I'm going to actually start while they try to set this up, tell you a little bit about
what I'm going to talk about. Open data, of course, is a movement, and it has to do a lot
with the idea that the government has information on you. Now, we all know a lot about that, but
legitimately, they collect all kinds of stuff. They collect bus schedules, they collect voting
records, and things like that. So the reason there's an open data movement is because, in fact,
there's a need for it, right? We want to know the bus time. And let's face it, governments are
not always the best writers of software. I'm a professor. I spent a frantic two hours yesterday
trying to deal with a government grant software in Canada because it was designed by civil
servants. So often it's best to actually say, let the community go out and design it. In New York
City, for example, all the subways have a sign up, our transit apps are WISKID certified. And
what that means is that we're not going to have to go out and design it. We're going to have to
do it. And what that means is the MTA didn't do them. They actually let other companies create
applications to use their data, which they make available openly. So one reason, of course, why
governments open up their data is in the interest of giving better service to customers.
Another one, of course, relates to the fact that if they have the data, they figure sooner or later
somebody's going to put it out on WikiLeaks anyway, so they might as well release what they have. So
the ability to actually go out there and see all the government data seems to be a natural thing.
It resonates.
It resonates with the whole spirit of DEF CON, which is data wants to be free. Data wants to be
open. And as a result, governments are opening up more and more of their data. The other thing, of
course, is they're cheap. They don't want to go out there and spend money on building applications
if other people will do it for free. So the reality is we have a lot of good reasons, and I am
not, this is kind of the big preamble, I am not against open data. I think open data is great.
There are open data hackathons that are held all over the world, and they basically,
have the advantage of getting the best minds to take the government's data and think of creative
uses. So if you have four kids and you need to take one to the soccer field and one to the baseball
diamond, and you want to somehow optimize that, that's really good. The problem, of course, is
that a lot of the data that the government collects is related to people. So I'm still hoping
that we're going to see images, because I do have images to share with you. But I'll tell you that
there are a lot of people in the democracy that we want to know what the voting results were. So
just as, and this is an example that I cooked up to illustrate one of the problems with open data. We
have a city in Alberta called Edmonton. It has a wildly popular mayor named Steven Mandel. He got,
you know, over half, well over half the votes in every ward. But when they published the results,
there were some minority candidates, people who only got a few votes, who got zero votes, in fact,
in some areas. So let's say, for example, if you're a Republican, you're going to get a vote in the
city. So let's say, for example, Mr. Dowdell, who was one of the other candidates, his wife was in
the hospital. And he goes and, you know, she says, yes, dear, I voted, and I voted for you. And he
goes and pulls down the online data, and guess what? He got zero votes in the citywide hospital
poll. Well, that's a type of torturing of data that the government never anticipated. They never
anticipated that we would ask questions like that of the data. So, you know, the term torturing data
in my title really relates to two things. First, you know, we have a lot of people who are
doing exactly what most people in this room love to do, which is to go out there and find things
that you're not supposed to be able to find. So when people ask, you know, what is DEF CON, I say
it's basically not people who are doing things that they shouldn't do. It's people doing things
that they shouldn't be able to do. And you can do that with data quite effectively. So, again,
while we're praying to the AV gods there, I'm going to start telling you about an example,
and we'll go through it quickly when the video comes up. There actually was a challenge,
the open data challenge held in Europe, and they got entries from most of the EU countries.
And the one that won was actually from Slovenia. I don't speak Slovenian, so I can't really say the
name, but it translates as from our taxes. And what they did was they actually took all the
government contracts that were registered online, and they started going out there and putting them
together and finding out what names were in common, which people were the directors of
different companies, which people were the lawyers who represented the deals and so on. And an
interesting thing happened. A woman named Ludmilla decided that this was invading her privacy. And
she actually convinced a judge in Slovenia to go out there and to order the NGO that created this
award-winning application to take down the data. Now, somebody asked me before the talk how
technical this is going to be. This is about as technical as it gets. They didn't have that.
That data was scraped off government databases that were maintained by the government. So here
we have a judge, and it proves the old saying that judges are about 10 years behind the average
member of society in understanding of technology. Yes, that's right. Yes, thank you. And so the
judge is ordering them to take down this information. And they can't take it down because
they don't really have it. I mean, what I suppose they could do is put filters into their program
that somehow allow them to take down this information. And they can't take it down because
they don't really allow them to go out there and to get that information trapped so that it
couldn't be revealed. But it just kind of shows a misunderstanding, a fundamental misunderstanding.
