WEBVTT

00:00:01.014 --> 00:00:04.185
(lift)

00:00:04.185 --> 00:00:07.244
(lift 12 - Feb 24 2012 - Geneva)

00:00:07.244 --> 00:00:10.044
(Rufus Pollock - Stories)

00:00:10.044 --> 00:00:11.788
[Rufus Pollock] Just to say for those of you who don't know:

00:00:11.788 --> 00:00:13.666
the Open Knowledge Foundation is a not-profit -- not for profit

00:00:13.666 --> 00:00:15.611
founded in 2004

00:00:15.611 --> 00:00:17.865
and which builds tools and communities

00:00:17.865 --> 00:00:20.934
to create, use and share open information

00:00:20.934 --> 00:00:24.585
and that's information that anyone can use, reuse and redistribute.

00:00:24.585 --> 00:00:28.321
And as such, we've been working on open data for quite a long time

00:00:28.321 --> 00:00:30.011
since we started in 2004.

00:00:30.011 --> 00:00:34.817
And today, I want to start the story by going back in time 5000 years,

00:00:34.817 --> 00:00:37.610
to ancient Mesopotamia.

00:00:37.610 --> 00:00:41.393
There, between the Tigris and the Euphrates rivers,

00:00:42.069 --> 00:00:44.390
flourished the Sumerian civilization.

00:00:44.390 --> 00:00:47.298
And they were confronted by a problem.

00:00:47.298 --> 00:00:50.269
They were confronted by the limitations of human memory

00:00:50.899 --> 00:00:54.338
in the recording of taxes, food and other goods.

00:00:54.338 --> 00:00:59.642
And those ancient civil servants and businessmen hit on a novel solution:

00:01:00.380 --> 00:01:04.666
What they decided to do was they would start counting things with small clay chits,

00:01:04.666 --> 00:01:09.234
which they would bake inside of a clay -- a little clay box

00:01:09.234 --> 00:01:12.617
and then mark, on the outside of that box, what they were counting.

00:01:12.617 --> 00:01:15.303
You know, was it grain, was it tax payments, whatever.

00:01:16.150 --> 00:01:19.786
And so, born out of necessity for a state and a society,

00:01:20.632 --> 00:01:25.773
came one of the great information technology revolutions of all time: writing.

00:01:25.773 --> 00:01:28.172
The Sumerians invented writing via cuneiform.

00:01:28.910 --> 00:01:34.039
And if we fast-forward from that a few thousand years, we come to the UK census.

00:01:34.039 --> 00:01:37.577
Again, it's always interesting that states, governments are often at the forefront

00:01:37.577 --> 00:01:42.681
of at least driving information technology and information systems innovations.

00:01:42.681 --> 00:01:44.654
The UK census: again, the state,

00:01:44.654 --> 00:01:46.565
this is during the Napoleon Wars,

00:01:46.565 --> 00:01:48.601
desired to count the population more accurately:

00:01:48.601 --> 00:01:51.995
and we have the first UK census in 1801.

00:01:51.995 --> 00:01:56.189
And in the US, they also had censuses, in fact starting in 1790.

00:01:56.819 --> 00:01:59.383
And one of the problems encountered in the 1880 census

00:01:59.383 --> 00:02:01.592
was they tabulated the census by hand.

00:02:02.345 --> 00:02:05.699
And by the 1880 census, it was taking seven years

00:02:05.699 --> 00:02:06.822
to tabulate the census.

00:02:06.822 --> 00:02:10.241
So after it got taken in 1880, it wasn't until 1887

00:02:10.241 --> 00:02:12.892
they actually had any data they could use.

00:02:12.892 --> 00:02:16.004
And they calculated that for the next census in 1890,

00:02:16.004 --> 00:02:18.164
they wouldn't be finished by 1900.

00:02:18.164 --> 00:02:21.936
They still wouldn't have the results of the census by the time they started the next one.

00:02:21.936 --> 00:02:24.233
They had a crisis of information technology.

00:02:24.233 --> 00:02:26.979
And what they went and did is they commissioned Herman Hollerith

00:02:26.979 --> 00:02:29.747
to build the first automatic tabulator.

00:02:29.747 --> 00:02:32.835
And for those of you who know your company history, of course,

00:02:32.835 --> 00:02:34.513
Herman Hollerith's company went on

00:02:34.513 --> 00:02:35.899
to be one of the founders, if you like,

00:02:35.899 --> 00:02:38.808
one of the companies that came and created IBM.

00:02:38.808 --> 00:02:42.258
And IBM, by the sixties, were building this

00:02:42.258 --> 00:02:44.374
-- they replaced those hand --

00:02:44.374 --> 00:02:45.905
those kind of wooden, mechanical tabulators

00:02:45.905 --> 00:02:48.524
with this stuff: digital tabulators,

00:02:48.524 --> 00:02:50.375
the modern computer of this age.

00:02:50.375 --> 00:02:52.610
And again, much of this -- I don't know if you guys know --

00:02:52.610 --> 00:02:53.705
IBM would have gone bankrupt

00:02:53.705 --> 00:02:58.477
if it hadn't been for Franklin Roosevelt passing the Social Security Act in the States,

00:02:58.477 --> 00:03:01.132
which necessitated a huge amount of new tabulation.

00:03:01.132 --> 00:03:04.629
So, again, a lot of innovation in this space came out of government need

00:03:04.629 --> 00:03:06.370
and also, of course, the nuclear program,

00:03:06.370 --> 00:03:08.641
the other great needer of computational power.

00:03:09.317 --> 00:03:11.899
And today, today,

00:03:12.623 --> 00:03:15.485
we find ourselves again in the midst of a revolution.

