了一起
05:24
combined it into something more interesting than the original 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 put it into this software,
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然后把数据放到这个软件中
05:32
which I think his son developed, originally,
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这个软件我觉得是他儿子开发的
05:34
and produces this wonderful presentation.
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最终他做出了这个美妙的演示
05:37
And Hans made a point
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最后汉斯说道
05:39
of saying, "Look, it's really important to have a lot of data."
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“瞧,有大量的数据是非常重要的”
05:43
And I was happy to see that at the party last night
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我高兴地看到在昨天的晚会上
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 being connected, 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 where everybody has put data on the web
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而是这个世界上任何人
06:01
and so virtually everything you can imagine is on the web
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都把数据和可以虚拟化的一切内容放到网络上
06:03
and then calling that linked data.
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然后把它们称为关联数据
06:05
The technology is linked data, and it's extremely simple.
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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 there are three rules:
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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 HTTP names --
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第一条规则是,需要有HTTP的名字
06:14
those things that start with "http:" --
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那些东西要以http:开头
06:16
we're using them not just for documents now,
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我们现在不仅对文档这样用
06:20
we're using them for things that the documents are about.
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对文档描述的事物也这样用
06:22
We're using them for people, we're using them for places,
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我们对人物、地点
06:24
we're using them for your products, we're using them for events.
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产品,事件等都这样用
06:28
All kinds of conceptual things, they have names now that start with HTTP.
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所有概念化的东西现在都以HTTP开头命名
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 thing with it and I fetch the data
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我可以从网上获取数据
06:39
using the HTTP protocol from the web,
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通过HTTP协议
06:41
I will get back some data in a standard format
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我将得到一些标准的格式化数据
06:44
which is kind of useful data that somebody might 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.
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某个事物或者事件的
06:51
Who's at the event? Whatever it is about that person,
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事件的主人公是谁?关于这个人的所有信息
06:53
where they were born, things like that.
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他们什么时候生的,等等
06:55
So the second rule is I get important information 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 rule is that when I get back that information
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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 height and weight and when they were born,
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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.
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还有数据间的关系
07:06
Data is relationships.
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数据是有联系的
07:08
Interestingly, data is relationships.
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很有趣,数据是有联系的
07:10
This person was born in Berlin; Berlin is in Germany.
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这个人出生在柏林,柏林在德国
07:14
And when it has relationships, whenever it expresses a relationship
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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 to
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另一件与之有联系的事物
07:20
is given one of those names that starts HTTP.
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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; 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 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 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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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 data.
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这就是关联数据
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给它命名为“关联数据”
07:44
and soon after that, things started to happen.
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之后不久,有些事开始发生了
07:48
The idea of linked data 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 that Hans 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.
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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 lot of other plants.
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它带给我们相当多的植物
07:59
It's not just a root supplying 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, whatever 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, an analysis, somebody's looking for patterns in the data --
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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
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它们都着眼于所有的数据
08:10
and they get it connected together,
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并且它们把数据联系起来
08:12
and the really important thing about data
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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, the more powerful 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 data.
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所以,关联数据
08:18
The meme went out there.
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由此而来
08:20
And, pretty soon Chris Bizer at the Freie Universitat in Berlin
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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 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 that Wikipedia --
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他注意到维基百科
08:28
you know Wikipedia, the online encyclopedia
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一部在线百科全书
08:31
with lots and lots of interesting documents in it.
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有很多有趣的文档
08:33
Well, in those documents, there are little squares, little boxes.
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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 boxes, there's data.
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在许多信息盒子中,就是数据
08:40
So he wrote a program to take the data, extract it from Wikipedia,
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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 blob of linked data
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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, which he called dbpedia.
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在网络上,被他称之为dbpedia(数据库百科)
08:49
Dbpedia is represented by the blue blob in the middle of this slide
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这张幻灯片中部蓝色的blob表示Dbpedia
08:53
and if you actually go and look up Berlin,
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如果你去找柏林
08:55
you'll find that there are other blobs of data
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你会发现还有其他的数据
08:57
which also have stuff about Berlin, and they're linked together.