Do we have any hopes back there, guys? Hope springs eternal, okay. Well, I could just hold
the screen up and give everybody a telescope or something like that, right? So let's talk about
some other kinds of open data. We have a member of the legislative assembly of Alberta who had
the misfortune to do two things. First of all, we have a member of the legislative assembly of
Uganda called Mike Allen. I mean, he saw these things wrong. On a government trip, he solicited a
prostitute and he got caught. Okay, so about three weeks ago, and his name was Mike Allen. And it was
all over the news. So I said, okay, what else can I find out about Mike Allen? So I went to a
database. I went to the Ramsey county, Minnesota, sheriff's office database. And sure enough,
there is poor Mike's information on what he was doing, the fact that it was gross. They used the word gross misconduct. His home
line was build up with a very good law firm. And I said, well, look, I have a little bit of experience. The prove it was a crime. It has a lot of value.
address. And that's where things get pretty interesting. Because if you think about it,
having his home address up there, it's private information in a sense. But hey, he was arrested.
Some sheriff in Minneapolis took that and posted it. Now we have a, you know, different countries
have different regard for privacy. Is there anybody from Germany here? Okay. All right. So
if you're from Germany, you're the best, right? You have like the people from Facebook say they
can't even operate in Germany, right? It's like, you know, everything's against the law there.
And then you have other countries. Now Canada, I would say, is between Germany and the U.S.
So a lot of things that you can get away with in the U.S. in terms of posting information on people
would not fly in Canada. To take that specific example, I'm sure that if this guy was arrested,
they wouldn't just willy-nilly put up the information about where he lives. Because
what's the need for that? But in the United States, there's certainly a tendency to do more
and more of that. And one of the photos, if we ever do get to it, I'll be able to show you,
is from Henderson,
Florida. Now Henderson County is a place you never want to get arrested. Because sheriffs in
the U.S., for those from Germany who don't know, are elected officials. So sheriffs, dog catchers,
people like that, they all get to be what they are by having people vote for them. So the reality
is they go out there, they want to show that they're doing their job. They're actually a good
sheriff. What better way to show that you're a good sheriff than to actually arrest people?
And sure enough, in Henderson County,
there's a lot of people who have been arrested. So if you're, you know, done for speeding or
whatever down there, and there's a really seedy, and again, we may have the slide one of these
days, when we do, you'll see some really seedy looking characters, people you would probably
cross the street to avoid who have been arrested. But you'll also see a photo of a 12-year-old boy.
And I captured that information off the government database and use it in my presentation. Now I
obscured his name. His first name is Bobby. I obscured his surname.
I put one of those black bars across his eyes, so you can't actually see what Bobby did,
or, you know, his personal identity. But the sheriff didn't do that. So the first thing to
realize is that he's up there, a minor child, 12 years old, and he's being sort of permanently
tarred in some ways. They say, well, not really permanently, because after all, it's only up there
for 30 days. And the answer is, yeah, but it's been in my presentation for over a year now.
When data is out there,
there's no way to really call it back. There's no way to bring data back into the fold if you've
let it loose. And this brings a lot of vulnerabilities. The reality is that quite a bit of
data is being put out there, captured by people. They say that if you put a photo up on Facebook
or something like that, I mean, at the very least, it's been copied by the NSA, but it's
probably been copied by a lot of other people as well. So there's no way to actually call back
data from being posted somewhere.
One aspect, again, I'm just randomly remembering my presentation. I usually print out a little
cheat sheet, but I trusted the tech here. Yeah. So anyway, another aspect of this relates
to DNA information. How many of you know Ancestry.com or Ancestry.co or whatever? Yeah. All the
different national versions. I won't ask because, you know, it's embarrassing to put your hand up.
Who has profiles on that?
