Tim Berners-Lee: The next Web of open, linked data

435,103 views ・ 2009-03-13

TED


请双击下面的英文字幕来播放视频。

翻译人员: Zheng Xiao 校对人员: Halei Liu
00:18
Time flies.
0
18330
2000
光阴似箭
00:20
It's actually almost 20 years ago
1
20330
2000
差不多是20年前
00:22
when I wanted to reframe the way we use information,
2
22330
4000
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.
3
26330
3000
协同工作方式的时候 - 我发明了万维网
00:29
Now, 20 years on, at TED,
4
29330
3000
20年过去了,现在,在TED
00:32
I want to ask your help in a new reframing.
5
32330
4000
我请求你们帮助创建新的架构
00:37
So going back to 1989,
6
37330
4000
回到1989年
00:41
I wrote a memo suggesting the global hypertext system.
7
41330
3000
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.
8
44330
3000
几乎没有什么人在真正用它
00:47
But 18 months later -- this is how innovation happens --
9
47330
4000
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,
10
51330
4000
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,
11
55330
2000
做一种游戏性质的项目
00:57
kick the tires of a new computer we'd got.
12
57330
2000
就拿我们新买来的电脑
00:59
And so he gave me the time to code it up.
13
59330
3000
他给了我些时间写代码实现
01:02
So I basically roughed out what HTML should look like:
14
62330
5000
我草拟了下HTML应该是什么样子
01:07
hypertext protocol, HTTP;
15
67330
3000
超文本协议 - HTTP -
01:10
the idea of URLs, these names for things
16
70330
3000
关于URLs 的想法 - 事物的名称
01:13
which started with HTTP.
17
73330
2000
这些事物都是以HTTP开头命名的
01:15
I wrote the code and put it out there.
18
75330
2000
我完成了代码并发布出来。
01:17
Why did I do it?
19
77330
2000
我为什么要这么做?
01:19
Well, it was basically frustration.
20
79330
2000
这是一个充满挫败感的过程
01:21
I was frustrated -- I was working as a software engineer
21
81330
4000
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,
22
85330
2000
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.
23
87330
2000
很多人从世界各地来到这里
01:29
They brought all sorts of different computers with them.
24
89330
3000
他们的电脑各不相同
01:32
They had all sorts of different data formats,
25
92330
3000
数据格式各不相同
01:35
all sorts, all kinds of documentation systems.
26
95330
2000
文件系统各不相同
01:37
So that, in all that diversity,
27
97330
3000
所以,这其中有很大的差异性
01:40
if I wanted to figure out how to build something
28
100330
2000
如果我想建立一点点东西
01:42
out of a bit of this and a bit of this,
29
102330
2000
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,
30
104330
4000
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,
31
108330
2000
运行一些新的程序
01:50
I would find the information I wanted in some new data format.
32
110330
5000
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.
33
115330
2000
这些都是不兼容的
01:57
It was just very frustrating.
34
117330
2000
这非常令人沮丧
01:59
The frustration was all this unlocked potential.
35
119330
2000
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.
36
121330
3000
事实上,这些磁盘里全是文件
02:04
So if you just imagined them all
37
124330
3000
所以如果你仅仅把他们
02:07
being part of some big, virtual documentation system in the sky,
38
127330
5000
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,
39
132330
2000
比如Internet
02:14
then life would be so much easier.
40
134330
2000
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
41
136330
4000
这样,一旦你有了这样的想法
02:20
and even if people don't read your memo --
42
140330
2000
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.
43
142330
3000
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.
44
145330
3000
他用铅笔在角落写到“模糊,但是令人兴奋”。
02:28
(Laughter)
45
148330
2000
(笑声)
02:30
But in general it was difficult -- it was really difficult to explain
46
150330
4000
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.
47
154330
2000
网络是什么样的
02:36
It's difficult to explain to people now that it was difficult then.
48
156330
2000
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
49
158330
3000
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.
50
161330
3000
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,
51
164330
2000
我现在可以向某人展示一大堆超链接
02:46
a page which has got links,
52
166330
2000
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.
53
168330
4000
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.
54
172330
2000
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.
55
174330
3000
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:
56
177330
3000
困难的是把它们想象出来
03:00
so, imagine that that link could have gone
57
180330
4000
所以,想象那个链接可以到
03:04
to virtually any document you could imagine.
58
184330
2000
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.
59
187330
4000
好的,这个跳跃对于人们是很难做到的
03:11
Well, some people did.
60
191330
2000
然而,一些人做到了
03:13
So yeah, it was difficult to explain, but there was a grassroots movement.
