Ben Wellington: How we found the worst place to park in New York City — using big data
80,027 views ・ 2015-02-26
请双击下面的英文字幕来播放视频。
翻译人员: zoe hong
校对人员: Min WANG
00:12
Six thousand miles of road,
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六千英里的公路,
00:15
600 miles of subway track,
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六百英里的铁路,
00:17
400 miles of bike lanes
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四百英里的自行车道,
00:19
and a half a mile of tram track,
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以及半英里的电车轨道,
00:21
if you've ever been to Roosevelt Island.
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如果你曾经去过罗斯福岛就会知道。
00:23
These are the numbers that make up
the infrastructure of New York City.
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上述数据构成了纽约的基础设施网络。
00:26
These are the statistics
of our infrastructure.
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这些是我们基础设施的统计数据。
这些数据你们都可以在
市政机关的报告中找到。
00:29
They're the kind of numbers you can find
released in reports by city agencies.
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比如,交通部可能会告诉你
00:32
For example, the Department
of Transportation will probably tell you
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他们维修了多少英里的路。
MTA(大纽约交通运输管理局)
会吹嘘纽约有多少英里的铁路。
00:36
how many miles of road they maintain.
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00:37
The MTA will boast how many miles
of subway track there are.
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多数的市政机关会给我们一些统计数据。
00:40
Most city agencies give us statistics.
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这是来自今年出租车与轿车
00:42
This is from a report this year
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委员会的一个报道,
00:43
from the Taxi and Limousine Commission,
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从中我们可以知道纽约一共有
13500辆出租车。
00:45
where we learn that there's about
13,500 taxis here in New York City.
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很有趣,对吧?
00:49
Pretty interesting, right?
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00:50
But did you ever think about
where these numbers came from?
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但是你们有没有想过这些数据从哪里来的?
因为这些数据的存在,市政机关的某个人
00:53
Because for these numbers to exist,
someone at the city agency
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00:56
had to stop and say, hmm, here's a number
that somebody might want want to know.
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可能会想:嗯,这个数据也许会有人想要知道。
00:59
Here's a number
that our citizens want to know.
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这个数据我们的市民想要了解。
于是他们找出原始数据
01:02
So they go back to their raw data,
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计数,做补充,再计算,
01:04
they count, they add, they calculate,
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01:05
and then they put out reports,
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并且将它们放在报告里。
于是这些报告就会包含这些数据。
01:07
and those reports
will have numbers like this.
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01:09
The problem is, how do they know
all of our questions?
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不过问题是,
他们要怎么知道我们所有感兴趣的问题?
01:11
We have lots of questions.
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我们有很多的疑问。
01:13
In fact, in some ways there's literally
an infinite number of questions
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事实上,关于我们的城市,
我们有无数的问题要问。
01:16
that we can ask about our city.
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政府部门当然没办法全部回答。
01:18
The agencies can never keep up.
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01:19
So the paradigm isn't exactly working,
and I think our policymakers realize that,
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所以现有模式不是十分有效,
并且我认为决策人也意识到了这个问题。
01:23
because in 2012, Mayor Bloomberg
signed into law what he called
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因为在2012年,彭博市长签署了一项法令,
他称之为
01:27
the most ambitious and comprehensive
open data legislation in the country.
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“全国最有雄心以及最综合性的
开放数据法案”。
01:31
In a lot of ways, he's right.
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在很多方面,他的决定是对的。
01:33
In the last two years,
the city has released 1,000 datasets
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在最近两年,
纽约已经在公开的数据门户上
01:35
on our open data portal,
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发布了1000组数据库,
01:37
and it's pretty awesome.
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非常了不起。
01:39
So you go and look at data like this,
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因此你们可以直接得到这些数据,
01:41
and instead of just counting
the number of cabs,
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除了能够计算出租车的数量,
01:43
we can start to ask different questions.
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我们不妨问一些不一样的问题。
01:45
So I had a question.
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我有一个问题。
01:46
When's rush hour in New York City?
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纽约的交通高峰期是哪个时间段?
01:48
It can be pretty bothersome.