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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 from dbpedia about Berlin,
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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 end 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 thing is it's starting to grow.
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令人兴奋的事情是它正在成长
09:08
This is just the grassroots stuff 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 for a bit.
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让我们多想想数据
09:13
Data comes in fact in lots and lots of different forms.
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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 of the web. It's a really important thing
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想想网络的多样性,很重要的一点
09:19
that the web allows you to put all kinds of data 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. I could talk about all kinds of data.
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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 data, enterprise data is really important,
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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 data, there's personal data,
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还有科学数据,个人数据
09:32
there's weather data, there's data about events,
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天气数据,关于事件的数据
09:34
there's data about talks, and there's news and there's all kinds of stuff.
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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 a few 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 of the diversity 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 potential.
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所以你可以看到其中的潜力
09:47
Let's start with government data.
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让我们从政府数据说起
09:49
Barack Obama said in a speech,
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让我们从政府数据说起
09:51
that he -- American government data would be available on the Internet
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美国的政府数据将在互联网上被应用
09:56
in accessible formats.
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以一种可访问的形式
09:58
And I hope that they will put it up as linked data.
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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. Why is it important?
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这非常重要,难道不是吗?
10:02
Not just for transparency, yeah transparency in government is important,
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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 -- this is the data from all the government departments
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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 is about how life is lived in America.
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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 useful. 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.
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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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我可以像个小孩子般把它用在我的家庭作业中
10:19
So we're talking about making the place, making the world 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 this data available.
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通过将这些数据变得更有用
10:24
In fact if you're responsible -- if you know about some data
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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 department, often 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 to keep it --
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有些人,他们会被这些数据所吸引
10:33
Hans calls it database hugging.
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Hans称之为数据库拥抱
10:36
You hug your database, 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 you've made a beautiful website 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 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 website,
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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 website?
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我没说不要建一个漂亮的网站
10:46
Make a beautiful website, but first
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建一个漂亮的网站,首先
10:49
give us the unadulterated data,
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要给我们纯粹的数据
10:52
we want the data.
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我们要的是数据
10:54
We want unadulterated data.
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我们要纯粹的数据
10:56
OK, we have to ask for raw data 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 that, OK?
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我要请你们练习一下,好吗?
11:01
Can you say "raw"?
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请说“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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请说“数据”
11:04
Audience: Data.
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数据
11:05
TBL: Can you say "now"?
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请说‘现在“
11:06
Audience: Now!
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现在
11:07
TBL: Alright, "raw data now"!
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好,原始数据现在!
11:09
Audience: Raw data now!
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原始数据现在!
11:11
Practice that. It's important because you have no idea the number of excuses
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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
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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 you've paid for it as a taxpayer.
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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. It's all over the world.
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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, of course -- it's enterprises 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 a few other thoughts on data.
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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 TED, and all the time we are very conscious
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在TED,我们一直关注于
11:34
of the huge challenges that human society has right now --
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人类社会目前所面临的巨大问题
11:39
curing cancer, understanding the brain for Alzheimer's,
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癌症治疗,了解阿尔茨海默病
11:42
understanding the economy to make it a little bit more stable,
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了解经济好让它稳定点
11:45
understanding how the world works.
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了解世界是如何运转的
11:47
The people who are going to solve those -- the scientists --
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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 ideas 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 those over the web.
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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 of the human race at the moment
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但是现状是很多人类的知识
11:57
is on databases, often sitting in their computers,
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现在都在数据库中,放在他们的电脑里
12:00
and actually, currently not shared.
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现在实际上也没被共享
12:03
In fact, 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, 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 discovery -- there is a whole lot of linked data which is just coming 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 in that field realize
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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 out of those silos,
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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 data in one database
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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, and they had their protein data in another.
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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 it onto -- linked data --
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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 of question, that you probably wouldn't 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 ask -- they would.
