Open Data: How We Got Here, and Where We’re Going
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0:01 - 0:04(lift)
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0:04 - 0:07(lift 12 - Feb 24 2012 - Geneva)
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0:07 - 0:10(Rufus Pollock - Stories)
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0:10 - 0:12[Rufus Pollock] Just to say for those of you who don't know:
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0:12 - 0:14the Open Knowledge Foundation is a not-profit -- not for profit
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0:14 - 0:16founded in 2004
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0:16 - 0:18and which builds tools and communities
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0:18 - 0:21to create, use and share open information
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0:21 - 0:25and that's information that anyone can use, reuse and redistribute.
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0:25 - 0:28And as such, we've been working on open data for quite a long time
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0:28 - 0:30since we started in 2004.
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0:30 - 0:35And today, I want to start the story by going back in time 5000 years,
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0:35 - 0:38to ancient Mesopotamia.
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0:38 - 0:41There, between the Tigris and the Euphrates rivers,
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0:42 - 0:44flourished the Sumerian civilization.
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0:44 - 0:47And they were confronted by a problem.
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0:47 - 0:50They were confronted by the limitations of human memory
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0:51 - 0:54in the recording of taxes, food and other goods.
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0:54 - 1:00And those ancient civil servants and businessmen hit on a novel solution:
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1:00 - 1:05What they decided to do was they would start counting things with small clay chits,
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1:05 - 1:09which they would bake inside of a clay -- a little clay box
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1:09 - 1:13and then mark, on the outside of that box, what they were counting.
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1:13 - 1:15You know, was it grain, was it tax payments, whatever.
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1:16 - 1:20And so, born out of necessity for a state and a society,
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1:21 - 1:26came one of the great information technology revolutions of all time: writing.
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1:26 - 1:28The Sumerians invented writing via cuneiform.
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1:29 - 1:34And if we fast-forward from that a few thousand years, we come to the UK census.
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1:34 - 1:38Again, it's always interesting that states, governments are often at the forefront
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1:38 - 1:43of at least driving information technology and information systems innovations.
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1:43 - 1:45The UK census: again, the state,
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1:45 - 1:47this is during the Napoleon Wars,
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1:47 - 1:49desired to count the population more accurately:
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1:49 - 1:52and we have the first UK census in 1801.
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1:52 - 1:56And in the US, they also had censuses, in fact starting in 1790.
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1:57 - 1:59And one of the problems encountered in the 1880 census
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1:59 - 2:02was they tabulated the census by hand.
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2:02 - 2:06And by the 1880 census, it was taking seven years
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2:06 - 2:07to tabulate the census.
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2:07 - 2:10So after it got taken in 1880, it wasn't until 1887
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2:10 - 2:13they actually had any data they could use.
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2:13 - 2:16And they calculated that for the next census in 1890,
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2:16 - 2:18they wouldn't be finished by 1900.
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2:18 - 2:22They still wouldn't have the results of the census by the time they started the next one.
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2:22 - 2:24They had a crisis of information technology.
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2:24 - 2:27And what they went and did is they commissioned Herman Hollerith
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2:27 - 2:30to build the first automatic tabulator.
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2:30 - 2:33And for those of you who know your company history, of course,
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2:33 - 2:35Herman Hollerith's company went on
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2:35 - 2:36to be one of the founders, if you like,
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2:36 - 2:39one of the companies that came and created IBM.
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2:39 - 2:42And IBM, by the sixties, were building this
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2:42 - 2:44-- they replaced those hand --
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2:44 - 2:46those kind of wooden, mechanical tabulators
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2:46 - 2:49with this stuff: digital tabulators,
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2:49 - 2:50the modern computer of this age.
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2:50 - 2:53And again, much of this -- I don't know if you guys know --
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2:53 - 2:54IBM would have gone bankrupt
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2:54 - 2:58if it hadn't been for Franklin Roosevelt passing the Social Security Act in the States,
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2:58 - 3:01which necessitated a huge amount of new tabulation.
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3:01 - 3:05So, again, a lot of innovation in this space came out of government need
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3:05 - 3:06and also, of course, the nuclear program,
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3:06 - 3:09the other great needer of computational power.