When is rush hour exactly?
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这个问题可能令人厌烦。
交通高峰期具体指哪个时间段?
01:51
And I thought to myself,
these cabs aren't just numbers,
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我在想,
这些出租车不仅仅是一些数据,
01:53
these are GPS recorders
driving around in our city streets
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它们是行驶在城市街道的
GPS(全球定位系统)记录器,
记录下每一段它们行驶的路线。
01:56
recording each and every ride they take.
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01:58
There's data there,
and I looked at that data,
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这里有一些数据,我处理了一下,
02:00
and I made a plot of the average speed of
taxis in New York City throughout the day.
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将纽约出租车全天的
平均速度做了一个图表。
02:04
You can see that from about midnight
to around 5:18 in the morning,
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你会发现从午夜到凌晨5点18分,
02:07
speed increases, and at that point,
things turn around,
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速度在增加,到了这个点后,
接下来就不一样了,
02:11
and they get slower and slower and slower
until about 8:35 in the morning,
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速度越来越慢直到早上8点35分,
02:15
when they end up at around
11 and a half miles per hour.
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这时候出租车的时速
只有每小时11.5英里。
02:18
The average taxi is going 11 and a half
miles per hour on our city streets,
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我们城市街道上的出租车
平均时速是每小时11.5英里,
02:21
and it turns out it stays that way
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并且最终保持这个速度
02:23
for the entire day.
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一整天。
02:27
(Laughter)
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(笑)
02:28
So I said to myself, I guess
there's no rush hour in New York City.
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所以我心说,
纽约并没有什么交通高峰时间段。
02:31
There's just a rush day.
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只有“高峰日”。
02:33
Makes sense. And this is important
for a couple of reasons.
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这个结论是有意义的,
因为以下几个原因:
02:36
If you're a transportation planner,
this might be pretty interesting to know.
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如果你是交通运输系统的规划人,
你可能有兴趣知道这些。
02:39
But if you want to get somewhere quickly,
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如果你想要快速到达某个地方,
02:41
you now know to set your alarm for
4:45 in the morning and you're all set.
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你现在就知道只要将闹钟设在早上4点45分,
估计就没问题了。
在纽约嘛,这样做很合理是吧?
02:45
New York, right?
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02:46
But there's a story behind this data.
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但是在这些数据背后有一个故事,
02:47
This data wasn't
just available, it turns out.
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这些数据不是现成的。
它实际上来自一个叫
”信息自由法案申请“的东西,
02:50
It actually came from something called
a Freedom of Information Law Request,
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或者称为”FOIL 申请“。
02:53
or a FOIL Request.
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02:54
This is a form you can find on the
Taxi and Limousine Commission website.
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这个表格你可以在出租车
与轿车管理委员会的网站上找到。
要拿到这些数据,你必须拿到这个表格,
02:58
In order to access this data,
you need to go get this form,
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填写表格,然后他们会通知你,
03:01
fill it out, and they will notify you,
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03:02
and a guy named Chris Whong
did exactly that.
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有一个叫克里斯·王的人就是这样做的。
03:05
Chris went down, and they told him,
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克里斯去了那里,他们告诉他,
03:06
"Just bring a brand new hard drive
down to our office,
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“只要带一个新的硬盘到我们办公室,
03:09
leave it here for five hours,
we'll copy the data and you take it back."
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我们会将数据拷贝到里面,
过5个小时你就可以拿回去了。”
03:13
And that's where this data came from.
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这就是这些数据怎么得来的。
03:15
Now, Chris is the kind of guy
who wants to make the data public,
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现在,克里斯想将这些数据公开,
这些数据最终被上传到网络上供大家使用,
这就是这个图表背后的故事。
03:18
and so it ended up online for all to use,
and that's where this graph came from.
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03:22
And the fact that it exists is amazing.
These GPS recorders -- really cool.