00:03:16.438 --> 00:03:19.331
It's a revolution driven by two needs:

00:03:19.331 --> 00:03:22.027
ones that have been the same throughout history as I've just shown,

00:03:22.027 --> 00:03:23.886
information complexity, which is the necessity,

00:03:24.456 --> 00:03:27.575
and information technology, which is the opportunity.

00:03:28.544 --> 00:03:32.702
And what we're doing in this case is a policy innovation, if you like.

00:03:32.702 --> 00:03:36.468
We are innovating by opening up information.

00:03:37.052 --> 00:03:39.436
So just take the obvious example, government,

00:03:39.436 --> 00:03:41.097
as I said, often the innovator.

00:03:41.097 --> 00:03:43.308
In the last -- 3 years ago, you go back 3 years,

00:03:43.308 --> 00:03:45.829
there's almost no open government data initiatives

00:03:45.829 --> 00:03:46.688
in the world.

00:03:46.688 --> 00:03:48.442
Today there are dozens.

00:03:48.442 --> 00:03:51.162
The UK, the US, Finland, Kenya, The Netherlands,

00:03:51.162 --> 00:03:53.049
and there's new ones almost every week.

00:03:53.049 --> 00:03:57.407
There's been a launch of an official kind of movement as a part of the UN

00:03:57.407 --> 00:04:00.097
called the Open Government Partnership in which countries sign up,

00:04:00.097 --> 00:04:02.433
and among other things, they open up their data.

00:04:03.002 --> 00:04:05.325
And of course, it's been, in the UK and other countries,

00:04:05.325 --> 00:04:06.562
Tim Berners-Lee has been involved.

00:04:06.562 --> 00:04:09.106
I've helped advise the government around this in the UK.

00:04:09.106 --> 00:04:11.221
But it's not just government, it's also companies.

00:04:11.651 --> 00:04:13.982
Companies are opening up data.

00:04:13.982 --> 00:04:15.690
Very interestingly, last year,

00:04:15.690 --> 00:04:19.092
Nike started an open data initiative there

00:04:19.092 --> 00:04:21.372
to open up supply chain and sustainability data,

00:04:21.372 --> 00:04:23.931
for themselves and also for their suppliers,

00:04:23.931 --> 00:04:26.800
which I think is a very interesting change.

00:04:26.800 --> 00:04:28.004
And it's also communities.

00:04:28.004 --> 00:04:29.715
Often, in fact, back there in the beginning,

00:04:29.715 --> 00:04:31.927
this incredible map that you saw in an earlier slide,

00:04:31.927 --> 00:04:35.002
is a OpenStreetMap activity, around the world.

00:04:35.002 --> 00:04:38.073
People adding to this crowd-built map of the world.

00:04:38.073 --> 00:04:41.074
And in the last 6 years, OpenStreetMap,

00:04:41.074 --> 00:04:42.445
from a bottom-up community,

00:04:42.445 --> 00:04:44.435
have built a complete, comprehensive,

00:04:44.435 --> 00:04:47.918
map of the world, of fully open data.

00:04:48.872 --> 00:04:50.898
So I've just gone on about Open Data,

00:04:50.898 --> 00:04:52.766
and one thing I'm aware of, of this audience,

00:04:52.766 --> 00:04:54.035
is you might not all know what it is.

00:04:54.035 --> 00:04:59.152
So I'm going to take a brief moment, a brief moment, to say what it is.

00:04:59.152 --> 00:05:01.493
What does it mean when I say 'open'?

00:05:01.493 --> 00:05:05.557
And was it, you know, what's different from anything else? What's different from simply public data?

00:05:05.557 --> 00:05:07.083
So there's actually a definition,

00:05:07.083 --> 00:05:10.177
a definition we the Open Knowledge Foundation helped write, it's very simple.

00:05:10.177 --> 00:05:13.671
In a nutshell, a piece of information, a piece of data,

00:05:13.671 --> 00:05:18.384
is open if anyone is free to use, reuse,

00:05:18.384 --> 00:05:20.797
and redistribute it, subject only at most

00:05:20.797 --> 00:05:22.891
to a requirement to attribute and share alike.

00:05:23.214 --> 00:05:25.784
And anyone means anyone!

00:05:25.784 --> 00:05:28.055
It doesn't mean -- there can't be any commercial restrictions.

00:05:28.055 --> 00:05:32.262
You can't say: hey, here's this data, but only people using it for non-commercial purposes.

00:05:32.262 --> 00:05:34.849
Or only people working in education.

00:05:34.849 --> 00:05:38.051
Or only people living in the developing world, or the developed world.

00:05:38.051 --> 00:05:40.743
There can't be any restrictions like that.

00:05:41.343 --> 00:05:43.189
And there's a reason for this, by the way,

00:05:43.209 --> 00:05:48.615
and it isn't just because one's obsessed about if you like, trademarking an attractive term.

00:05:49.315 --> 00:05:51.081
It's because it's about interoperability.

00:05:51.291 --> 00:05:54.617
One of my experiences at this conference, which I remember from previous trips to Geneva,

00:05:54.627 --> 00:05:56.974
is I've been unable to plug in my laptop!

00:05:56.974 --> 00:06:02.048
Even though I have a French adaptor, in fact, these wonderful Swiss plugs here, are, you know,

00:06:02.048 --> 00:06:03.582
these wonderful, small octagonal shape.

00:06:03.582 --> 00:06:05.379
And even with my adaptor I can't plug in.

00:06:05.379 --> 00:06:07.347
Right? And it's called interoperability.

00:06:07.347 --> 00:06:10.929
When we travel around to different countries, our power adaptors don't actually fit in.

00:06:10.929 --> 00:06:12.581
We have to buy something.

00:06:12.581 --> 00:06:16.755
And the point about this definition, and the point about caring about Open Data,

00:06:16.755 --> 00:06:18.317
is, it's about interoperability.