Ancestry, of course, is they allow you to sign up for 14 days for free and do all kinds of
exploring with their data. So they are using public information, census data. They're using
military records, prison records, all kinds of things. Those are particularly useful for
Australia. Lots of prison records down there. And so they take all this data and they make it
freely available to you for 14 days. And on the 15th day, they charge you like $299 if you don't
cancel your membership. Now, it's an interesting
model because they're taking public data and eventually making money from it. But, you know,
we assume that that's probably okay. Second thing, though, of course, is that they, after you leave,
after you tell them, hey, I don't want to sign up for the $299, they go out there and they keep
your data. So they know your family tree. So you have enriched their database. And guess what? You
can never, you can cancel your account. You can, you know, check into the Hotel of California. You
can never check out your data. It is permanently
part of their database. So a few years ago, they got a brain wave. They said, you know what would
make this a lot better? Send us your DNA. And then we'll tell you, you know, if you're descended
from, you know, Adam or Noah or, you know, whoever. Whoever is way, way back in your family
tree. And some people, I think, were actually dumb enough to send their DNA. And doing that,
of course, provides a tremendous amount of information. And if you think about it with
DNA information, it's not just about you. It's about your siblings, your family,
all kinds of people who didn't give any consent for you to give that information. So the reality
is putting DNA information out there is risky. Giving it up voluntarily is dumb. And Privacy
International, the NGO in the U.K., actually launched a lawsuit against Ancestry.com.
Now, I was down in Utah, and I thought I'd visit Ancestry.com, and I'd try to find out all about
this. And they said, oh, well, we just keep the database here. That's the genetic genealogy
project, and it's with the real smart people down in California. So the genetic genealogy
project is something to really worry about, okay? The possibility is out there for somebody
to get tremendous amounts of information on you. Do we have any hope back there? Hope
springs eternal? You're getting closer. So everyone, leave your laptop at the door.
Right? So a couple of principles on dealing with this data. Okay. The New York City released
with great fanfare in 2009, New York City data mine, and they had 110 databases there. And they
said, you know, these are all interesting things, like all the women's organizations in New York
City are now in this database. Well, they realized a day later that they had forgotten to take out
the private e-mail addresses and the secret questions. So what was your first
pet is the most common secret question, and fluffy is the most common answer. So that
information was disclosed out there, and, you know, the next day there were only 109 public
databases from New York City because they had to go in there and they had to take back some of
that information. I want to explain an experiment to you that I did with what's called
openphilly.com. So Philadelphia is one of the leading cities in making their data open, and they
went out there and they actually put online contributions to the data that they were
taking. They took contributions to the data that they had in the database. They went out there
records. Now, again, because it's an international audience, it varies a lot from country to
country. But in the United States, there's laws about campaign contributions, particularly
those over $200 that say that if you make a contribution, you have to go out there and you
have to give your name, your address and your occupation. And those things are publicly
available information. But what Philadelphia did is they took all the contributions, even the ones
of $1.49, for the last seven years retroactively and they put them up in this wonderful database.
Now we're going to get technical one more time. It was put up there with a front end that said
you can query this database, but hey, you better not go out there and actually download it. Like
it's not for downloading. Okay, so here's how you download it. And any of my computer science
students who didn't get this would get an F. First you say, tell me all the people, download
all the people whose first name begins with A. Then you do all the people whose last name begins
with A. Then you do the last names beginning with B and C and D. See the pattern? So within about
eight minutes I had a comma separated file of all of these contributions. And then I started to
torture the data and have a little bit of fun with it. So I said, well, what can I find out?
Who in this room knows who Ronald Rivest is?
Okay, who's heard of RSA, Rivest Shamir Edelman? Okay, there is a candidate, her name is Shelly
something or other, in Philadelphia and all of her contributions seem to be local except one came
from Massachusetts. Well, who was it? It was Ron Rivest. And he obviously endorsed this candidate
enough that he sent money to her. So, you know, by plotting the data on a bit of a graph, I was
actually able to find some interesting things. The most interesting thing I found was that an
awful lot of people in Philadelphia were not interested in the data. So I said, well, who's
in Philadelphia live in the same place? 1719 Spring Street. I mean, thousands of people live
there. And I went, what the heck is this? So I went over to Google Maps and I bring it up and it is
the office of the International Brotherhood of Electrical Workers. So I think you can see the
scene. Guido comes in, he's going to get his job as an electrical worker and they say, wait a
minute, you got to come over here, you know, you got to make this contribution. And he says, oh,
yeah, I got to do that. And he filled out the form. And, you know, when people do,
you know, campaign contributions, they're very scrupulous about putting some address down
because they want to get the tax receipt. But maybe he doesn't want to give his own address.