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这一切真的很不可思议,
这些GPS记录器实在太酷了。
03:25
But the fact that we have citizens
walking around with hard drives
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但是实际上市民为了使数据公开,
03:28
picking up data from city agencies
to make it public --
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需要带着装有市政部门数据的
硬盘走来走去——
这已经是一种公开性质的,
你们都可以得到,
03:31
it was already kind of public,
you could get to it,
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不过它虽说是“公开”的,
但并不是真正意义上的“公开”。
03:33
but it was "public," it wasn't public.
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03:35
And we can do better than that as a city.
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我们作为一个城市可以做得更好。
我们不需要市民带着硬盘走来走去。
03:37
We don't need our citizens
walking around with hard drives.
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另外,不是每一组数据都需要
填写信息自由法案的申请。
03:40
Now, not every dataset
is behind a FOIL Request.
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03:42
Here is a map I made with the most
dangerous intersections in New York City
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这是一张我根据自行车事故数据绘制出的
纽约最危险十字路口的地图。
03:46
based on cyclist accidents.
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03:48
So the red areas are more dangerous.
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红色区域是最危险的。
03:50
And what it shows is first
the East side of Manhattan,
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首先显示的是曼哈顿的东区,
03:52
especially in the lower area of Manhattan,
has more cyclist accidents.
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特别曼哈顿的下城区,
发生过很多自行车车祸。
03:56
That might make sense
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这可能说得通,
03:57
because there are more cyclists
coming off the bridges there.
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因为很多自行车都是从桥上过来的。
04:00
But there's other hotspots worth studying.
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不过还有其他值得研究的热点区域。
这里是威廉斯堡。
这里是皇后区的罗福斯大道。
04:02
There's Williamsburg.
There's Roosevelt Avenue in Queens.
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04:04
And this is exactly the kind of data
we need for Vision Zero.
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这些正是Vision Zero
(跨国道路交通安全项目)所需要的数据。
04:07
This is exactly what we're looking for.
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这正是我们所要找的。
04:09
But there's a story
behind this data as well.
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在这些数据的背后也有一个故事。
04:11
This data didn't just appear.
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它们也不是现成的。
04:13
How many of you guys know this logo?
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有多少人知道这个标志?
04:16
Yeah, I see some shakes.
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我看到有些人点头。
04:17
Have you ever tried to copy
and paste data out of a PDF
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你们是否曾要复制和黏贴
PDF里的内容,
04:20
and make sense of it?
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并且搞清楚这些数据的意义?
04:21
I see more shakes.
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我看到更多的人在点头。
04:22
More of you tried copying and pasting
than knew the logo. I like that.
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比起知道这个标志,有更多的人
试过复制和黏贴。很不错。
所以你们刚才看到的
数据确实是来自一个PDF。
04:26
So what happened is, the data
that you just saw was actually on a PDF.
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04:29
In fact, hundreds and hundreds
and hundreds of pages of PDF
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事实上,有不计其数的PDF文档
04:32
put out by our very own NYPD,
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都是通过纽约警察局公布的,
04:34
and in order to access it,
you would either have to copy and paste
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为了得到这些数据,
你要么需要花几百个小时
复制和黏贴,
04:38
for hundreds and hundreds of hours,
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04:39
or you could be John Krauss.
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或者像约翰·克劳斯那样做。
04:41
John Krauss was like,
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他是这样做的:
04:42
I'm not going to copy and paste this data.
I'm going to write a program.
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我不想复制黏贴这些数据,
我要写一个程序。
这个程序被称为:”纽约警察局事故数据创可贴“
(NYPD Crash Data Band-Aid),
04:45
It's called the NYPD Crash Data Band-Aid,
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04:47
and it goes to the NYPD's website
and it would download PDFs.
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这个程序先进入纽约警察局的网站,
然后下载PDF文件。
04:50
Every day it would search;
if it found a PDF, it would download it
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每天进行搜索,如果发现PDF文件,
就会下载下来,
04:54
and then it would run
some PDF-scraping program,
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然后它会运行PDF解码程序,
04:56
and out would come the text,
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就可以将文本拷出来,
04:57
and it would go on the Internet,
and then people could make maps like that.
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然后上传到网络上,
大家就可以做出这样的地图了。
05:01
And the fact that the data's here,
the fact that we have access to it --
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只要数据在这里,
我们就可以使用这些数据——
05:04
Every accident, by the way,
is a row in this table.
