Ben Wellington: How we found the worst place to park in New York City — using big data

80,081 views ・ 2015-02-26

TED


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譯者: Karen SONG 審譯者: Muyun Zhou
00:12
Six thousand miles of road,
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六千英里公路,
00:15
600 miles of subway track,
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六百英里地鐵路線,
00:17
400 miles of bike lanes
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四百英里腳踏車專用道,
00:19
and a half a mile of tram track,
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半英里的有軌電車專用道
00:21
if you've ever been to Roosevelt Island.
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僅在羅斯福島。
00:23
These are the numbers that make up the infrastructure of New York City.
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這些數字構成了紐約市的基建。
00:26
These are the statistics of our infrastructure.
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這些基建的統計數字,
都可以在市政機關公佈的報告中找到。
00:29
They're the kind of numbers you can find released in reports by city agencies.
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譬如,交通部門可能會告訴你,
00:32
For example, the Department of Transportation will probably tell you
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他們維護這多少英里的道路。
MTA(紐約交通運輸管理局)會自誇 他們掌管著多少英里捷運。
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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多數的市政機關都在公佈統計數據。
00:40
Most city agencies give us statistics.
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這是今年計程車與轎車委員會發佈的報告,
00:42
This is from a report this year
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00:43
from the Taxi and Limousine Commission,
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我們從中知道紐約市運營著 大約一萬三千五百輛計程車。
00:45
where we learn that there's about 13,500 taxis here in New York City.
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很有趣,是嗎?
00:49
Pretty interesting, right?
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但你有否想過這些數據來自哪裡?
00:50
But did you ever think about where these numbers came from?
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既然有這些數字存在, 那肯定是因為在市政機關的某個人
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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想過:嗯......這個數字可能有人會想知道。
00:59
Here's a number that our citizens want to know.
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這個數字是市民們想知道的。
所以他們找回那些原始數據,
01:02
So they go back to their raw data,
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他們計數、相加、計算,
01:04
they count, they add, they calculate,
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01:05
and then they put out reports,
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然後把得出的結果寫進報告中,
所以那些報告中會有這樣的數字。
01:07
and those reports will have numbers like this.
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那麼問題來了:他們怎麼會知道 我們的問題都是什麼?
01:09
The problem is, how do they know all of our questions?
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01:11
We have lots of questions.
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我們有很多問題。
01:13
In fact, in some ways there's literally an infinite number of questions
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事實上,可以說我們有無窮無盡的問題
01:16
that we can ask about our city.
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有關我們這座城市。
市政機關可無法跟得上(我們的節奏)。
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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現有模式並不具有實效,我覺得 我們的政策制定者也知道這點,
01:23
because in 2012, Mayor Bloomberg signed into law what he called
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因為在2012年,彭博市長 簽署了一個法令,他稱之為
01:27
the most ambitious and comprehensive open data legislation in the country.
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全美最具雄心和綜合性的 開放數據立法。
01:31
In a lot of ways, he's right.
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從各種意義上來說,他是對的。
01:33
In the last two years, the city has released 1,000 datasets
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在過去兩年中,市政有1000個數據庫
01:35
on our open data portal,
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放在我們的開放數據門戶網站上,
01:37
and it's pretty awesome.
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還是蠻驚人的。
01:39
So you go and look at data like this,
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我們來檢視這些數據,
01:41
and instead of just counting the number of cabs,
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除了數數計程車的數量,
01:43
we can start to ask different questions.
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我們也能開始問不一樣的問題了。
01:45
So I had a question.
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我有一個問題:
01:46
When's rush hour in New York City?
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紐約市的交通高峰在什麼時候?
01:48
It can be pretty bothersome. When is rush hour exactly?
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這簡直煩人。高峰到底是什麼時候?
01:51
And I thought to myself, these cabs aren't just numbers,
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我想到,這些計程車可不僅僅是個數字,
01:53
these are GPS recorders driving around in our city streets
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它們可以是開遍全市道路的GPS記錄儀,
01:56
recording each and every ride they take.
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記錄著乘客的每一差車程。
01:58
There's data there, and I looked at that data,
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數據是現成的。我檢視它們,
02:00
and I made a plot of the average speed of taxis in New York City throughout the day.