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3:09 - 3:12And today, today,
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3:13 - 3:15we find ourselves again in the midst of a revolution.
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3:16 - 3:19It's a revolution driven by two needs:
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3:19 - 3:22ones that have been the same throughout history as I've just shown,
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3:22 - 3:24information complexity, which is the necessity,
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3:24 - 3:28and information technology, which is the opportunity.
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3:29 - 3:33And what we're doing in this case is a policy innovation, if you like.
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3:33 - 3:36We are innovating by opening up information.
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3:37 - 3:39So just take the obvious example, government,
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3:39 - 3:41as I said, often the innovator.
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3:41 - 3:43In the last -- 3 years ago, you go back 3 years,
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3:43 - 3:46there's almost no open government data initiatives
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3:46 - 3:47in the world.
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3:47 - 3:48Today there are dozens.
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3:48 - 3:51The UK, the US, Finland, Kenya, The Netherlands,
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3:51 - 3:53and there's new ones almost every week.
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3:53 - 3:57There's been a launch of an official kind of movement as a part of the UN
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3:57 - 4:00called the Open Government Partnership in which countries sign up,
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4:00 - 4:02and among other things, they open up their data.
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4:03 - 4:05And of course, it's been, in the UK and other countries,
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4:05 - 4:07Tim Berners-Lee has been involved.
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4:07 - 4:09I've helped advise the government around this in the UK.
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4:09 - 4:11But it's not just government, it's also companies.
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4:12 - 4:14Companies are opening up data.
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4:14 - 4:16Very interestingly, last year,
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4:16 - 4:19Nike started an open data initiative there
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4:19 - 4:21to open up supply chain and sustainability data,
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4:21 - 4:24for themselves and also for their suppliers,
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4:24 - 4:27which I think is a very interesting change.
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4:27 - 4:28And it's also communities.
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4:28 - 4:30Often, in fact, back there in the beginning,
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4:30 - 4:32this incredible map that you saw in an earlier slide,
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4:32 - 4:35is a OpenStreetMap activity, around the world.
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4:35 - 4:38People adding to this crowd-built map of the world.
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4:38 - 4:41And in the last 6 years, OpenStreetMap,
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4:41 - 4:42from a bottom-up community,
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4:42 - 4:44have built a complete, comprehensive,
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4:44 - 4:48map of the world, of fully open data.
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4:49 - 4:51So I've just gone on about Open Data,
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4:51 - 4:53and one thing I'm aware of, of this audience,
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4:53 - 4:54is you might not all know what it is.
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4:54 - 4:59So I'm going to take a brief moment, a brief moment, to say what it is.
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4:59 - 5:01What does it mean when I say 'open'?
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5:01 - 5:06And was it, you know, what's different from anything else? What's different from simply public data?
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5:06 - 5:07So there's actually a definition,
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5:07 - 5:10a definition we the Open Knowledge Foundation helped write, it's very simple.
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5:10 - 5:14In a nutshell, a piece of information, a piece of data,
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5:14 - 5:18is open if anyone is free to use, reuse,
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5:18 - 5:21and redistribute it, subject only at most
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5:21 - 5:23to a requirement to attribute and share alike.
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5:23 - 5:26And anyone means anyone!
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5:26 - 5:28It doesn't mean -- there can't be any commercial restrictions.
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5:28 - 5:32You can't say: hey, here's this data, but only people using it for non-commercial purposes.
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5:32 - 5:35Or only people working in education.
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5:35 - 5:38Or only people living in the developing world, or the developed world.
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5:38 - 5:41There can't be any restrictions like that.
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5:41 - 5:43And there's a reason for this, by the way,
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5:43 - 5:49and it isn't just because one's obsessed about if you like, trademarking an attractive term.
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5:49 - 5:51It's because it's about interoperability.
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5:51 - 5:55One of my experiences at this conference, which I remember from previous trips to Geneva,
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5:55 - 5:57is I've been unable to plug in my laptop!
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5:57 - 6:02Even though I have a French adaptor, in fact, these wonderful Swiss plugs here, are, you know,
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6:02 - 6:04these wonderful, small octagonal shape.