00:06:18.317 --> 00:06:22.112
The dream of Open Data is interoperability.

00:06:22.112 --> 00:06:26.058
Of seamlessly being able to share and interweave information.

00:06:27.898 --> 00:06:31.704
And if every time I get information from two different people I have to consult a lawyer,

00:06:31.704 --> 00:06:35.300
I have to work out whether I'm allowed to do it, whether I'm allowed to put these things together,

00:06:35.300 --> 00:06:37.634
we lose that dream, that dream is shattered.

00:06:37.634 --> 00:06:42.166
And the key point is, this definition, and those conditions, ensure interoperability.

00:06:42.166 --> 00:06:45.744
If you comply with them, we know that any piece of info, of Open Data,

00:06:45.744 --> 00:06:47.880
will work with any other piece of Open Data.

00:06:48.681 --> 00:06:52.932
And also, it's worth saying for a quick moment, what kind of data, and to emphasize a point.

00:06:52.932 --> 00:06:55.985
Just to foreclose those kinds of questions, otherwise I always get asked.

00:06:55.985 --> 00:06:58.809
When we talk about opening up data, in general,

00:06:58.809 --> 00:07:01.026
we're not talking about personal data.

00:07:01.026 --> 00:07:04.161
We're not talking about opening up your private health records

00:07:04.161 --> 00:07:08.302
or opening up your personal tax information.

00:07:08.302 --> 00:07:11.267
We're talking about information that is non-personal in nature.

00:07:11.267 --> 00:07:15.667
And for the government for example: transport, geodata, statistics, electoral, legal.

00:07:15.667 --> 00:07:19.510
Stuff that the UK has, in fact, for example been opening up over the last few years.

00:07:19.510 --> 00:07:23.381
This financial information, on government spending, this information on health outcomes,

00:07:23.381 --> 00:07:28.625
on prescriptions, this information on educational outcomes, this information on the law.

00:07:28.625 --> 00:07:30.765
This information -- statistical information.

00:07:30.785 --> 00:07:32.691
That's the kind of thing that we're talking about.

00:07:34.186 --> 00:07:37.393
Now, I want to say, it's in this story, we have this story of over time.

00:07:37.393 --> 00:07:38.996
But why governments are doing it now?

00:07:39.596 --> 00:07:40.598
And why Open Data?

00:07:41.268 --> 00:07:43.930
So, okay, for thousands of years, governments innovate,

00:07:43.930 --> 00:07:47.274
but why do they innovate at this particular moment and in this way?

00:07:47.274 --> 00:07:51.976
So I want to start here with a quick story, a story of medicine gone wrong.

00:07:52.006 --> 00:07:54.484
It is from a great book by a guy called Stephen Klaidman.

00:07:54.484 --> 00:07:55.918
It's in fact one of the things

00:07:55.918 --> 00:07:57.781
that made me think quite deeply about this:

00:07:57.781 --> 00:07:59.852
why I was interested in Open Data.

00:08:01.172 --> 00:08:02.917
In that picture there, you can see

00:08:02.917 --> 00:08:05.726
what was the Redding Medical Centre in Northern California.

00:08:05.726 --> 00:08:10.471
There, in 2002, in the Summer of 2002, John Corapi,

00:08:11.231 --> 00:08:12.401
in typical American style,

00:08:12.401 --> 00:08:15.374
an ex-accountant from Vegas turned Catholic priest,

00:08:15.374 --> 00:08:17.243
[scattered laughter]

00:08:17.783 --> 00:08:22.274
...arrived at the Redding Medical Centre having been referred by his doctor for having chest pains.

00:08:22.784 --> 00:08:28.419
He had a cardiogram by the local cardiologist and was told that he needed an immediate heart bypass,

00:08:28.419 --> 00:08:31.484
that he was at serious risk, and that he should come back later that day,

00:08:31.484 --> 00:08:34.514
or at the latest, tomorrow, to have open heart surgery.

00:08:35.764 --> 00:08:37.985
Rather shocked, and dazed by this news,

00:08:37.985 --> 00:08:41.225
he returned home to pack his bags in order to return to hospital.

00:08:41.225 --> 00:08:45.102
He called up his best friend, who was still an accountant in Vegas,

00:08:46.032 --> 00:08:52.568
whose partner was a hospital nurse, and who advised him that he should get a second opinion,

00:08:52.568 --> 00:08:55.904
that, according to his partner, it was not, you know,

00:08:55.904 --> 00:08:58.981
it was very unusual that you would need to have immediate open heart surgery,

00:08:58.981 --> 00:09:00.235
and that he should get a second opinion.

00:09:00.975 --> 00:09:04.507
Rather doubtful about this, because he was extremely worried, he did get on a plane.

00:09:04.507 --> 00:09:07.919
He went to Vegas, he got seen by another specialist...

00:09:07.919 --> 00:09:11.785
who, to his complete surprise, told him there was nothing wrong with his heart.

00:09:12.805 --> 00:09:15.289
He saw another specialist, just to make sure.

00:09:15.289 --> 00:09:18.563
They told him also, there was nothing wrong with his heart.

00:09:19.343 --> 00:09:25.067
Relieved, and rather, you know, happy, he returned home and just wanted to really forget about it.

00:09:25.067 --> 00:09:27.389
But his friend said: "No, what's going on here? Something's wrong".

00:09:27.389 --> 00:09:32.613
And they went in to see the CEO of the Tenet Healthcare, the people running this hospital

00:09:32.613 --> 00:09:35.654
(which, by the way, was a private hospital), and said:

00:09:35.654 --> 00:09:38.614
"Look, something's wrong, what's going on, what are you going to do about this?"