61
193330
3000
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.
62
197330
4000
这正是使它好玩的地方
03:21
That has been the most exciting thing,
63
201330
2000
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,
64
203330
2000
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
65
205330
2000
而是实际的交流,所有这些人的思想汇聚
03:27
getting together, sending the emails.
66
207330
2000
在一起,发送电子邮件
03:29
That's what it was like then.
67
209330
2000
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.
68
211330
3000
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 --
69
214330
2000
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?"
70
216330
3000
我说“你能把你的文档放到网络上吗?”
03:39
And you did.
71
219330
3000
然后,你做了
03:42
Thanks.
72
222330
1000
谢谢
03:43
It's been a blast, hasn't it?
73
223330
2000
这已经是一场疾风,不是吗?
03:45
I mean, it has been quite interesting
74
225330
2000
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
75
227330
2000
因为我们发现,网络上发生的事情似乎
03:49
really sort of blow us away.
76
229330
2000
已经把我们吹到了一边
03:51
They're much more than we'd originally imagined
77
231330
2000
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
78
233330
2000
最初的设计只是想把文档放在一起
03:55
that we started off with.
79
235330
2000
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.
80
237330
3000
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.
81
240330
4000
还是有巨大的可释放潜力
04:04
There is still a huge frustration
82
244330
2000
也有很大的挫败感
04:06
that people have because we haven't got data on the web as data.
83
246330
4000
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?
84
250330
2000
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?
85
252330
3000
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.
86
255330
3000
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.
87
258330
2000
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?
88
260330
6000
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 --
89
266330
4000
一个伟大的 – 很多人已经看过了 –
04:30
one of the great TED Talks.
90
270330
2000
一个伟大的TED演讲
04:32
Hans put up this presentation
91
272330
2000
汉斯在他的演示文档中
04:34
in which he showed, for various different countries, in various different colors --
92
274330
5000
使用不同的颜色表示不同的国家
04:39
he showed income levels on one axis
93
279330
3000
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.
94
282330
3000
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
95
285330
4000
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
96
289330
3000
这个演讲打破了很多人
04:52
about the economics in the developing world.
97
292330
4000
对发展中国家经济的神话
04:56
He put up a slide a little bit like this.
98
296330
2000
他展示了一个类似的幻灯片
04:58
It had underground all the data
99
298330
2000
数据都被埋在地下
05:00
OK, data is brown and boxy and boring,
100
300330
3000
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?
101
303330
2000
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
102
305330
3000
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
103
308330
4000
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.
104
312330
3000
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
105
315330
2000
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.
106
317330
5000
汉斯在美国网站找到各种数据和事物
05:22
He had put it together,
107
322330
2000
他把数据放到了一起
05:24
combined it into something more interesting than the original pieces
108
324330
3000
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,
109
327330
5000
然后把数据放到这个软件中
05:32
which I think his son developed, originally,
110
332330
2000
这个软件我觉得是他儿子开发的
05:34
and produces this wonderful presentation.
111
334330
3000
最终他做出了这个美妙的演示
05:37
And Hans made a point
112
337330
2000
最后汉斯说道
05:39
of saying, "Look, it's really important to have a lot of data."
113
339330
4000
“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
114
343330
3000
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."
115
346330
4000
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
116
350330
2000
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,
117
352330
4000
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
118
356330
5000
而是这个世界上任何人
06:01
and so virtually everything you can imagine is on the web
119
361330
2000
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.
120
363330
2000
然后把它们称为关联数据
06:05
The technology is linked data, and it's extremely simple.
121
365330
2000
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:
122
367330
4000
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 --
123
371330
3000
第一条规则是,需要有HTTP的名字
06:14
those things that start with "http:" --
124
374330
2000
那些东西要以http:开头
06:16
we're using them not just for documents now,
125
376330
4000
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.
126
380330
2000
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,
127
382330
2000
我们对人物、地点
06:24
we're using them for your products, we're using them for events.
128
384330
4000
产品,事件等都这样用
06:28
All kinds of conceptual things, they have names now that start with HTTP.
129
388330
4000
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
130
392330
5000
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
131
397330
2000
我可以从网上获取数据
06:39
using the HTTP protocol from the web,
132
399330
2000
通过HTTP协议
06:41
I will get back some data in a standard format
133
401330
3000
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
134
404330
5000
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.
135
409330
2000
某个事物或者事件的
06:51
Who's at the event? Whatever it is about that person,
136
411330
2000
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.
137
413330
2000
他们什么时候生的,等等
06:55
So the second rule is I get important information back.