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6:04 - 6:05And even with my adaptor I can't plug in.
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6:05 - 6:07Right? And it's called interoperability.
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6:07 - 6:11When we travel around to different countries, our power adaptors don't actually fit in.
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6:11 - 6:13We have to buy something.
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6:13 - 6:17And the point about this definition, and the point about caring about Open Data,
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6:17 - 6:18is, it's about interoperability.
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6:18 - 6:22The dream of Open Data is interoperability.
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6:22 - 6:26Of seamlessly being able to share and interweave information.
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6:28 - 6:32And if every time I get information from two different people I have to consult a lawyer,
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6:32 - 6:35I have to work out whether I'm allowed to do it, whether I'm allowed to put these things together,
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6:35 - 6:38we lose that dream, that dream is shattered.
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6:38 - 6:42And the key point is, this definition, and those conditions, ensure interoperability.
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6:42 - 6:46If you comply with them, we know that any piece of info, of Open Data,
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6:46 - 6:48will work with any other piece of Open Data.
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6:49 - 6:53And also, it's worth saying for a quick moment, what kind of data, and to emphasize a point.
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6:53 - 6:56Just to foreclose those kinds of questions, otherwise I always get asked.
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6:56 - 6:59When we talk about opening up data, in general,
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6:59 - 7:01we're not talking about personal data.
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7:01 - 7:04We're not talking about opening up your private health records
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7:04 - 7:08or opening up your personal tax information.
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7:08 - 7:11We're talking about information that is non-personal in nature.
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7:11 - 7:16And for the government for example: transport, geodata, statistics, electoral, legal.
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7:16 - 7:20Stuff that the UK has, in fact, for example been opening up over the last few years.
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7:20 - 7:23This financial information, on government spending, this information on health outcomes,
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7:23 - 7:29on prescriptions, this information on educational outcomes, this information on the law.
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7:29 - 7:31This information -- statistical information.
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7:31 - 7:33That's the kind of thing that we're talking about.
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7:34 - 7:37Now, I want to say, it's in this story, we have this story of over time.
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7:37 - 7:39But why governments are doing it now?
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7:40 - 7:41And why Open Data?
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7:41 - 7:44So, okay, for thousands of years, governments innovate,
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7:44 - 7:47but why do they innovate at this particular moment and in this way?
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7:47 - 7:52So I want to start here with a quick story, a story of medicine gone wrong.
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7:52 - 7:54It is from a great book by a guy called Stephen Klaidman.
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7:54 - 7:56It's in fact one of the things
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7:56 - 7:58that made me think quite deeply about this:
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7:58 - 8:00why I was interested in Open Data.
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8:01 - 8:03In that picture there, you can see
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8:03 - 8:06what was the Redding Medical Centre in Northern California.
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8:06 - 8:10There, in 2002, in the Summer of 2002, John Corapi,
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8:11 - 8:12in typical American style,
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8:12 - 8:15an ex-accountant from Vegas turned Catholic priest,
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8:15 - 8:17[scattered laughter]
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8:18 - 8:22...arrived at the Redding Medical Centre having been referred by his doctor for having chest pains.
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8:23 - 8:28He had a cardiogram by the local cardiologist and was told that he needed an immediate heart bypass,
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8:28 - 8:31that he was at serious risk, and that he should come back later that day,
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8:31 - 8:35or at the latest, tomorrow, to have open heart surgery.
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8:36 - 8:38Rather shocked, and dazed by this news,
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8:38 - 8:41he returned home to pack his bags in order to return to hospital.
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8:41 - 8:45He called up his best friend, who was still an accountant in Vegas,
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8:46 - 8:53whose partner was a hospital nurse, and who advised him that he should get a second opinion,
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8:53 - 8:56that, according to his partner, it was not, you know,
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8:56 - 8:59it was very unusual that you would need to have immediate open heart surgery,
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8:59 - 9:00and that he should get a second opinion.
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9:01 - 9:05Rather doubtful about this, because he was extremely worried, he did get on a plane.
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9:05 - 9:08He went to Vegas, he got seen by another specialist...