00:09:38.614 --> 00:09:40.256
And basically they were told: not very much.

00:09:40.256 --> 00:09:44.581
You know, mistakes get made, it's bad luck, don't worry about it,

00:09:44.581 --> 00:09:46.233
we'll look into it, but thank you very much.

00:09:46.763 --> 00:09:51.631
They weren't convinced by this, and eventually they decided to contact the FBI.

00:09:51.631 --> 00:09:53.826
The reason they contacted the FBI, by the way,

00:09:53.826 --> 00:09:56.401
is it's a private healthcare provider in the United States,

00:09:56.401 --> 00:10:00.476
they provide Medicare provision of healthcare to the Federal Government.

00:10:00.476 --> 00:10:04.202
So, if the Federal Government is getting defrauded, the FBI can get involved.

00:10:04.982 --> 00:10:06.850
The FBI started investigating.

00:10:08.281 --> 00:10:12.081
Eventually it turned out, that hundreds, probably thousands of people

00:10:12.081 --> 00:10:15.854
over a ten or longer year period, had been operated on unnecessarily.

00:10:16.704 --> 00:10:19.561
Most of them had had serious procedures performed on them,

00:10:19.561 --> 00:10:22.189
open heart surgery, some had died as a result.

00:10:22.189 --> 00:10:24.325
Obviously it's quite a serious operation.

00:10:24.325 --> 00:10:27.437
Some people had basically been condemned to a lifetime of pain.

00:10:27.437 --> 00:10:31.437
One of the most traumatic examples was a 36-year-old, he had been cut open,

00:10:31.437 --> 00:10:33.000
which is obviously what happens in open heart surgery,

00:10:33.000 --> 00:10:35.369
and his chest had never knitted back together correctly.

00:10:35.999 --> 00:10:38.125
Basically, he would be in pain for the rest of his life.

00:10:39.395 --> 00:10:43.000
So, hundreds, thousands of people had been harmed.

00:10:43.610 --> 00:10:45.968
One of the interesting things was that in this community

00:10:45.968 --> 00:10:48.159
there was already some suspicion, there were anecdotes.

00:10:48.159 --> 00:10:50.853
I mean, one of the ones I really liked from this book was the story that went:

00:10:50.853 --> 00:10:56.021
'Don't get a flat tyre outside of Redding Medical Centre because you'll end up with a heart bypass.'

00:10:56.021 --> 00:10:57.303
[scattered laughter]

00:10:57.303 --> 00:11:00.258
You know, but the thing was, there was no data.

00:11:00.728 --> 00:11:04.563
People were you know, a bit suspicious, but it was among doctors who knew,

00:11:04.563 --> 00:11:06.867
you know, in the community, and who wants to doubt it.

00:11:06.867 --> 00:11:12.171
And guess what? Also, Redding Medical Centre had one of the best mortality rates,

00:11:13.001 --> 00:11:15.350
for cardiac procedures in the United States,

00:11:15.350 --> 00:11:19.609
because if you operate on healthy people, you have a good mortality rate!

00:11:19.619 --> 00:11:21.129
[scattered laughter]

00:11:21.129 --> 00:11:23.390
So, the other thing, though,

00:11:23.390 --> 00:11:25.452
and this is the point that comes to Open Data for me

00:11:25.452 --> 00:11:28.722
the other red flag if you had been looking at the data,

00:11:28.741 --> 00:11:31.927
was these two things: one is incredibly low mortality rate,

00:11:31.927 --> 00:11:35.351
and (B) that it had almost the highest number of procedures

00:11:35.351 --> 00:11:37.464
for the population that it covered in the United States,

00:11:38.144 --> 00:11:39.634
which should be a red flag, right?

00:11:39.634 --> 00:11:42.618
Because, one, it's just a massive outlier on that basis, and also,

00:11:42.618 --> 00:11:45.815
the more people you should be operating on, the more you're doing marginal cases,

00:11:45.815 --> 00:11:49.450
the higher should be your mortality rate unless something very odd is going on.

00:11:50.030 --> 00:11:53.015
The thought was: what if people had been looking at this data?

00:11:53.015 --> 00:11:56.045
What if we'd - if this data had been open and public,

00:11:56.045 --> 00:11:59.517
and not maybe just for particular researchers to look at or the government?

00:11:59.927 --> 00:12:04.129
And it kind of reminded me of a phrase that's very famous in Open Source software, which is:

00:12:04.129 --> 00:12:05.965
"To many eyes, all bugs are shallow".

00:12:05.965 --> 00:12:10.504
What's great about Open Source software is lots of people can look at it, lots of people can fix it.

00:12:10.504 --> 00:12:14.730
And for me, what this was saying was: to many eyes, all anomalies are noticeable.

00:12:14.730 --> 00:12:16.679
It's somewhat of an exaggeration,

00:12:16.679 --> 00:12:18.908
but what happens if rather than ten or twenty people

00:12:18.908 --> 00:12:22.077
who worked in monitoring Medicare provision in the US government,

00:12:22.077 --> 00:12:23.877
we'd had thousands or millions of people?

00:12:23.877 --> 00:12:26.919
If the local journalists or citizens, who had suspicions,

00:12:26.919 --> 00:12:28.747
had been able to go and look at that data and say:

00:12:28.747 --> 00:12:32.485
"Whoa! What's going on here? This isn't just anecdotes, there's some data".

00:12:34.205 --> 00:12:40.225
And so, and it's not just then, about kind of spotting healthcare errors, or issues, or risks,

00:12:40.225 --> 00:12:42.415
it's also about things like apps and services

00:12:42.415 --> 00:12:43.857
that you can build with Open Data.

00:12:43.867 --> 00:12:46.667
This is a great app built by mySociety in the UK,

00:12:46.667 --> 00:12:47.640
called Mapumental.