138
415330
2000
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
139
417330
4000
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,
140
421330
3000
不仅仅是某人的身高、体重和出生日期
07:04
it's got relationships.
141
424330
2000
还有数据间的关系
07:06
Data is relationships.
142
426330
2000
数据是有联系的
07:08
Interestingly, data is relationships.
143
428330
2000
很有趣,数据是有联系的
07:10
This person was born in Berlin; Berlin is in Germany.
144
430330
4000
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
145
434330
3000
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
146
437330
3000
另一件与之有联系的事物
07:20
is given one of those names that starts HTTP.
147
440330
4000
就以HTTP开头命名
07:24
So, I can go ahead and look that thing up.
148
444330
2000
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
149
446330
3000
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,
150
449330
3000
这个城市的所在区域,城市的城镇
07:32
and the population of it, and so on.
151
452330
3000
人口等等
07:35
So I can browse this stuff.
152
455330
2000
这样我就能浏览这些信息
07:37
So that's it, really.
153
457330
2000
真的,就是这样
07:39
That is linked data.
154
459330
2000
这就是关联数据
07:41
I wrote an article entitled "Linked Data" a couple of years ago
155
461330
3000
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.
156
464330
4000
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
157
468330
4000
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,
158
472330
2000
类似汉斯拥有的盒子
07:54
and we get lots and lots and lots of things sprouting.
159
474330
2000
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.
160
476330
3000
它带给我们相当多的植物
07:59
It's not just a root supplying a plant,
161
479330
2000
不仅仅是一个根供给一个植物
08:01
but for each of those plants, whatever it is --
162
481330
3000
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 --
163
484330
3000
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
164
487330
3000
它们都着眼于所有的数据
08:10
and they get it connected together,
165
490330
2000
并且它们把数据联系起来
08:12
and the really important thing about data
166
492330
2000
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.
167
494330
2000
你把很多东西联系起来,数据就更加有价值
08:16
So, linked data.
168
496330
2000
所以,关联数据
08:18
The meme went out there.
169
498330
2000
由此而来
08:20
And, pretty soon Chris Bizer at the Freie Universitat in Berlin
170
500330
4000
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,
171
504330
2000
做为第一人把有趣的东西放在一起
08:26
he noticed that Wikipedia --
172
506330
2000
他注意到维基百科
08:28
you know Wikipedia, the online encyclopedia
173
508330
3000
一部在线百科全书
08:31
with lots and lots of interesting documents in it.
174
511330
2000
有很多有趣的文档
08:33
Well, in those documents, there are little squares, little boxes.
175
513330
4000
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.
176
517330
3000
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,
177
520330
4000
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
178
524330
2000
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.
179
526330
3000
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
180
529330
4000
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,
181
533330
2000
如果你去找柏林
08:55
you'll find that there are other blobs of data
182
535330
2000
你会发现还有其他的数据
08:57
which also have stuff about Berlin, and they're linked together.
183
537330
3000
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,
184
540330
3000
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.
185
543330
2000
你也最终会摘出其他内容
09:05
And the exciting thing is it's starting to grow.
186
545330
3000
令人兴奋的事情是它正在成长
09:08
This is just the grassroots stuff again, OK?
187
548330
2000
这又是一个草根做的事情,对吗?
09:10
Let's think about data for a bit.
188
550330
3000
让我们多想想数据
09:13
Data comes in fact in lots and lots of different forms.
189
553330
3000
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
190
556330
3000
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.
191
559330
3000
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.
192
562330
2000
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,
193
565330
4000
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,
194
569330
3000
还有科学数据,个人数据
09:32
there's weather data, there's data about events,
195
572330
2000
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.
196
574330
4000
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
197
578330
3000
我只提到了一小部分数据
09:41
so that you get the idea of the diversity of it,
198
581330
2000
你们就可以看出其多样性
09:43
so that you also see how much unlocked potential.
199
583330
4000
所以你可以看到其中的潜力
09:47
Let's start with government data.
200
587330
2000
让我们从政府数据说起
09:49
Barack Obama said in a speech,
201
589330
2000
让我们从政府数据说起
09:51
that he -- American government data would be available on the Internet
202
591330
5000
美国的政府数据将在互联网上被应用
09:56
in accessible formats.
203
596330
2000
以一种可访问的形式
09:58
And I hope that they will put it up as linked data.
204
598330
2000
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?
205
600330
2000
这非常重要,难道不是吗?
10:02
Not just for transparency, yeah transparency in government is important,
206
602330
3000
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
207
605330
3000
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.
208
608330
5000
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.
209
613330
2000
它的确很有用,很有价值
10:15
I can use it in my company.