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9:08 - 9:12who, to his complete surprise, told him there was nothing wrong with his heart.
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9:13 - 9:15He saw another specialist, just to make sure.
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9:15 - 9:19They told him also, there was nothing wrong with his heart.
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9:19 - 9:25Relieved, and rather, you know, happy, he returned home and just wanted to really forget about it.
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9:25 - 9:27But his friend said: "No, what's going on here? Something's wrong".
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9:27 - 9:33And they went in to see the CEO of the Tenet Healthcare, the people running this hospital
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9:33 - 9:36(which, by the way, was a private hospital), and said:
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9:36 - 9:39"Look, something's wrong, what's going on, what are you going to do about this?"
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9:39 - 9:40And basically they were told: not very much.
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9:40 - 9:45You know, mistakes get made, it's bad luck, don't worry about it,
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9:45 - 9:46we'll look into it, but thank you very much.
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9:47 - 9:52They weren't convinced by this, and eventually they decided to contact the FBI.
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9:52 - 9:54The reason they contacted the FBI, by the way,
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9:54 - 9:56is it's a private healthcare provider in the United States,
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9:56 - 10:00they provide Medicare provision of healthcare to the Federal Government.
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10:00 - 10:04So, if the Federal Government is getting defrauded, the FBI can get involved.
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10:05 - 10:07The FBI started investigating.
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10:08 - 10:12Eventually it turned out, that hundreds, probably thousands of people
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10:12 - 10:16over a ten or longer year period, had been operated on unnecessarily.
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10:17 - 10:20Most of them had had serious procedures performed on them,
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10:20 - 10:22open heart surgery, some had died as a result.
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10:22 - 10:24Obviously it's quite a serious operation.
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10:24 - 10:27Some people had basically been condemned to a lifetime of pain.
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10:27 - 10:31One of the most traumatic examples was a 36-year-old, he had been cut open,
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10:31 - 10:33which is obviously what happens in open heart surgery,
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10:33 - 10:35and his chest had never knitted back together correctly.
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10:36 - 10:38Basically, he would be in pain for the rest of his life.
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10:39 - 10:43So, hundreds, thousands of people had been harmed.
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10:44 - 10:46One of the interesting things was that in this community
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10:46 - 10:48there was already some suspicion, there were anecdotes.
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10:48 - 10:51I mean, one of the ones I really liked from this book was the story that went:
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10:51 - 10:56'Don't get a flat tyre outside of Redding Medical Centre because you'll end up with a heart bypass.'
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10:56 - 10:57[scattered laughter]
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10:57 - 11:00You know, but the thing was, there was no data.
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11:01 - 11:05People were you know, a bit suspicious, but it was among doctors who knew,
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11:05 - 11:07you know, in the community, and who wants to doubt it.
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11:07 - 11:12And guess what? Also, Redding Medical Centre had one of the best mortality rates,
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11:13 - 11:15for cardiac procedures in the United States,
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11:15 - 11:20because if you operate on healthy people, you have a good mortality rate!
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11:20 - 11:21[scattered laughter]
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11:21 - 11:23So, the other thing, though,
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11:23 - 11:25and this is the point that comes to Open Data for me
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11:25 - 11:29the other red flag if you had been looking at the data,
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11:29 - 11:32was these two things: one is incredibly low mortality rate,
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11:32 - 11:35and (B) that it had almost the highest number of procedures
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11:35 - 11:37for the population that it covered in the United States,
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11:38 - 11:40which should be a red flag, right?
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11:40 - 11:43Because, one, it's just a massive outlier on that basis, and also,
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11:43 - 11:46the more people you should be operating on, the more you're doing marginal cases,
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11:46 - 11:49the higher should be your mortality rate unless something very odd is going on.
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11:50 - 11:53The thought was: what if people had been looking at this data?
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11:53 - 11:56What if we'd - if this data had been open and public,
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11:56 - 12:00and not maybe just for particular researchers to look at or the government?
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12:00 - 12:04And it kind of reminded me of a phrase that's very famous in Open Source software, which is:
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12:04 - 12:06"To many eyes, all bugs are shallow".