00:12:47.640 --> 00:12:48.974
And the question is, I don't know if people know,

00:12:48.974 --> 00:12:50.646
London house prices are very expensive,

00:12:50.646 --> 00:12:52.510
I don't know whether they rival Geneva's,

00:12:52.510 --> 00:12:55.238
but they're, it's a pretty difficult thing.

00:12:55.238 --> 00:12:57.978
And one of the questions was, if I have to work somewhere,

00:12:57.978 --> 00:13:01.752
and I want to know where I can live, and afford,

00:13:01.752 --> 00:13:05.757
and I can commute to work in a certain time, and it's not too ugly,

00:13:05.757 --> 00:13:07.583
this is what this app does.

00:13:07.583 --> 00:13:11.200
You can choose the price, you can say where you're going to work,

00:13:11.200 --> 00:13:14.195
you can choose the commute time, and you can choose the scenicness.

00:13:14.195 --> 00:13:17.167
And it will show you, on this map, where you can live.

00:13:18.427 --> 00:13:20.796
Another example, more about transparency,

00:13:20.796 --> 00:13:22.746
is a project we did called "Where Does My Money Go?".

00:13:23.976 --> 00:13:25.406
It's an interactive version,

00:13:25.406 --> 00:13:26.211
you can kind of draw it out,

00:13:26.211 --> 00:13:29.114
so what it starts with, is one, is it tells you what your tax is,

00:13:29.114 --> 00:13:30.821
something that most people often don't know,

00:13:30.821 --> 00:13:33.668
and it will tell you how much you're paying each day

00:13:33.668 --> 00:13:36.254
to a particular area of society.

00:13:36.254 --> 00:13:37.328
And the dream for me,

00:13:37.328 --> 00:13:39.127
a dream that we're on the way to realising,

00:13:39.127 --> 00:13:42.817
is in this visualisation, you can drill down into areas.

00:13:42.817 --> 00:13:45.092
And my dream is to keep drilling down.

00:13:45.472 --> 00:13:47.633
So depending on what day we have, I want to go down,

00:13:47.633 --> 00:13:49.628
right down through those bubbles, step by step,

00:13:49.628 --> 00:13:52.403
until I see the money spent on street lights on my street,

00:13:52.403 --> 00:13:55.270
on filling in potholes, on collecting my rubbish.

00:13:56.190 --> 00:13:57.138
And for two reasons:

00:13:57.138 --> 00:13:59.704
One, obviously there's a question, particularly in some countries,

00:13:59.704 --> 00:14:01.016
of inefficiency or corruption,

00:14:01.436 --> 00:14:05.176
but also, just because most of us don't feel very happy about paying tax.

00:14:06.066 --> 00:14:08.157
It's not one of those things people welcome!

00:14:08.157 --> 00:14:09.817
But it's something that we should.

00:14:09.817 --> 00:14:11.960
Government does an awful lot for us,

00:14:11.960 --> 00:14:14.287
and having a better sense of where it's going

00:14:14.287 --> 00:14:17.120
could make us feel an awful lot better about paying that tax.

00:14:17.120 --> 00:14:18.657
In the way that when we go to a restaurant,

00:14:18.657 --> 00:14:21.397
we don't, when we get the bill, we don't necessarily feel bad.

00:14:21.397 --> 00:14:24.334
We feel "Wow, I had a great meal. That was worth it."

00:14:25.274 --> 00:14:26.366
But why Open?

00:14:26.366 --> 00:14:29.079
I've given you examples, and you know, we see a lot of apps and services.

00:14:29.079 --> 00:14:30.948
Why is Open relevant here?

00:14:31.598 --> 00:14:36.350
This goes back to what I said about the information technology, the revolution.

00:14:36.350 --> 00:14:37.813
So it's the challenge and the opportunity.

00:14:37.813 --> 00:14:42.387
It's the challenge that we see today, is exploding informational complexity.

00:14:42.797 --> 00:14:43.924
I mean, another great story:

00:14:43.924 --> 00:14:47.728
in the 1820s, all bank clearing in the largest financial centre in the world

00:14:47.728 --> 00:14:51.848
was done in a single room, where people -- one person from each bank gathered

00:14:51.848 --> 00:14:56.402
and they'd go round the room pulling out gold, and swapping it around, between different banks.

00:14:56.402 --> 00:14:58.434
And that's how they did bank clearing.

00:14:59.074 --> 00:15:01.991
Today we have billions of transactions a minute.

00:15:01.991 --> 00:15:07.945
And the way we as humans deal with complexity is by dividing and conquering it.

00:15:07.945 --> 00:15:10.683
We split it up into manageable chunks that we deal with.

00:15:11.013 --> 00:15:12.381
The other answer,

00:15:12.381 --> 00:15:14.883
and this answer's particularly relevant about Open Data,

00:15:14.883 --> 00:15:16.219
is information technology.

00:15:16.219 --> 00:15:18.951
Today, a smartphone has as much computing power

00:15:18.951 --> 00:15:22.260
as the system that ran the Apollo moon landings.

00:15:22.260 --> 00:15:24.027
And an even better example is storage:

00:15:24.027 --> 00:15:26.930
one terabyte of storage today is a hundred dollars.

00:15:26.930 --> 00:15:30.297
In 1994, this would have cost 400,000 dollars.

00:15:30.297 --> 00:15:33.977
I can have every financial transaction

00:15:33.977 --> 00:15:38.376
the UK government, or the US government made last year, or even for the last decade,

00:15:38.376 --> 00:15:39.665
on my laptop.

00:15:39.665 --> 00:15:43.543
That was not possible for an average citizen a decade ago.

00:15:44.283 --> 00:15:48.187
So it's mass participation, information access, processing, and production.