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並制出一張圖表,標出 一天中紐約市計程車的平均時速。
02:04
You can see that from about midnight to around 5:18 in the morning,
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大家可以看到, 從半夜到凌晨五點十八分,
02:07
speed increases, and at that point, things turn around,
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時速一直在增加,然後到了拐點,
02:11
and they get slower and slower and slower until about 8:35 in the morning,
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時速逐漸下降,在早間的八點三十五分,
02:15
when they end up at around 11 and a half miles per hour.
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時速降到十一英里半。
02:18
The average taxi is going 11 and a half miles per hour on our city streets,
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運營中計程車的平均時速 保持在十一英里半,
02:21
and it turns out it stays that way
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結果沒有變化,
02:23
for the entire day.
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整天都是如此。
02:27
(Laughter)
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(笑聲)
02:28
So I said to myself, I guess there's no rush hour in New York City.
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我告訴自己,紐約市並不存在高峰時段,
02:31
There's just a rush day.
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而是全天都高峰。
02:33
Makes sense. And this is important for a couple of reasons.
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這是個有意義的結論,原因有幾點。
02:36
If you're a transportation planner, this might be pretty interesting to know.
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如果你是做交通規劃的, 知道這個結論會有意義。
02:39
But if you want to get somewhere quickly,
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如果你要快速到達某地,
02:41
you now know to set your alarm for 4:45 in the morning and you're all set.
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只要把鬧鐘定在凌晨四點四十五分就行了。
紐約嘛!
02:45
New York, right?
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02:46
But there's a story behind this data.
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但這個數據背後還有故事。
02:47
This data wasn't just available, it turns out.
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這個數據並不真的是現成的。
你需要做一個「信息自由法案申請」,
02:50
It actually came from something called a Freedom of Information Law Request,
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02:53
or a FOIL Request.
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也叫「FOIL申請」。
02:54
This is a form you can find on the Taxi and Limousine Commission website.
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你可以在計程車和轎車委員會的網站上 找到相關申請表。
如果要獲得這些數據, 你要弄到這張申請表,
02:58
In order to access this data, you need to go get this form,
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填好上交,受理人員屆時會通知你。
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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一個叫克里斯▪旺的人就這樣做了。
克里斯來到委員會,工作人員告訴他
03:05
Chris went down, and they told him,
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03:06
"Just bring a brand new hard drive down to our office,
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「帶個全新的硬盤來辦公室,
03:09
leave it here for five hours, we'll copy the data and you take it back."
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我們會把相關數據拷貝給你, 過五小時來拿。」
03:13
And that's where this data came from.
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這就是拿到數據的經過。
03:15
Now, Chris is the kind of guy who wants to make the data public,
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克里斯想公開這些數據,
於是放到網路上供所有人使用, 所以我才能做出這張圖。
03:18
and so it ended up online for all to use, and that's where this graph came from.
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這一切——這些GPS記錄儀真是酷。
03:22
And the fact that it exists is amazing. These GPS recorders -- really cool.
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03:25
But the fact that we have citizens walking around with hard drives
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但是,市民要攜帶自己的移動硬盤
03:28
picking up data from city agencies to make it public --
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踏遍市政機關, 然後通過自己的努力公開,這件事——
03:31
it was already kind of public, you could get to it,
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政府數據可以說是公開的, 普通市民能得到它,
03:33
but it was "public," it wasn't public.
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但這只是名義上的「公開」, 並不是真正的公開。
03:35
And we can do better than that as a city.
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我們的城市可以做得更好。
我們不需要費力帶著移動硬盤到處跑。
03:37
We don't need our citizens walking around with hard drives.
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並不是每一個數據庫都需要FOIL申請。
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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我做的這張地圖標出了紐約市最危險的路口,
03:46
based on cyclist accidents.
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來源是腳踏車騎行者的交通事故數據。
03:48
So the red areas are more dangerous.
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紅色區域更危險,
03:50
And what it shows is first the East side of Manhattan,
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圖上顯示,首先,曼哈頓的東側,
03:52
especially in the lower area of Manhattan, has more cyclist accidents.
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特別是曼哈頓的下城區域, 腳踏車事故更多。
03:56
That might make sense
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這可能是因為,
03:57
because there are more cyclists coming off the bridges there.
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在這裡有更多的騎行者從大橋下來。
04:00
But there's other hotspots worth studying.
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圖上還有其他的熱點區域值得研究。
04:02
There's Williamsburg. There's Roosevelt Avenue in Queens.
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威廉姆斯堡、皇后區的羅斯福大道,
04:04
And this is exactly the kind of data we need for Vision Zero.