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12:06 - 12:11What's great about Open Source software is lots of people can look at it, lots of people can fix it.
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12:11 - 12:15And for me, what this was saying was: to many eyes, all anomalies are noticeable.
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12:15 - 12:17It's somewhat of an exaggeration,
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12:17 - 12:19but what happens if rather than ten or twenty people
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12:19 - 12:22who worked in monitoring Medicare provision in the US government,
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12:22 - 12:24we'd had thousands or millions of people?
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12:24 - 12:27If the local journalists or citizens, who had suspicions,
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12:27 - 12:29had been able to go and look at that data and say:
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12:29 - 12:32"Whoa! What's going on here? This isn't just anecdotes, there's some data".
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12:34 - 12:40And so, and it's not just then, about kind of spotting healthcare errors, or issues, or risks,
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12:40 - 12:42it's also about things like apps and services
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12:42 - 12:44that you can build with Open Data.
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12:44 - 12:47This is a great app built by mySociety in the UK,
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12:47 - 12:48called Mapumental.
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12:48 - 12:49And the question is, I don't know if people know,
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12:49 - 12:51London house prices are very expensive,
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12:51 - 12:53I don't know whether they rival Geneva's,
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12:53 - 12:55but they're, it's a pretty difficult thing.
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12:55 - 12:58And one of the questions was, if I have to work somewhere,
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12:58 - 13:02and I want to know where I can live, and afford,
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13:02 - 13:06and I can commute to work in a certain time, and it's not too ugly,
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13:06 - 13:08this is what this app does.
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13:08 - 13:11You can choose the price, you can say where you're going to work,
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13:11 - 13:14you can choose the commute time, and you can choose the scenicness.
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13:14 - 13:17And it will show you, on this map, where you can live.
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13:18 - 13:21Another example, more about transparency,
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13:21 - 13:23is a project we did called "Where Does My Money Go?".
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13:24 - 13:25It's an interactive version,
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13:25 - 13:26you can kind of draw it out,
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13:26 - 13:29so what it starts with, is one, is it tells you what your tax is,
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13:29 - 13:31something that most people often don't know,
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13:31 - 13:34and it will tell you how much you're paying each day
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13:34 - 13:36to a particular area of society.
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13:36 - 13:37And the dream for me,
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13:37 - 13:39a dream that we're on the way to realising,
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13:39 - 13:43is in this visualisation, you can drill down into areas.
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13:43 - 13:45And my dream is to keep drilling down.
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13:45 - 13:48So depending on what day we have, I want to go down,
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13:48 - 13:50right down through those bubbles, step by step,
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13:50 - 13:52until I see the money spent on street lights on my street,
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13:52 - 13:55on filling in potholes, on collecting my rubbish.
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13:56 - 13:57And for two reasons:
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13:57 - 14:00One, obviously there's a question, particularly in some countries,
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14:00 - 14:01of inefficiency or corruption,
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14:01 - 14:05but also, just because most of us don't feel very happy about paying tax.
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14:06 - 14:08It's not one of those things people welcome!
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14:08 - 14:10But it's something that we should.
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14:10 - 14:12Government does an awful lot for us,
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14:12 - 14:14and having a better sense of where it's going
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14:14 - 14:17could make us feel an awful lot better about paying that tax.
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14:17 - 14:19In the way that when we go to a restaurant,
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14:19 - 14:21we don't, when we get the bill, we don't necessarily feel bad.
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14:21 - 14:24We feel "Wow, I had a great meal. That was worth it."
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14:25 - 14:26But why Open?
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14:26 - 14:29I've given you examples, and you know, we see a lot of apps and services.
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14:29 - 14:31Why is Open relevant here?
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14:32 - 14:36This goes back to what I said about the information technology, the revolution.
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14:36 - 14:38So it's the challenge and the opportunity.
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14:38 - 14:42It's the challenge that we see today, is exploding informational complexity.
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14:43 - 14:44I mean, another great story:
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14:44 - 14:48in the 1820s, all bank clearing in the largest financial centre in the world
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14:48 - 14:52was done in a single room, where people -- one person from each bank gathered
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14:52 - 14:56and they'd go round the room pulling out gold, and swapping it around, between different banks.