00:15:48.187 --> 00:15:49.557
It's decentralisation.

00:15:49.557 --> 00:15:51.728
And the claim here is that openness is key.

00:15:51.728 --> 00:15:53.957
It's because it's about scaling.

00:15:54.547 --> 00:15:57.399
What we are doing is weaving data together.

00:15:57.399 --> 00:15:59.615
As I said, we deal with complexity by splitting it up.

00:15:59.615 --> 00:16:02.928
We componentise, we split data up into blocks

00:16:02.928 --> 00:16:04.670
that we recombine.

00:16:04.670 --> 00:16:07.201
But if we are going to recombine information,

00:16:07.961 --> 00:16:10.076
we need to put Humpty Dumpty back together again,

00:16:10.076 --> 00:16:12.909
it won't work most of the time if it is closed.

00:16:13.449 --> 00:16:17.039
We need Open Data to scale and to componentise.

00:16:17.679 --> 00:16:21.518
And it's a point just to make here in this respect, that you might think:

00:16:21.518 --> 00:16:23.351
"Well you know, you're talking about Open Data,

00:16:23.351 --> 00:16:24.721
you know, this could be true of anything!

00:16:24.721 --> 00:16:25.789
Why don't we have like,

00:16:25.789 --> 00:16:28.232
Open Cars, and Open Shoes, and you know,

00:16:28.232 --> 00:16:29.578
why don't we just share everything, man!

00:16:29.578 --> 00:16:31.026
It would be so beautiful!".

00:16:31.706 --> 00:16:33.393
Right? And the sad thing is,

00:16:33.393 --> 00:16:39.070
is that that hasn't generally worked as a way of organising most production in our society.

00:16:39.070 --> 00:16:44.074
Instead, we have private property, and so we don't do that much openness relatively.

00:16:44.074 --> 00:16:45.848
But there's something different about digital information.

00:16:45.848 --> 00:16:48.944
We all know it, but it's worth emphasising, which is, it's very cheaply copied.

00:16:49.344 --> 00:16:52.782
I mean, give me a copy of your data isn't a problem if you're the government.

00:16:52.782 --> 00:16:56.393
Give me a copy of your car, or your house, or whatever, is.

00:16:56.803 --> 00:16:58.584
And it's also about innovation here.

00:16:58.584 --> 00:17:01.219
I mean, in a way it's almost the purest aspect of markets.

00:17:01.219 --> 00:17:05.619
Markets are about moving things to the person who could use them most best.

00:17:06.389 --> 00:17:07.200
And that's true of data.

00:17:07.200 --> 00:17:10.660
The best thing to do with your data will likely be thought of by someone else.

00:17:11.340 --> 00:17:14.973
And vice versa! You will think of the best thing to do with someone else's data.

00:17:15.783 --> 00:17:20.103
And Open Data allows us, in the most frictionless, easiest way,

00:17:20.103 --> 00:17:22.708
to move data to where it can be most optimally used,

00:17:22.728 --> 00:17:23.905
particularly if you're government.

00:17:24.275 --> 00:17:26.843
So in short, it's about better understanding, it's about better government,

00:17:26.843 --> 00:17:29.115
it's about better research, it's about better economy.

00:17:29.115 --> 00:17:31.124
And something also for companies and governments:

00:17:31.124 --> 00:17:32.707
I think it's about better engagement.

00:17:33.137 --> 00:17:34.986
It's about a closer relationship, sometimes,

00:17:34.986 --> 00:17:37.331
between your citizens and you as the government.

00:17:37.331 --> 00:17:40.960
Between you, even possibly, as a company, and your users.

00:17:41.690 --> 00:17:43.972
So I wanted to kind of finish here by saying where we're going.

00:17:43.972 --> 00:17:46.429
The story was, of this talk, was, you know, where are we?

00:17:46.869 --> 00:17:49.654
Why have we got here? And where are we going?

00:17:50.734 --> 00:17:52.248
So one answer is just more use.

00:17:52.248 --> 00:17:55.313
So right now, I just said at the beginning, Open Data is relatively young.

00:17:55.313 --> 00:17:57.844
This vast outpouring, for example, of government data,

00:17:57.844 --> 00:18:02.058
that anyone can freely use, reuse, and redistribute, is really new,

00:18:02.058 --> 00:18:03.382
even if it's done three years ago.

00:18:03.382 --> 00:18:06.479
For example, in the UK, much of the most useful data that could be released

00:18:06.479 --> 00:18:09.091
has only been released in the last six months or a year.

00:18:09.091 --> 00:18:10.478
You want prescription data?

00:18:10.478 --> 00:18:11.894
Are you a pharmaceutical company,

00:18:11.894 --> 00:18:15.261
and you want to know what kind of prescription habits are going on in the UK?

00:18:15.261 --> 00:18:18.837
I would emphasise: at an anonymised or somewhat aggregate level.

00:18:18.837 --> 00:18:20.707
Do you want to know about what crime is going on?

00:18:20.707 --> 00:18:24.241
Are you building a real estate website and you want data on environment,

00:18:24.241 --> 00:18:25.742
or you want data on unemployment,

00:18:25.742 --> 00:18:28.742
or other information about where properties are situated?

00:18:28.742 --> 00:18:30.077
You can now get that.

00:18:30.687 --> 00:18:32.783
So I think there's going to be a lot more use from business.

00:18:33.743 --> 00:18:35.398
There'll be a lot more use from everyone.

00:18:35.398 --> 00:18:38.686
But I think particularly business is going to wake up to the opportunities here.

00:18:38.686 --> 00:18:40.192
I think it's also going to lead to more data.

00:18:40.192 --> 00:18:41.789
One is, government is going to be more data.