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這些咨詢才是Vision Zero項目所需要的。
04:07
This is exactly what we're looking for.
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這正是我們要找的東西。
04:09
But there's a story behind this data as well.
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這個數據背後也有個故事。
04:11
This data didn't just appear.
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這個數據並不是現成的。
04:13
How many of you guys know this logo?
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有多少人知道這個符號?
04:16
Yeah, I see some shakes.
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我看到有人點頭了。
04:17
Have you ever tried to copy and paste data out of a PDF
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你們有沒有試過從PDF文檔中 拷貝和黏貼數據,
04:20
and make sense of it?
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並據此作出結論呢?
04:21
I see more shakes.
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我看到更多人點頭了。
04:22
More of you tried copying and pasting than knew the logo. I like that.
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試圖拷貝粘貼的人 比認識這個標誌的人更多,真有趣。
04:26
So what happened is, the data that you just saw was actually on a PDF.
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你們剛剛看到的數據是做在PDF裡的。
04:29
In fact, hundreds and hundreds and hundreds of pages of PDF
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事實上,是成千上萬頁的PDF文檔,
04:32
put out by our very own NYPD,
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由我們的紐約警署發佈。
04:34
and in order to access it, you would either have to copy and paste
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如果你想享用這些數據, 你要不就持續
做複製黏貼的動作,花掉成千上萬小時,
04:38
for hundreds and hundreds of hours,
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04:39
or you could be John Krauss.
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要不就像約翰▪克勞斯一樣。
04:41
John Krauss was like,
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約翰▪克勞斯
04:42
I'm not going to copy and paste this data. I'm going to write a program.
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可不想重複地去複製黏貼, 他寫了一個程式。
04:45
It's called the NYPD Crash Data Band-Aid,
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這個程序叫做 「紐約警署交通事故數據OK蹦」,
04:47
and it goes to the NYPD's website and it would download PDFs.
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它能到紐約警署的網站下載PDF文檔,
04:50
Every day it would search; if it found a PDF, it would download it
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每天它都去搜索; 如果找到一個PDF文檔,就下載下來,
04:54
and then it would run some PDF-scraping program,
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然後運行某個PDF解碼的程式,
04:56
and out would come the text,
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把其中的文字信息提取出來,
04:57
and it would go on the Internet, and then people could make maps like that.
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其中的訊息會發佈在網路上, 人們就可以製作這些地圖。
05:01
And the fact that the data's here, the fact that we have access to it --
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這些數據就在那兒,我們都能得到——
05:04
Every accident, by the way, is a row in this table.
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每一個交通事故就是一行數據。
05:07
You can imagine how many PDFs that is.
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你們可以想像有多少PDF需要轉碼。
05:08
The fact that we have access to that is great,
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——我們能看到這些數據固然好,
05:11
but let's not release it in PDF form,
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但能不能不要弄成PDF格式的,
05:13
because then we're having our citizens write PDF scrapers.
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不然市民們就得去寫PDF解碼的程式,
05:15
It's not the best use of our citizens' time,
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這對市民的時間來說是一種浪費,
而我們的城市能做的更好。
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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有個好消息,白思豪市長的班底
05:22
actually recently released this data a few months ago,
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在幾個月前公開了這份數據,
05:25
and so now we can actually have access to it,
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所以我們能直接享用這些數據,
05:27
but there's a lot of data still entombed in PDF.
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然而還有很多數據是PDF格式的。
05:29
For example, our crime data is still only available in PDF.
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譬如,我們的罪案數據目前只有PDF格式的。
05:33
And not just our crime data, our own city budget.
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除了罪案數據,市政預算也是如此。
05:36
Our city budget is only readable right now in PDF form.
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目前我們的市政預算只有PDF格式的。
05:40
And it's not just us that can't analyze it --
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不僅是我們無法分析這些數字,
05:42
our own legislators who vote for the budget
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那些為市政預算投票的立法委員們
05:45
also only get it in PDF.
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也只能拿到PDF版本的數字。
05:47
So our legislators cannot analyze the budget that they are voting for.
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所以我們的立法委員是無法分析 他們要為之投票的市政預算的。
05:51
And I think as a city we can do a little better than that as well.
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我認為我們的城市還能做得更好。
05:55
Now, there's a lot of data that's not hidden in PDFs.
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很多數據已經不躲在PDF中了。
05:57
This is an example of a map I made,
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這裡有一幅地圖可以作為例證,
05:59
and this is the dirtiest waterways in New York City.