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每个事故都是这个
表格里的一行数据。
05:07
You can imagine how many PDFs that is.
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你门可以想象得有多少个PDF文件。
05:08
The fact that we
have access to that is great,
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我们可以使用这些数据当然非常棒,
05:11
but let's not release it in PDF form,
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但是不要用PDF的格式公开这些数据,
05:13
because then we're having our citizens
write PDF scrapers.
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因为还需要我们的市民写PDF解码程序。
05:15
It's not the best use
of our citizens' time,
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这是在浪费市民的时间,
我们作为一个城市可以做得更好。
05:18
and we as a city can do better than that.
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05:20
Now, the good news is that
the de Blasio administration
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有一个好消息,
白思豪(纽约市长)的行政办公室
05:22
actually recently released this data
a few months ago,
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几个月前公开了这些数据。
05:25
and so now we can
actually have access to it,
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现在我们可以直接使用这些数据了,
05:27
but there's a lot of data
still entombed in PDF.
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但是依然有很多数据隐藏在PDF里。
05:29
For example, our crime data
is still only available in PDF.
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比如,与犯罪相关的数据
依然只能在PDF里才能看到。
05:33
And not just our crime data,
our own city budget.
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不仅仅是与犯罪相关的数据,
还有我们城市的预算。
05:36
Our city budget is only readable
right now in PDF form.
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我们城市的预算只能
在PDF格式的文件里才能看到。
05:40
And it's not just us
that can't analyze it --
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不仅仅是我们无法分析这些数据——
05:42
our own legislators
who vote for the budget
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我们为预算投票的立法者
05:45
also only get it in PDF.
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也只能通过PDF得到这些数据。
05:47
So our legislators cannot analyze
the budget that they are voting for.
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因此我们的立法者也无法
分析他们要投票的预算方案。
05:51
And I think as a city we can do
a little better than that as well.
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我认为我们作为一个
城市同样可以做得更好。
05:55
Now, there's a lot of data
that's not hidden in PDFs.
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有许多没有被隐藏在PDF文件里的数据。
05:57
This is an example of a map I made,
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我做的地图就是一个例子,
05:59
and this is the dirtiest waterways
in New York City.
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这是纽约最脏的水沟。
06:02
Now, how do I measure dirty?
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我怎么判断肮脏的程度呢?
06:03
Well, it's kind of a little weird,
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可能有点奇怪,
06:05
but I looked at the level
of fecal coliform,
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我是根据粪便菌群数的水平来判断的,
06:07
which is a measurement of fecal matter
in each of our waterways.
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就是测量每一个水沟粪便物的指标。
06:11
The larger the circle,
the dirtier the water,
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圆圈越大,表示水越脏。
06:14
so the large circles are dirty water,
the small circles are cleaner.
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所以大圆圈代表脏水,
小圆圈代表较干净的水。
06:17
What you see is inland waterways.
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你们看到的是内陆地区的水沟。
06:19
This is all data that was sampled
by the city over the last five years.
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这些是过去五年城市取样的所有数据。
06:22
And inland waterways are,
in general, dirtier.
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内陆地区的水沟普遍更脏。
06:25
That makes sense, right?
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有道理,是吧?
06:26
And the bigger circles are dirty.
And I learned a few things from this.
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圆圈越大表示越脏。
我从中了解到几件事。
第一:不要在任何名字末尾有
“小溪”、“运河”的地方游泳。
06:30
Number one: Never swim in anything
that ends in "creek" or "canal."
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06:33
But number two: I also found
the dirtiest waterway in New York City,
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第二:经过一次测量我就发现了
06:37
by this measure, one measure.
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纽约最脏的水沟。
06:39
In Coney Island Creek, which is not
the Coney Island you swim in, luckily.
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就是康尼岛小溪,
幸运的是这并不是你们去游泳的康尼岛,
是在岛的另一面。
06:43
It's on the other side.