00:18:41.789 --> 00:18:45.597
I think also businesses are going to realise, and communities,

00:18:45.597 --> 00:18:47.719
that they want to share back some of that data,

00:18:47.719 --> 00:18:48.764
some of the data they have.

00:18:48.764 --> 00:18:50.863
It's not going to be their kind of crown jewels,

00:18:50.863 --> 00:18:53.707
and it's not going -- often start out with data that's not core to their business.

00:18:53.707 --> 00:18:58.108
It's like. kind of Nike, they realised that by opening and sharing data,

00:18:58.108 --> 00:19:00.569
they can scale in a way they can't on their own.

00:19:01.029 --> 00:19:03.069
And does it mean that richer data, going back

00:19:03.069 --> 00:19:05.809
-- how could I leave out Hegel and Marx in a talk like this --

00:19:05.809 --> 00:19:08.869
"Quantity changes quality" as Hegel told us.

00:19:09.319 --> 00:19:14.156
And more data, going back to that woven ball, more data actually means better data.

00:19:14.156 --> 00:19:17.634
It means richer data, it's a qualitative difference in what we can do.

00:19:17.634 --> 00:19:19.781
Geodata on it's own isn't that useful.

00:19:19.781 --> 00:19:21.593
Transport data on it's own isn't useful.

00:19:21.593 --> 00:19:24.023
Geodata plus transport data is useful!

00:19:24.703 --> 00:19:26.187
And we're going to be seeing data refining.

00:19:26.187 --> 00:19:27.441
Data is the new oil, right?

00:19:27.441 --> 00:19:28.928
So, we're going to refine it.

00:19:28.928 --> 00:19:32.037
And that's going to be a big business: higher quality data.

00:19:32.487 --> 00:19:34.149
I want to leave you with a couple of thoughts.

00:19:34.149 --> 00:19:35.646
So, one is, some people say:

00:19:35.646 --> 00:19:37.527
"Well, okay, but, you know, selling data is big business".

00:19:37.527 --> 00:19:40.987
And it is, but going forward in some of these things like software,

00:19:40.987 --> 00:19:42.485
data is going to be a platform.

00:19:42.485 --> 00:19:43.720
It's not a commodity.

00:19:43.720 --> 00:19:46.084
Businesses built purely on selling data,

00:19:46.084 --> 00:19:47.558
I just don't think are going to make it.

00:19:47.558 --> 00:19:51.668
You need to be building on your data, not attempting to purely sell it.

00:19:52.588 --> 00:19:54.638
And the other answer is to be modest.

00:19:55.278 --> 00:19:56.797
So I said: where are we going?

00:19:56.797 --> 00:19:57.917
I don't know if people know

00:19:57.917 --> 00:20:02.124
-- and this takes us back to an earlier age, an age of electricity and steam -- of Faraday.

00:20:02.124 --> 00:20:04.678
So he's demonstrating electricity at the Royal Society,

00:20:04.678 --> 00:20:08.316
and Gladstone, the future Prime Minister of England, sees him do this stuff, you know,

00:20:08.316 --> 00:20:10.445
the frog legs move, and Gladstone's like:

00:20:10.445 --> 00:20:12.392
"Well, I mean, this is party trick, Faraday.

00:20:12.392 --> 00:20:15.971
It's great, but, what's really, you know, what's electricity going to amount to?" (20:16)

00:20:15.971 --> 00:20:20.832
And Faraday says to him: "Well, what's the use of a baby?"

00:20:20.832 --> 00:20:24.299
You know, a baby when it's young is not very useful.

00:20:24.299 --> 00:20:25.718
[scattered laughter]

00:20:25.718 --> 00:20:27.426
But it grows up into something!

00:20:27.916 --> 00:20:29.725
And that is where we are going today.

00:20:29.725 --> 00:20:32.488
We are the beginning of the Open Data journey.

00:20:33.088 --> 00:20:36.157
And partly is, we don't know what it's going to grow up into.

00:20:36.157 --> 00:20:37.004
Thank you very much!

00:20:37.004 --> 00:20:40.558
[Applause]

00:20:40.558 --> 00:20:44.708
[Questioner] Um, citizens and I guess patients at hospitals,

00:20:44.708 --> 00:20:48.683
assume that the institutions have all this data and it's very well organised,

00:20:48.683 --> 00:20:49.925
and it's a question of will.

00:20:50.555 --> 00:20:53.889
Have you encountered cases in which they simply don't have it,

00:20:53.889 --> 00:20:57.268
or they have it, and it's just such a mess that they're too embarrassed to give it out?

00:20:57.268 --> 00:20:58.661
[Rufus Pollock] Absolutely.

00:20:58.661 --> 00:21:00.959
I mean, one story that kind of intrigues me,

00:21:00.959 --> 00:21:03.914
is we've been building this "Where Does My Money Go?" open spending project.

00:21:04.094 --> 00:21:06.948
And one of the things the government mandated was giving out,

00:21:06.948 --> 00:21:09.065
rather than just high-level financial information,

00:21:09.065 --> 00:21:11.445
giving out information at a detailed level, you know,

00:21:11.445 --> 00:21:12.838
so they now publish, for example,

00:21:12.838 --> 00:21:15.601
spending data from each government department monthly,

00:21:15.601 --> 00:21:17.713
every transaction within 5,000 pounds (check).

00:21:17.713 --> 00:21:22.119
Every purchase they make, every mobile phone provider they contract with, we get that data.

00:21:22.119 --> 00:21:25.590
And one of the intriguing things, of their mandating this, was it turned out,

00:21:25.590 --> 00:21:30.022
before, they had no way, before they did this, of actually seeing, on any regular basis,

00:21:30.022 --> 00:21:31.232
what their department spent money on.