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標示了紐約市最骯髒的水路。
06:02
Now, how do I measure dirty?
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我是如何衡量「骯髒」的呢?
06:03
Well, it's kind of a little weird,
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這裡有些奇怪,
06:05
but I looked at the level of fecal coliform,
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我衡量的是糞便大腸菌群的水平,
06:07
which is a measurement of fecal matter in each of our waterways.
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這是水路中糞便物質的一種衡量指標。
06:11
The larger the circle, the dirtier the water,
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圓圈越大,水就越髒,
06:14
so the large circles are dirty water, the small circles are cleaner.
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所以圖上的大圓圈代表髒水, 小圓圈代表乾淨的水。
06:17
What you see is inland waterways.
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大家看到的是內河水道。
06:19
This is all data that was sampled by the city over the last five years.
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這裡有紐約市過去五年採樣的所有數據。
06:22
And inland waterways are, in general, dirtier.
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內河水道總的來說變髒了。
06:25
That makes sense, right?
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這個結論挺合理的,對嗎?
06:26
And the bigger circles are dirty. And I learned a few things from this.
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大圓圈代表髒水。 我從中學到了幾件事情。
06:30
Number one: Never swim in anything that ends in "creek" or "canal."
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第一:千萬別在任何叫做「xx溪」 或「xx運河」的地方游泳。
06:33
But number two: I also found the dirtiest waterway in New York City,
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但是第二:紐約市最髒的水路,
06:37
by this measure, one measure.
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只看(糞便大腸菌群)這個唯一的指標,
06:39
In Coney Island Creek, which is not the Coney Island you swim in, luckily.
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在康尼島溪,幸好不是你們游泳的康尼島。
06:43
It's on the other side.
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那在島的另一面。
06:44
But Coney Island Creek, 94 percent of samples taken over the last five years
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但在康尼島溪中, 過去五年的採樣中有94%
06:48
have had fecal levels so high
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含有超標的糞便含量,
06:50
that it would be against state law to swim in the water.
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以至於達到州法律禁止游泳的水平。
06:53
And this is not the kind of fact that you're going to see
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這種類型的事實
06:56
boasted in a city report, right?
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你可不會在市政報告中看到,不是嗎?
06:57
It's not going to be the front page on nyc.gov.
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這也不會登上紐約市政府網站的頭條。
06:59
You're not going to see it there,
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我們肯定不會看到的,
07:01
but the fact that we can get to that data is awesome.
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但能看到這些數據真實不錯。
07:04
But once again, it wasn't super easy,
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同樣,拿到這些數據並不容易,
07:05
because this data was not on the open data portal.
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因為它們並不在公開數據門戶網站上。
07:08
If you were to go to the open data portal,
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如果你看公開數據的門戶網站,
07:10
you'd see just a snippet of it, a year or a few months.
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你只能看到其中一些片段, 只有一年內或幾個月的數據。
07:12
It was actually on the Department of Environmental Protection's website.
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這些數據其實是在環境保護部門的網站上。
07:16
And each one of these links is an Excel sheet, and each Excel sheet is different.
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每一個鏈接都是一個Excel文件, 而每個Excel文件都是不一樣的。
07:20
Every heading is different: you copy, paste, reorganize.
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每一個表頭都不同: 需要複製、黏貼、還有重新整理。
07:22
When you do you can make maps and that's great, but once again,
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一旦完成你就能做出這些地圖, 但我要再次重申,
07:25
we can do better than that as a city, we can normalize things.
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我們的城市能做的更好, 我們可以標準化。
我們正在改善這裡有個 索克拉塔公司建立的網站
07:28
And we're getting there, because there's this website that Socrata makes
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叫做「紐約市公開數據門戶」。
07:32
called the Open Data Portal NYC.
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這裡,1100個數據庫
07:33
This is where 1,100 data sets that don't suffer
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都不存在標準化的問題,
07:35
from the things I just told you live,
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而且(這些無縫連接的數據庫)數字還在增加。
07:37
and that number is growing, and that's great.
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你可以下載任一格式的數據: CSV、PDF或Excel文件都可以。
07:39
You can download data in any format, be it CSV or PDF or Excel document.
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按你自己的需求來下載。
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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但問題又來了,
你會發現不同的機構 用不同的代碼來表示地址。
07:47
you will find that each agency codes their addresses differently.
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07:50
So one is street name, intersection street,
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有街道名、有路口名、
07:52
street, borough, address, building, building address.