Maybe he's in the witness protection program or something. So they go up. We'll use the address
of the union. So a significant number of the contributions to certain candidates map back to
that one building, which is the headquarters of the union. Now, then I thought I'd be a real sort
of objective computer scientist and run a statistical study. So I found out the most common
names in the United States, names like Jones and Smith. And I did an analysis. The only reason
really to publish the name and address of political contributors that I could see is if there's two
John Smiths and you want to know which one it is. So I actually did a statistical test and I
found there were 385 Jay Smiths and the actual power or the need to actually resolve duplicates
came down to only about three or four.
There was almost no information added by having this, but there was a significant privacy risk.
So what I'm suggesting to governments is that they need to go out there and think long and hard
about how they put out the data, why they put out the data. Now, again, I don't know if we ever
get the images and we're going to have like a flash dance of the images if we do get them up
here. But I have a complete stalking exercise I did on a notable Albertan. He actually was the
president of an airline. And I said, to tell you the truth, I started with the premier of the
president. And I said, I'm going to do this. I'm going to do this. And I said, I'm going to do this.
And I said, how well does he protect his privacy? And my first test was, is his phone number unlisted?
And it was. So then I worked down to other people. And finally I found the president of a pretty big
airline whose home phone number was listed. In fact, it's still listed if you look hard enough.
So then I went from his home phone number. Hey, we have the technology. Okay. So monkey or
whoever's back there, work with me, but work with me, darling, and let's make this happen. Okay. So
go forward. Just keep, I'll say next, next, next. Okay. So we talked about this. Stop right
there. Okay. New York City. Okay. This is one we didn't talk about. New York City data mine where
the women's organizations were outed. So there's a problem which is neglecting to read and redact
data before releasing it. Next slide. Yes. Toronto. You know, you call 311, you complain about
something. So sure enough, in Toronto, they build a database of that. And they're supposed to be
careful to anonymize it. We have six-digit postal codes. They're only supposed to put in the first
three. Well, I looked at the database, and sometimes they go blur and Danforth. They put
actual intersections. So just sloppy, lazy data entry is the second problem. Next slide.
Okay. This is actually from my place in Calgary. Do any of you know C-Click-Fix? Great system. You
want to report a pothole. You want to report a place where criminals hang out. You go anonymously
and you enter the data. Well, sure enough, in Calgary, there's somebody who hates the car wash
in his neighborhood. So every day he puts in excessive noise, dangerous ice. So he's just got
a hate on for that car wash. Next slide. Okay. This is the European data channel. Next slide.
Who won? There it is in Slovenia from our taxes. Next slide. Okay. Who wouldn't agree with that?
Well, the judge ordered them to take down the data. Next slide. A little technical aside,
they didn't take down the data, so judges lagged behind technology. We know that. Next slide.
Election results. There's the guy who got all the votes. Next slide. Did my wife vote for me? Well,
apparently not, because all these people got zero votes. Next slide. Philadelphia. Okay. Finance
records. Next slide. There it is. The full home address is provided. Next slide. Okay. That's the
kind of computer that we had. I had one of those Commodore pets. Anybody have a pet? Yeah. In the
law. So maybe they're a little out of date. Next slide. Okay. There's the kind of stuff I could get.
There's Ronald Revest's home address if you want to write to him in Arlington, Massachusetts. Next
slide. Yes, that is Ron Revest and all of his family gave to Barack Obama in this case. Next
slide. Okay. Let's just keep going. Next slide. Okay. So the donor files were downloadable. Next
slide. Most common names, Smith, Johnson, and Williams. That's the number of Smiths and
Johnson's. Very small number of duplicates. Next slide. Okay. It was really useless, and when I
looked at the address on Spring Street. Next slide. There it is. It's the International Brotherhood
of Electrical Workers. Next slide. Okay. Problems underestimating our desire to torture the
data, inconsistent data, like some people giving home address, some giving the union, and the
wire requiring address needs to be examined in the light of new tools. Next slide. Okay.
There's the guy. His name is Clyde Betto. Nice man. Next slide. There's his home address and the
phone book. I took out his phone number. It's still valid. Next slide. There's his property tax
assessment. Next slide. There's details of his property tax. Next slide. There he is plotted on a
map. His house is worth $710,000. His neighbors are worth less. This spawned an industry of people
writing letters to say, dear Mr. Betto, we see that you're assessed at this much money. Did you
know that your house is assessed at $414,000? Wouldn't you like us to appeal your taxes? So the
city actually had to shut down this database. Next slide. They now have technical and legal
safeguards which are dumb, like you can only query ten times from an IP address in a day. Well,
anybody in this room can spoof that one. Next slide. Next one. Okay. Here's Fernando County.