00:21:31.232 --> 00:21:35.029
Because in fact, the only thing they reported up on to, in central government to Treasury,

00:21:35.029 --> 00:21:38.871
was kind of like, how much did you spend against Project X that you were allocated budget for?

00:21:38.871 --> 00:21:41.156
You know, departments, were actually really intrigued, they [say]:

00:21:41.156 --> 00:21:43.435
"Oh, that other department's going with Vodafone,

00:21:43.435 --> 00:21:46.349
and we're with Orange, and look how much they're paying per month!"

00:21:46.349 --> 00:21:49.310
So I think in essence, it is really driving changes in government,

00:21:49.310 --> 00:21:52.700
and yeah, there are people, I think you'd been worried about giving out data quality.

00:21:52.700 --> 00:21:54.841
I was just talking to the Department of Education last week and they said

00:21:54.841 --> 00:21:57.650
-- you know, one of the things -- they had financial information from schools,

00:21:57.650 --> 00:21:59.567
and which they were slowly being mandated to publish.

00:21:59.567 --> 00:22:01.220
And schools are suddenly all ringing up, saying:

00:22:01.220 --> 00:22:04.290
"Well we never really bothered to really update that information to be accurate!

00:22:04.290 --> 00:22:05.900
Uh, we really want to do it right now".

00:22:06.210 --> 00:22:08.164
So I think that definitely does happen, yep.

00:22:08.164 --> 00:22:12.460
[Questioner] Are you seeing now new roles in government, to help facilitate this?

00:22:13.099 --> 00:22:16.009
[Rufus Pollock] Yeah. I mean, to take another example, I, sorry.

00:22:16.009 --> 00:22:19.492
Both in government, so the UK government has a transparency kind of 'czar' if you like.

00:22:19.492 --> 00:22:22.812
Also I learnt, is Nike hired an Open Data evangelist.

00:22:22.812 --> 00:22:24.611
One of the things they, while they were implementing this programme,

00:22:24.611 --> 00:22:27.990
they actually hired explicitly, an Open Data evangelist.

00:22:27.990 --> 00:22:30.023
So yeah, I think we are, we're definitely seeing this in government.

00:22:30.023 --> 00:22:32.357
Both in the tech level, but also at the policy level.

00:22:32.357 --> 00:22:34.729
And I think it's not just government,

00:22:34.729 --> 00:22:37.957
it will also be companies doing this, and so on, who will be saying:

00:22:37.957 --> 00:22:39.192
"We need an Open Data expert.

00:22:39.192 --> 00:22:43.662
We need to be aware of what's going on here and be able to plan it as part of our strategy."

00:22:44.472 --> 00:22:45.489
[Questioner] A final question.

00:22:45.489 --> 00:22:48.972
You mentioned that, kind of outsourcing, almost, some of this data refining,

00:22:48.972 --> 00:22:51.306
outside government or the big institutions, has helped them.

00:22:51.306 --> 00:22:54.446
Can you tell us any stories of kind of gratitude being expressed by the government? I mean...

00:22:55.146 --> 00:22:57.247
[Rufus Pollock] Well, I mean, to kind of, yeah.

00:22:57.247 --> 00:22:58.773
I mean there was an interesting example actually

00:22:58.773 --> 00:23:01.792
where we had some complaint because the open spending data I told you about

00:23:01.792 --> 00:23:05.323
where we're aggregating the government spending and financial data

00:23:05.323 --> 00:23:10.651
-- you know, the site had a few performance issues, occasionally, as we loaded more data in.

00:23:10.651 --> 00:23:12.755
I remember kind of getting this call kind of going :

00:23:12.755 --> 00:23:16.266
"Well, you know, we're a little bit upset, you know, data.gov.uk,"

00:23:16.266 --> 00:23:19.133
and it turned out the reason was, the Treasury kept looking at this data,

00:23:19.133 --> 00:23:21.002
and they were annoyed when the site was going down.

00:23:21.002 --> 00:23:22.563
So that was really intriguing to me

00:23:22.563 --> 00:23:26.139
that we were kind of one of the best, at least, up-to-date aggregators out there.

00:23:26.139 --> 00:23:29.484
Um, I think you are already seeing people doing stuff with the data

00:23:29.484 --> 00:23:30.979
and kind of doing stuff, sometimes for free, you know.

00:23:31.289 --> 00:23:33.131
You don't have to have the shiny front-end.

00:23:33.131 --> 00:23:35.019
I mean, one of the things we went about, on about,

00:23:35.019 --> 00:23:36.493
I know Tim Berners-Lee went on about --

00:23:36.493 --> 00:23:41.393
raw data now, you know, you can build fewer shiny front-ends, and just release raw data.

00:23:41.393 --> 00:23:46.455
And you know, someone else will help you build the app, the front-end, the interface,

00:23:46.455 --> 00:23:47.762
and help you innovate about it.

00:23:47.762 --> 00:23:50.917
What is the best way to provide healthcare data to citizens,

00:23:50.917 --> 00:23:52.254
or education data to citizens,

00:23:52.254 --> 00:23:54.367
so they make better and more informed choices?

00:23:54.367 --> 00:23:56.608
I don't know, and the government probably doesn't know.

00:23:56.608 --> 00:23:59.155
But somewhere out there, someone is going to innovate

00:23:59.155 --> 00:24:02.672
and really provide the best way for us to deliver that kind of information to citizens.

00:24:02.672 --> 00:24:04.250
QUESTIONER: Thank you very much.

00:24:04.250 --> 00:24:05.296
[Rufus Pollock] Thank you.

00:24:05.296 --> 00:24:06.901
[Applause]

00:24:06.901 --> 00:24:09.423
lift _ Video Production ACTUA

00:24:09.423 --> 00:24:11.311
Copyright (c) 2012 Lift conference