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行政區、地址、建築物、建築物地址等等。
07:55
So once again, you're spending time, even when we have this portal,
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所以,即使有這個門戶網站的幫助,
07:58
you're spending time normalizing our address fields.
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你還得花時間來標準化地址這塊的數據。
08:01
And that's not the best use of our citizens' time.
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這也不是有效利用市民時間的方法。
08:03
We can do better than that as a city.
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我們的城市能做得更好。
08:05
We can standardize our addresses,
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我們可以對地址進行標準化,
08:07
and if we do, we can get more maps like this.
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如果做到了, 我們就能做出更多這樣的地圖。
08:09
This is a map of fire hydrants in New York City,
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這是紐約市消防龍頭的地圖,
08:11
but not just any fire hydrants.
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但不僅於此。
08:13
These are the top 250 grossing fire hydrants in terms of parking tickets.
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這些是前250個吃到最多違章停車罰單的 消防栓位置圖。
08:17
(Laughter)
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(笑聲)
08:19
So I learned a few things from this map, and I really like this map.
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我從圖中學到了幾件事, 我也真的喜歡這張圖。
08:23
Number one, just don't park on the Upper East Side.
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第一:別在上東區停車。
08:25
Just don't. It doesn't matter where you park, you will get a hydrant ticket.
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千萬別停。因為不管停哪裡都會吃罰單。
08:29
Number two, I found the two highest grossing hydrants in all of New York City,
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第二:我找出了全紐約市最最容易 吃到違章停車罰單的兩個消防栓的位置,
08:33
and they're on the Lower East Side,
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兩個都在下東區,
08:35
and they were bringing in over 55,000 dollars a year in parking tickets.
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每年能在罰單上創收五萬五千多美金。
08:40
And that seemed a little strange to me when I noticed it,
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我注意到這點,覺得有些奇怪,
08:42
so I did a little digging and it turns out what you had is a hydrant
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於是深入挖掘了一下原因, 結果發現消防栓
08:46
and then something called a curb extension,
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都有一個叫做控制擴展的區域,
08:48
which is like a seven-foot space to walk on,
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是約有七英呎的一塊地方,可以走路,
08:50
and then a parking spot.
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然後是一個停車位。
08:51
And so these cars came along, and the hydrant --
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所以車開過來,司機發現消防栓,
08:53
"It's all the way over there, I'm fine,"
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想“還有一段距離,這裡沒問題的”,
08:55
and there was actually a parking spot painted there beautifully for them.
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何況地上還有一個畫得美美的停車位,
司機停好車,但紐約警署不同意這種配置,
08:59
They would park there, and the NYPD disagreed with this designation
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開出了罰單。
09:02
and would ticket them.
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可不只是我本人吃了罰單,
09:03
And it wasn't just me who found a parking ticket.
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這是谷歌街景拍到的一輛過路車,
09:05
This is the Google Street View car driving by
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09:07
finding the same parking ticket.
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也吃了同樣的一張罰單。
09:09
So I wrote about this on my blog, on I Quant NY, and the DOT responded,
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於是我把這件事發到自己的部落格上 以及“I Quant NY”上,
09:13
and they said,
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結果交通部門回復如下:
09:14
"While the DOT has not received any complaints about this location,
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“交通部並未就此地點收到相關投訴,
09:18
we will review the roadway markings and make any appropriate alterations."
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我們會重新檢視道路標誌, 並做出適當的改善措施。”
09:22
And I thought to myself, typical government response,
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我暗自想:多麼官腔!
09:25
all right, moved on with my life.
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好吧,我該幹嘛幹嘛去了。
09:27
But then, a few weeks later, something incredible happened.
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然而,幾週時間過去, 發生了意料之外的事情。
09:31
They repainted the spot,
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停車位重新畫了,
09:34
and for a second I thought I saw the future of open data,
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那一瞬間我覺得能看到公開數據的未來。
09:36
because think about what happened here.
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大家想想這件事,
09:38
For five years, this spot was being ticketed, and it was confusing,
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過去五年,這個讓人困惑的停車位 一直讓人吃罰單,
09:44
and then a citizen found something, they told the city, and within a few weeks
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但某一天,一位市民發現了問題 報告市政機關,又過了幾週時間,
09:48
the problem was fixed.
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問題車位被修正了。
09:49
It's amazing. And a lot of people see open data as being a watchdog.