210
615330
2000
我可以把它用在我的公司
10:17
I could use it as a kid to do my homework.
211
617330
2000
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
212
619330
3000
所以,我们谈论的是让世界变得更好
10:22
by making this data available.
213
622330
2000
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
214
624330
4000
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
215
628330
2000
关于政府的, 你经常会发现
10:30
these people, they're very tempted to keep it --
216
630330
3000
有些人,他们会被这些数据所吸引
10:33
Hans calls it database hugging.
217
633330
3000
Hans称之为数据库拥抱
10:36
You hug your database, you don't want to let it go
218
636330
2000
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.
219
638330
2000
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 --
220
640330
2000
嗯,我想建议的是,除了建一个漂亮的网站
10:42
yes, make a beautiful website,
221
642330
2000
是的,建一个漂亮的网站
10:44
who am I to say don't make a beautiful website?
222
644330
2000
我没说不要建一个漂亮的网站
10:46
Make a beautiful website, but first
223
646330
3000
建一个漂亮的网站,首先
10:49
give us the unadulterated data,
224
649330
3000
要给我们纯粹的数据
10:52
we want the data.
225
652330
2000
我们要的是数据
10:54
We want unadulterated data.
226
654330
2000
我们要纯粹的数据
10:56
OK, we have to ask for raw data now.
227
656330
3000
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?
228
659330
2000
我要请你们练习一下,好吗?
11:01
Can you say "raw"?
229
661330
1000
请说“原始”
11:02
Audience: Raw.
230
662330
1000
原始
11:03
Tim Berners-Lee: Can you say "data"?
231
663330
1000
请说“数据”
11:04
Audience: Data.
232
664330
1000
数据
11:05
TBL: Can you say "now"?
233
665330
1000
请说‘现在“
11:06
Audience: Now!
234
666330
1000
现在
11:07
TBL: Alright, "raw data now"!
235
667330
2000
好,原始数据现在!
11:09
Audience: Raw data now!
236
669330
2000
原始数据现在!
11:11
Practice that. It's important because you have no idea the number of excuses
237
671330
4000
这样练习是非常重要的
11:15
people come up with to hang onto their data
238
675330
2000
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.
239
677330
4000
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.
240
681330
2000
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.
241
683330
3000
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.
242
686330
3000
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
243
689330
5000
在TED,我们一直关注于
11:34
of the huge challenges that human society has right now --
244
694330
5000
人类社会目前所面临的巨大问题
11:39
curing cancer, understanding the brain for Alzheimer's,
245
699330
3000
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,
246
702330
3000
了解经济好让它稳定点
11:45
understanding how the world works.
247
705330
2000
了解世界是如何运转的
11:47
The people who are going to solve those -- the scientists --
248
707330
2000
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,
249
709330
2000
他们脑海中有些还不成熟的想法
11:51
they try to communicate those over the web.
250
711330
3000
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
251
714330
3000
但是现状是很多人类的知识
11:57
is on databases, often sitting in their computers,
252
717330
3000
现在都在数据库中,放在他们的电脑里
12:00
and actually, currently not shared.
253
720330
3000
现在实际上也没被共享
12:03
In fact, I'll just go into one area --
254
723330
3000
事实上,我就从一个方面来说明 -
12:06
if you're looking at Alzheimer's, for example,
255
726330
2000
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
256
728330
3000
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
257
731330
2000
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,
258
733330
3000
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
259
736330
4000
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.
260
740330
3000
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 --
261
743330
3000
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,
262
746330
3000
他们可以问排序的问题,也许你不会问
12:29
I wouldn't ask -- they would.
263
749330
2000
我不会问,但是他们会
12:31
What proteins are involved in signal transduction
264
751330
2000
哪些蛋白质参与信号转导
12:33
and also related to pyramidal neurons?
265
753330
2000
并且也和锥体神经元相关?
12:35
Well, you take that mouthful and you put it into Google.
266
755330
3000
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
267
758330
3000
自然没有回答结果的页面
12:41
because nobody has asked that question before.
268
761330
2000
因为之前没有人问过这样的问题
12:43
You get 223,000 hits --
269
763330
2000
虽然你得到了223,000个结果
12:45
no results you can use.
270
765330
2000
但是没有一个你用得上
12:47
You ask the linked data -- which they've now put together --
271
767330
3000
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
272
770330
4000
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.
273
774330
2000
并且你可以看到
12:56
The power of being able to ask those questions, as a scientist --
274
776330
3000
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 --
275
779330
2000
那些问题基本上都是跨学科的问题
13:01
is really a complete sea change.