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06:44
But Coney Island Creek, 94 percent
of samples taken over the last five years
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过去五年,康尼岛小溪94%的取样
06:48
have had fecal levels so high
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所含排泄物含量水平如此高,
06:50
that it would be against state law
to swim in the water.
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以至于州立法已经
禁止人们在此游泳。
06:53
And this is not the kind of fact
that you're going to see
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这不是你所看到的市政报告中
06:56
boasted in a city report, right?
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吹嘘的那一类数据,对吧?
06:57
It's not going to be
the front page on nyc.gov.
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也不会出现在纽约政府官网的首页上。
06:59
You're not going to see it there,
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你们不会在那里看到,
07:01
but the fact that we can get
to that data is awesome.
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但是我们能得到这些数据是非常棒的。
07:04
But once again, it wasn't super easy,
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但是再说一次,
这些数据并不是轻易得到的,
07:05
because this data was not
on the open data portal.
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因为这些数据并不是公开的数据库。
如果你们查看公开的数据,
07:08
If you were to go to the open data portal,
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只会看到其中的部分数据,
一年或几个月的数据。
07:10
you'd see just a snippet of it,
a year or a few months.
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环境保护部门网站上
提供的数据就是这样的。
07:12
It was actually on the Department
of Environmental Protection's website.
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每一个链接都是一个Excel表格,
每一个表格都是不一样的。
07:16
And each one of these links is an Excel
sheet, and each Excel sheet is different.
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标题也是不一样的:
你复制,黏贴,重新整理。
07:20
Every heading is different:
you copy, paste, reorganize.
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07:22
When you do you can make maps
and that's great, but once again,
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然后你就可以做一份地图,
那是很棒的,但是再说一次,
作为一个城市我们可以做得更好,
我们可以使数据标准化。
07:25
we can do better than that
as a city, we can normalize things.
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我们正在慢慢改进,
Socrata做了一个网站
07:28
And we're getting there, because
there's this website that Socrata makes
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叫做“纽约市公开数据门户网站”。
这里有1100组数据,
这些数据不会遭遇
07:32
called the Open Data Portal NYC.
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07:33
This is where 1,100 data sets
that don't suffer
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我刚才跟你们说的那种情况,
07:35
from the things I just told you live,
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并且数量还在增长,
这个网站真的很不错。
07:37
and that number is growing,
and that's great.
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你们可以下载任何格式的数据,
CSV或者PDF 或者Excel。
07:39
You can download data in any format,
be it CSV or PDF or Excel document.
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你想要什么格式,就以那种格式下载。
07:43
Whatever you want,
you can download the data that way.
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07:45
The problem is, once you do,
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问题是,一旦你开始下载数据,
07:47
you will find that each agency
codes their addresses differently.
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就会发现不同的部门会
用不同方式编码他们的地址。
07:50
So one is street name,
intersection street,
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有的用街道名,十字路口,
07:52
street, borough, address, building,
building address.
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街道,区,地址,大厦,大厦地址。
07:55
So once again, you're spending time,
even when we have this portal,
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所以你还是需要花时间,
即使我们有这个网站,
07:58
you're spending time
normalizing our address fields.
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你还是需要花时间使地址格式规范化。
08:01
And that's not the best use
of our citizens' time.
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这在浪费市民时间。
08:03
We can do better than that as a city.
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我们作为一个城市完全可以做得更好。
08:05
We can standardize our addresses,
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我们可以将我们的地址格式标准化,
08:07
and if we do,
we can get more maps like this.
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如果我们做到了,
就可以做更多类似这样的地图,
08:09
This is a map of fire hydrants
in New York City,
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这是纽约市防火栓的地图,
08:11
but not just any fire hydrants.
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但并不是全部的。
08:13
These are the top 250 grossing fire
hydrants in terms of parking tickets.
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这些是最容易被开罚单的前250个防火栓。
08:17
(Laughter)
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1986
(笑声)
08:19
So I learned a few things from this map,
and I really like this map.
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我从这张地图学到了一些东西,
我非常喜欢这张地图。
08:23
Number one, just don't park
on the Upper East Side.