There's the sheriff. Nice smiley face. Next slide. There's the not so friendly looking people who
work for things like uttering Ford's instrument and contempt of court. Next slide. There's poor
Bobby. That's real. Note his date of birth, 1997. That made him 12 years, 12 months at the time of
arrest. Shame on you, sheriff. Next slide. Data journalism. Okay. I lived in the Bronx for a long
time. The Rockland County newspaper released a map of all the people with pistol permits. Well,
sure enough, one of them actually lived in the Bronx on Crosby Avenue, a few blocks from where I
was. So this is public information. You get some interesting results, though, like people who have
multiple pistol permits and live opposite an elementary school. Next slide. Okay. So here's a
kind of provocative question. Should the rich have less privacy? You know, when we go out there
and we do data journalism on rich people, like corporate directors, we could also go out there
and find people who are abusing the SNAP food stamp program. But it's an interesting societal
question. Do we go after those people or do we just go after the eaters? I don't know. I don't know.
Easy pickings, the high profile ones. Next slide. Okay. Indirect risk. There are companies
collecting this data like Checkpoint. Next slide. Ancestry.com. They have 6 billion records, mostly
courtesy of the public. Next slide. There's your DNA test. They want your DNA. And they charge you
$99 to take it from you. Next slide. Or if you're in New York City, there's mobile DNA testing. All
you have to do is flag him down. There he is. And he'll tell you who your daddy was right on the
spot.
Next slide, please. Okay. There's the complaint against him from Privacy International. Next
slide. Tools that we use for this. An inquiring mind. That's the most important one. Having a
motive. Like, you know, financial motive, ID theft and so on. Scripting languages. Scraper
wiki. Again, getting technical on you here. Python, PHP scripts. All this stuff is out there.
There are libraries of scripts. And if you don't want to do that, just go to a hackathon.
And some friendly person will show you how to do it. Next slide. Okay. Even if it's always been public
data, it's super public. Companies like Check Point actually go out there, Choice Point, rather,
they actually go out there and they pay high school students to go into the basement of
courthouses and hand copy people's divorce settlements. Because you're not allowed to
photocopy them. You're not allowed to download them electronically. But they're public
information. Once that stuff gets put into a public file, as it is at Choice Point,
it can be accessed for a fee. I knew one guy who could never get a job. He didn't know why.
He was an engineer. He'd always get interviewed, never get hired. And he finally got a friend to
pull his private file from Choice Point. And what was it? He was a convicted murderer. Well,
he wasn't actually a convicted murderer. They got his social security number wrong. And, you know,
his friend said, well, you know why you're not getting a job? You're a murderer. And he said,
I am not. Next slide. Okay. So here are the dirty dozen. Inadvertent disclosure of data. Sloppy
malicious information. The lag between law and policy. Making inferences from those small
numbers like very few people who voted. Assuming nobody like me will torture the data. My name is
Tom and I torture data. Next. Inconsistent data where, you know, I did a project with the
RAND Corporation years ago where we were collecting data on New York City fire trucks.
And we had people getting from the battery, like Battery Park to Harlem in a fire truck in three
and 40 seconds. And we couldn't figure out how that could be. You know, they're not helicopters.
We finally went and watched them. And what happened is the guy who sits next to the driver was
recording the data. They would go out and put fires out all day. And then they would go, oh,
we forgot to do that for those RAND guys. We better go fix it. And they made up all the data.
Data jigsawing, taking different databases, public and private, and putting them together. Facial
recognition. A whole big area coming up. Your face can be quite a vulnerable thing. I know
Alessandro Acquisti stood here.
Last year and talked about the fact that he can take your photo on Facebook and your photo on
Match.com. And he can find out if you're a sexy babe 235, if you're a hung dude 204. He can
disambiguate those just using your face. Retroactive analysis going back. So some
recommendations. We have to scan the file for PII that might be included. Think about ways it
could be revealed indirectly. This is all on the CD. I don't need to read it to your next slide.