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我不会问,但是他们会
12:31
What proteins are involved in signal transduction
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哪些蛋白质参与信号转导
12:33
and also related to pyramidal neurons?
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并且也和锥体神经元相关?
12:35
Well, you take that mouthful and you put it into Google.
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当你将这个问题放到Google上搜索
12:38
Of course, there's no page on the web which has answered that question
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自然没有回答结果的页面
12:41
because nobody 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 --
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虽然你得到了223,000个结果
12:45
no results you can use.
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但是没有一个你用得上
12:47
You ask the linked data -- which they've now put together --
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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, each of which is a protein which has those properties
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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 of being able to ask those questions, as a scientist --
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做为一个科学家, 询问那些问题的能力
12:59
questions which actually bridge across different disciplines --
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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 sea change.
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是真正的C-change
13:04
It's very very important.
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这是非常非常重要的
13:06
Scientists are totally stymied at the moment --
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科学家们那时完全陷入了困境
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 so we can tackle those huge problems.
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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 think that all the data comes from huge institutions
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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.
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但是,这种想法并不对
13:25
In fact, data is about our lives.
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事实上,数据关乎我们的生活
13:27
You just -- you log on to your social networking site,
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你刚刚登陆了你的社会化网络站点
13:30
your favorite one, you say, "This is my friend."
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你最喜欢的一个,你说“这是我朋友”
13:32
Bing! Relationship. Data.
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叮!联系,数据
13:35
You say, "This photograph, it's about -- it depicts this person. "
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你说“这副照片,是这个人的”
13:38
Bing! That's data. Data, data, data.
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叮!那是数据。数据,数据,数据
13:41
Every time you do things on the social networking site,
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每次你在社会化网络上做的事
13:43
the social networking site is taking data and using it -- re-purposing 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 it to make other people's lives more interesting on the site.
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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 linked data site --
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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,
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假设是一个旅游网站
13:56
and you say, "I want to send this photo 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.
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但你却无法翻过这些墙
14:01
The Economist wrote an article about it, and lots of people have blogged 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 frustration.
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巨大的挫败感
14:04
The way to break down the silos is to get inter-operability
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打破孤岛的方式是实现互操作
14:06
between social networking sites.
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在这些社交网络之间
14:08
We need to do that with linked data.
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我们需要通过关联数据做这件事
14:10
One last type of data I'll talk about, maybe it's the most exciting.
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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 down here, I looked it up on OpenStreetMap
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在我来这之前,我通过OpenStreetMap查找了一下
14:16
The OpenStreetMap's a map, but it's also a Wiki.
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OpenStreetMap是一个地图,但同样也是一个维基
14:18
Zoom in and that square thing is a theater -- which 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 Theater. It didn't have a name 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 mode, I could select the theater,
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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 the name, and I could save 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 OpenStreetMap. org,
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现在你再去访问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. 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 is all about everybody 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 an incredible resource
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将会产生难以置信的资源
14:48
because everybody else does theirs.
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因为其他每个人都做了
14:51
And that is what linked data 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 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 data works.
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关联数据就是这样工作的
15:03
You do your bit. Everybody else does theirs.
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你做一些,每个人都做一些
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 it.
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但你知道你需要它
15:14
And we've practiced that.
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我们已经在实践了
15:16
So, linked data -- it's huge.
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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 in every aspect of our lives,
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我们生活的每个方面
15:25
every aspect of work and pleasure,
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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 where data comes,
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不管是数据出处的有多少
15:31
it's about connecting it together.
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关键是把它联系起来
15:34
And when you connect data together, you get power
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当你把数据联系起来
15:37
in a way that doesn't happen just with the web, with documents.
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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 power 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 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.
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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 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 off when everybody else has done 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 do it because they're the sort 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 would be good if everybody else 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 data.
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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 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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我也认为这个想法值得宣扬
16:14
Thanks.
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谢谢
16:15
(Applause)
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谢谢
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