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第一,不要在上东区停车。
08:25
Just don't. It doesn't matter where
you park, you will get a hydrant ticket.
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不论你停在哪里,
你都会收到一张罚单。
08:29
Number two, I found the two highest
grossing hydrants in all of New York City,
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第二,我发现全纽约市消防栓
最多的两个区域,
08:33
and they're on the Lower East Side,
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都在下东区,
08:35
and they were bringing in over
55,000 dollars a year in parking tickets.
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5098
并且一年可以带来
55000美元的罚单收入。
08:40
And that seemed a little strange
to me when I noticed it,
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我发现这点的时候,感觉有点奇怪,
08:42
so I did a little digging and it turns out
what you had is a hydrant
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我做了一些研究,比如有一个消防栓,
08:46
and then something called
a curb extension,
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旁边有横向拓宽的人行道,
08:48
which is like a seven-foot
space to walk on,
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2059
就像一个可以行走的七英尺的空间,
08:50
and then a parking spot.
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1156
然后旁边是停车位置。
08:51
And so these cars came along,
and the hydrant --
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司机将车开过来,心想
08:53
"It's all the way over there, I'm fine,"
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1911
“ 还离得挺远,没问题的,“
何况地上还有一个画得美美的停车位。
08:55
and there was actually a parking spot
painted there beautifully for them.
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于是他们将车停在这里,
但纽约警察局不允许这样,
08:59
They would park there, and the NYPD
disagreed with this designation
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然后他们就会被开罚单。
09:02
and would ticket them.
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不仅仅是我收到罚单。
09:03
And it wasn't just me
who found a parking ticket.
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谷歌街景车开过的时候
09:05
This is the Google
Street View car driving by
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也看到了同样的罚单。
09:07
finding the same parking ticket.
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09:09
So I wrote about this on my blog,
on I Quant NY, and the DOT responded,
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我将这件事情写在我的博客和
“I Quant NY ”上,交通部回复了我,
09:13
and they said,
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1020
他们说,
09:14
"While the DOT has not received
any complaints about this location,
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3410
”虽然交通部没有收到关于这个地点的投诉,
09:18
we will review the roadway markings
and make any appropriate alterations."
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4542
我们还是会评估道路标志,
做出合适的调整。
09:22
And I thought to myself,
typical government response,
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我认为这是典型的政府答复,
09:25
all right, moved on with my life.
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好吧,继续过我的日子。
09:27
But then, a few weeks later,
something incredible happened.
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3970
但是几个礼拜后,
难以置信的事情发生了。
09:31
They repainted the spot,
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2520
他们重新粉刷了停车位置,
09:34
and for a second I thought I saw
the future of open data,
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2690
这让我立刻看到了公开数据的未来,
09:36
because think about what happened here.
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2000
想想这里发生的事情吧。
09:38
For five years, this spot was being
ticketed, and it was confusing,
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5100
五年来,这个位置的车常被开罚单,
令人很困惑。
09:44
and then a citizen found something,
they told the city, and within a few weeks
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4306
然后有人发现了一些事情,
并且告诉了城市的管理者,在几周内
09:48
the problem was fixed.
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1294
这个问题就得到了解决。
09:49
It's amazing. And a lot of people
see open data as being a watchdog.
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这太不可思议了。
很多人把公开数据当做监督者。
09:52
It's not, it's about being a partner.
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不是的,它更像是一个合作伙伴。
09:54
We can empower our citizens
to be better partners for government,
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3138
我们可以赋予市民权利
成为政府的优秀合作伙伴,
09:57
and it's not that hard.
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1881
这不是很难。
09:59
All we need are a few changes.
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1459
只需要一些改变。
10:01
If you're FOILing data,
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1107
如果你正在申请FOIL数据,
10:02
if you're seeing your data
being FOILed over and over again,
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如果你看到你要的数据被反复的请求获得,
10:05
let's release it to the public, that's
a sign that it should be made public.