And I want to tell you a little bit about this image. There's a great project out there,
concepts for all. And it basically is, I want to end on a hopeful note, there was a poster program
at the University of Quebec of Montreal, a poster design program. It was going to be shut down
because it's so expensive to print posters and all that. And my friend who runs it discovered
this thing called the internet. So now all these images get posted on the internet. They are
beautiful images. And the only condition for using them for something like this is to print them.
Is that you say this was courtesy of Elise Pechat. So I've given her credit for that. So I
recommend that site to you. I recommend that you talk to your government. We are the people. We are
the democracy. We get to decide supposedly what our governments do to or for us. This is an area
that you're going to be hearing much more about. I promise to stay on time. I think I've got five
minutes for questions. Is that about right? Yep. Okay. So let's have the first question. Thank you.
And thanks to all the hard working goons who made this image actually come up there. We've paved
the way for all the future speakers. It's hard to get the first question. I'll start with the
second question, okay? Who's got a question? Yes, you're in. Turn him on. Turn him on, please.
Come up. Oh, there we go. I'd rather see you.
I don't want to be recognized. So there's generally a movement in the United States to crack
down on perceived voter registration fraud. It's mostly bullshit. But it's a way to keep black
people from voting. But in general, in general, I think governments feel like if you require
people to provide an address, it keeps them honest, even if it isn't particularly useful. Is
there another way you can think of to keep people more honest on forms?
You can take it. Is there another way you can think of to keep people more honest on forms?
Or should we just stop worrying about it? I mean, you know, actual election fraud where somebody
pretends to vote or votes twice, I mean, it's almost impossible to find an instance. But I was
wondering what you think about that. You could take their DNA. There's all kinds of other things
you can do. I mean, the whole point of the address is the reason people get. Yeah. You could
do other. He asked how you could do something other than addresses to eliminate voter fraud.
And I joked that you could take people's DNA. I mean, there are countries in the world where people
vote and they don't vote. And they don't vote. And they don't vote. And they don't vote. And they
get their finger marked with ink, right? And sometimes they don't want to vote because having
their finger marked with ink, they might get that finger cut off by somebody or, you know, be punished
for voting. There are alternative ways to do it. But I don't, I can't think of too many other ways.
If your contribution is small enough, I think the reality is giving your address is optional. You
can give the address of your union and never go pick up the result. So campaign laws, I guess the
big idea is that the campaign law really needs to be reviewed. When it was passed in 1970,
it didn't really have, we didn't have the technology to do the kind of things that we do now
with the data. And it's only going to get bigger. And the data now is going to stick around forever.
So they'll be able to go back not seven years, but 27 years. Yes.
Scraper Wiki has a whole library of tools. I mean, to tell you the God's honest truth,
I used Excel because that's all I had to really use to take that.
There's in the presentation, there are those lists of Scraper Wiki and so on. There are a bunch of
places where you have kind of customized scripts that allow you to go out there and scrape public
databases. You know, the world is your oyster. I think just about every municipality now has
some kind of data there. And I just keep finding more and more. And I haven't really found one yet
that I don't have problems with. So I guess the challenge to you for, you know, between now and
next year is to find a lot more holes in open government and bring them to our attention.
One more question maybe? Going once?
Yeah, do it.
Do you know if any of those terms of service for public data requests have been tested in courts?
I don't. And I actually asked Marcia Hoffman that very question. And she's researching that
because I thought that's a very interesting thing. All I can tell you is in Calgary,
I'll just summarize the story. Because of people doing what I did and also because of that
secondary use of the data to actually try to commercialize it, the city shut the database
down for a period of time. And when it came back, there was a very elaborate terms of use that I
violated here today because it says this is only for checking your tax records. Because when it
first came out, people were checking their boss's house assessment. They were checking their ex-wife,
everybody that they knew. And they now control it.
What they've done, and it's a good point, they have two different levels of access.
If you want to just know, and I should tell you, you're allowed to know what your neighbor has
assessed because that's an issue of fairness. If you're assessed unfairly, you have a right to
appeal. But you're not allowed to know how many square feet and all the other details. So what
they do now is there's a public-facing one with just the number, the assessment. There's a deeper
level that you have to sign up and be validated. So that's how Calgary, and I want to say Calgary
did. I think in Calgary, it was a very, very, very, very, very, very, very, very, very, very,
an admirable job of taking what was a real mess and making it good. And hopefully other cities
will follow that lead. Are we done? Thanks, Monki. Thanks very much.