276
781330
3000
是真正的C-change
13:04
It's very very important.
277
784330
2000
这是非常非常重要的
13:06
Scientists are totally stymied at the moment --
278
786330
2000
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
279
788330
5000
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.
280
793330
3000
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
281
796330
4000
现在,如果我继续像这样讲
13:20
and has nothing to do with you.
282
800330
3000
和你没有一点关系
13:23
But, that's not true.
283
803330
2000
但是,这种想法并不对
13:25
In fact, data is about our lives.
284
805330
2000
事实上,数据关乎我们的生活
13:27
You just -- you log on to your social networking site,
285
807330
3000
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."
286
810330
2000
你最喜欢的一个,你说“这是我朋友”
13:32
Bing! Relationship. Data.
287
812330
3000
叮!联系,数据
13:35
You say, "This photograph, it's about -- it depicts this person. "
288
815330
3000
你说“这副照片,是这个人的”
13:38
Bing! That's data. Data, data, data.
289
818330
3000
叮!那是数据。数据,数据,数据
13:41
Every time you do things on the social networking site,
290
821330
2000
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 --
291
823330
4000
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.
292
827330
4000
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 --
293
831330
2000
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,
294
833330
3000
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,"
295
836330
3000
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.
296
839330
2000
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 --
297
841330
2000
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.
298
843330
1000
巨大的挫败感
14:04
The way to break down the silos is to get inter-operability
299
844330
2000
打破孤岛的方式是实现互操作
14:06
between social networking sites.
300
846330
2000
在这些社交网络之间
14:08
We need to do that with linked data.
301
848330
2000
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.
302
850330
3000
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
303
853330
3000
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.
304
856330
2000
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 --
305
858330
3000
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.
306
861330
2000
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,
307
863330
2000
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.
308
865330
5000
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,
309
870330
3000
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.
310
873330
3000
你找到这个地方,你会发现它现在有名字了
14:36
I did that. Me!
311
876330
2000
这都是我做的
14:38
I did that to the map. I just did that!
312
878330
2000
我在地图上标的,刚刚做的
14:40
I put that up on there. Hey, you know what?
313
880330
2000
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
314
882330
3000
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
315
885330
3000
将会产生难以置信的资源
14:48
because everybody else does theirs.
316
888330
3000
因为其他每个人都做了
14:51
And that is what linked data is all about.
317
891330
3000
这就是关联数据
14:54
It's about people doing their bit
318
894330
3000
每个人都做一点
14:57
to produce a little bit, and it all connecting.
319
897330
3000
生成一点内容,然后把它们连接起来
15:00
That's how linked data works.
320
900330
3000
关联数据就是这样工作的
15:03
You do your bit. Everybody else does theirs.
321
903330
4000
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
322
907330
4000
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.
323
911330
3000
但你知道你需要它
15:14
And we've practiced that.
324
914330
2000
我们已经在实践了
15:16
So, linked data -- it's huge.
325
916330
4000
关联数据 -- 是非常巨大的
15:20
I've only told you a very small number of things
326
920330
3000
我只能告诉你很小一部分
15:23
There are data in every aspect of our lives,
327
923330
2000
我们生活的每个方面
15:25
every aspect of work and pleasure,
328
925330
3000
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,
329
928330
3000
不管是数据出处的有多少
15:31
it's about connecting it together.
330
931330
3000
关键是把它联系起来
15:34
And when you connect data together, you get power
331
934330
3000
当你把数据联系起来
15:37
in a way that doesn't happen just with the web, with documents.
332
937330
3000
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.
333
940330
4000
你能从中得到巨大的能量
15:44
So, we're at the stage now
334
944330
3000
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.
335
947330
4000
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 --
336
951330
3000
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
337
954330
2000
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 --
338
956330
3000
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
339
959330
4000
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.
340
963330
3000
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.
341
966330
2000
OK,这就是关联数据
16:08
I want you to make it.
342
968330
2000
我希望你参与
16:10
I want you to demand it.
343
970330
2000
我希望你需要它
16:12
And I think it's an idea worth spreading.
344
972330
2000
我也认为这个想法值得宣扬
16:14
Thanks.
345
974330
1000
谢谢
16:15
(Applause)
346
975330
3000
谢谢
关于本网站

这个网站将向你介绍对学习英语有用的YouTube视频。你将看到来自世界各地的一流教师教授的英语课程。双击每个视频页面上显示的英文字幕,即可从那里播放视频。字幕会随着视频的播放而同步滚动。如果你有任何意见或要求,请使用此联系表与我们联系。

https://forms.gle/WvT1wiN1qDtmnspy7