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3574
让我们直接将这些数据向大众公开吧,
这是一个数据需要公开的信号。
如果你是一个政府部门,
要公开一个PDF,
10:08
And if you're a government agency
releasing a PDF,
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2482
10:11
let's pass legislation that requires you
to post it with the underlying data,
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3649
让我们通过立法,发布被要求的源数据,
10:14
because that data
is coming from somewhere.
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2028
因为数据肯定来自某个地方。
10:16
I don't know where, but it's
coming from somewhere,
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2482
虽然我不知道是哪里,
但你们可用PDF的形式将这些数据公开。
10:19
and you can release it with the PDF.
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1725
让我们采用和共享公开数据的标准。
10:20
And let's adopt and share
some open data standards.
239
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2411
我们先从纽约的地址开始。
10:23
Let's start with our addresses
here in New York City.
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从规范地址格式开始。
10:25
Let's just start
normalizing our addresses.
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2074
纽约在公开数据上属于引领者。
10:27
Because New York is a leader in open data.
242
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2062
抛开这些问题,
我们在公开数据方面绝对是领先者,
10:30
Despite all this, we are absolutely
a leader in open data,
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如果我们开始规范化一些事情,
并且建立一个公开数据的标准,
10:32
and if we start normalizing things,
and set an open data standard,
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其他人会照着标准做,
纽约州也会照着做,甚至是联邦政府。
10:35
others will follow. The state will follow,
and maybe the federal government,
245
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3634
其他国家也可能参照这套标准,
不久的将来,我们可以编写一个程序,
10:39
Other countries could follow,
246
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1445
10:40
and we're not that far off from a time
where you could write one program
247
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3411
并整理出100个国家的数据信息。
10:44
and map information from 100 countries.
248
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1890
这不是科幻小说。
我们已经很接近这个目标了。
10:46
It's not science fiction.
We're actually quite close.
249
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2487
顺便说一下,我们的授权对象是谁?
10:48
And by the way, who are we
empowering with this?
250
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2240
不仅仅是约翰·克劳斯和克里斯·王。
10:51
Because it's not just John Krauss
and it's not just Chris Whong.
251
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3005
现在纽约有上百个聚会小组,
10:54
There are hundreds of meetups
going on in New York City right now,
252
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3095
活跃的聚会小组。
10:57
active meetups.
253
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1025
成千上万的人参加了这些小组。
10:58
There are thousands of people
attending these meetups.
254
658144
2572
11:00
These people are going after work
and on weekends,
255
660716
2368
人们在下班后或周末去参加这些活动,
在活动上,人们会处理这些公开数据,
11:03
and they're attending these meetups
to look at open data
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663084
2636
想办法让我们的城市越来越好。
11:05
and make our city a better place.
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1640
像BetaNYC这样的组织,
上周刚公开了一个叫citygram.nyc的网站,
11:07
Groups like BetaNYC, who just last week
released something called citygram.nyc
258
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4073
11:11
that allows you to subscribe
to 311 complaints
259
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2147
允许你订阅你家附近
11:13
around your own home,
or around your office.
260
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2068
或者你公司附近的311投诉。
11:15
You put in your address,
you get local complaints.
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2427
输入地址,你就能看到本地的投诉。
11:18
And it's not just the tech community
that are after these things.
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3374
这背后不仅仅有个技术团体,
还有许多城市规划者,
比如我在普瑞特艺术学院教过的学生。
11:21
It's urban planners like
the students I teach at Pratt.
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2622
不仅仅是政策的提倡者,是每一个人,
11:24
It's policy advocates, it's everyone,
264
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1919
11:25
it's citizens from a diverse
set of backgrounds.
265
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2563
是具有不同背景的城市市民。
11:28
And with some small, incremental changes,
266
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2786
通过一些微小但与日俱增的变化,
11:31
we can unlock the passion
and the ability of our citizens
267
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3225
我们就能释放市民的热情和能力,
11:34
to harness open data
and make our city even better,
268
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3156
去利用公开数据
使我们的城市变得更美好,
11:37
whether it's one dataset,
or one parking spot at a time.
269
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3626
无论是每次一组数据,
还是一个停车点。
11:41
Thank you.
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谢谢。
11:43
(Applause)
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3305
(掌声}
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