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太不可思議了。很多人認為 公開數據讓市民變成政府的監視者,
09:52
It's not, it's about being a partner.
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並非如此,它實則讓人們成為了合作夥伴。
09:54
We can empower our citizens to be better partners for government,
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市民能夠有底氣成為政府更好的合作夥伴,
09:57
and it's not that hard.
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這並不難。
09:59
All we need are a few changes.
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我們只需要作出一些改變。
10:01
If you're FOILing data,
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如果我們在申請FOIL信息自由法案數據,
10:02
if you're seeing your data being FOILed over and over again,
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如果你看到自己申請的數據已經被反覆申請,
10:05
let's release it to the public, that's a sign that it should be made public.
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讓我們直接向公眾公開, 因為反覆申請就是需要公開的一种信號。
10:08
And if you're a government agency releasing a PDF,
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如果某個政府機關正在發佈PDF數據,
10:11
let's pass legislation that requires you to post it with the underlying data,
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讓我們通過法案 要求他們發佈隱藏的數據,
10:14
because that data is coming from somewhere.
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因為這些數據必定有來源。
10:16
I don't know where, but it's coming from somewhere,
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我不知道從哪兒,但肯定有來源,
10:19
and you can release it with the PDF.
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可以發佈PDF之外的信息。
10:20
And let's adopt and share some open data standards.
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讓我們運用并分享一些公開數據的標準。
10:23
Let's start with our addresses here in New York City.
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讓我們從紐約本市的地址開始,
10:25
Let's just start normalizing our addresses.
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把地址標準化。
10:27
Because New York is a leader in open data.
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因為紐約是公開數據的領導者。
10:30
Despite all this, we are absolutely a leader in open data,
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儘管如此,我們絕對是公開數據的領導者,
10:32
and if we start normalizing things, and set an open data standard,
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如果我們開始做標準化的工作, 建立公開數據的標準,
其他人都會追隨的。州里會、聯邦政府也可能,
10:35
others will follow. The state will follow, and maybe the federal government,
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我知道這或許聽上去有些瘋狂, 但別的國家也未嘗不會追隨。
10:39
Other countries could follow,
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10:40
and we're not that far off from a time where you could write one program
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我們不久後也許能開發出
可以涵蓋100個國家地圖信息的程式。
10:44
and map information from 100 countries.
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這可不是科幻小說, 而是指日可待的事實。
10:46
It's not science fiction. We're actually quite close.
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10:48
And by the way, who are we empowering with this?
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這能幫助誰?
可不單單是約翰▪克勞斯和克里斯▪旺。
10:51
Because it's not just John Krauss and it's not just Chris Whong.
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紐約城現在正有幾百個聚會在進行,
10:54
There are hundreds of meetups going on in New York City right now,
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10:57
active meetups.
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都是活躍的聚會。
這些聚會讓幾千人參與其中。
10:58
There are thousands of people attending these meetups.
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11:00
These people are going after work and on weekends,
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他們下班後或在週末會面,
共同研究空開數據,
11:03
and they're attending these meetups to look at open data
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11:05
and make our city a better place.
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幫助我們的城市變得更好,
11:07
Groups like BetaNYC, who just last week released something called citygram.nyc
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BetaNYC這樣的團體,上週剛剛發佈了 citygram.nyc
11:11
that allows you to subscribe to 311 complaints
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讓你能夠訂閱311個
11:13
around your own home, or around your office.
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自己住家或辦公地周圍的投訴。
11:15
You put in your address, you get local complaints.
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你輸入地址,就能看到附近的投訴。
11:18
And it's not just the tech community that are after these things.
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而且,做這些事情的並不限於技術社團。
11:21
It's urban planners like the students I teach at Pratt.
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我在Pratt學院教的城市規劃學生 也在做同樣的事。
11:24
It's policy advocates, it's everyone,
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還有政策提倡者、以至每個人,
11:25
it's citizens from a diverse set of backgrounds.
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是擁有不同領域背景的市民們。
11:28
And with some small, incremental changes,
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隨著一個個小的改變,
11:31
we can unlock the passion and the ability of our citizens
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我們能解開市民們激情和能力的封印,
11:34
to harness open data and make our city even better,
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好好利用空開數據,建設更好的城市,
11:37
whether it's one dataset, or one parking spot at a time.
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就算每次只有一個數據庫,或只是一個停車位。
11:41
Thank you.
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謝謝。
11:43
(Applause)
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(掌聲)
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