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14:56 - 14:58And that's how they did bank clearing.
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14:59 - 15:02Today we have billions of transactions a minute.
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15:02 - 15:08And the way we as humans deal with complexity is by dividing and conquering it.
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15:08 - 15:11We split it up into manageable chunks that we deal with.
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15:11 - 15:12The other answer,
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15:12 - 15:15and this answer's particularly relevant about Open Data,
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15:15 - 15:16is information technology.
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15:16 - 15:19Today, a smartphone has as much computing power
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15:19 - 15:22as the system that ran the Apollo moon landings.
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15:22 - 15:24And an even better example is storage:
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15:24 - 15:27one terabyte of storage today is a hundred dollars.
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15:27 - 15:30In 1994, this would have cost 400,000 dollars.
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15:30 - 15:34I can have every financial transaction
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15:34 - 15:38the UK government, or the US government made last year, or even for the last decade,
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15:38 - 15:40on my laptop.
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15:40 - 15:44That was not possible for an average citizen a decade ago.
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15:44 - 15:48So it's mass participation, information access, processing, and production.
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15:48 - 15:50It's decentralisation.
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15:50 - 15:52And the claim here is that openness is key.
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15:52 - 15:54It's because it's about scaling.
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15:55 - 15:57What we are doing is weaving data together.
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15:57 - 16:00As I said, we deal with complexity by splitting it up.
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16:00 - 16:03We componentise, we split data up into blocks
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16:03 - 16:05that we recombine.
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16:05 - 16:07But if we are going to recombine information,
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16:08 - 16:10we need to put Humpty Dumpty back together again,
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16:10 - 16:13it won't work most of the time if it is closed.
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16:13 - 16:17We need Open Data to scale and to componentise.
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16:18 - 16:22And it's a point just to make here in this respect, that you might think:
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16:22 - 16:23"Well you know, you're talking about Open Data,
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16:23 - 16:25you know, this could be true of anything!
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16:25 - 16:26Why don't we have like,
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16:26 - 16:28Open Cars, and Open Shoes, and you know,
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16:28 - 16:30why don't we just share everything, man!
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16:30 - 16:31It would be so beautiful!".
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16:32 - 16:33Right? And the sad thing is,
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16:33 - 16:39is that that hasn't generally worked as a way of organising most production in our society.
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16:39 - 16:44Instead, we have private property, and so we don't do that much openness relatively.
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16:44 - 16:46But there's something different about digital information.
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16:46 - 16:49We all know it, but it's worth emphasising, which is, it's very cheaply copied.
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16:49 - 16:53I mean, give me a copy of your data isn't a problem if you're the government.
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16:53 - 16:56Give me a copy of your car, or your house, or whatever, is.
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16:57 - 16:59And it's also about innovation here.
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16:59 - 17:01I mean, in a way it's almost the purest aspect of markets.
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17:01 - 17:06Markets are about moving things to the person who could use them most best.
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17:06 - 17:07And that's true of data.
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17:07 - 17:11The best thing to do with your data will likely be thought of by someone else.
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17:11 - 17:15And vice versa! You will think of the best thing to do with someone else's data.
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17:16 - 17:20And Open Data allows us, in the most frictionless, easiest way,
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17:20 - 17:23to move data to where it can be most optimally used,
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17:23 - 17:24particularly if you're government.
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17:24 - 17:27So in short, it's about better understanding, it's about better government,
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17:27 - 17:29it's about better research, it's about better economy.
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17:29 - 17:31And something also for companies and governments:
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17:31 - 17:33I think it's about better engagement.
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17:33 - 17:35It's about a closer relationship, sometimes,
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17:35 - 17:37between your citizens and you as the government.
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17:37 - 17:41Between you, even possibly, as a company, and your users.
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17:42 - 17:44So I wanted to kind of finish here by saying where we're going.
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17:44 - 17:46The story was, of this talk, was, you know, where are we?
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17:47 - 17:50Why have we got here? And where are we going?
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17:51 - 17:52So one answer is just more use.
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17:52 - 17:55So right now, I just said at the beginning, Open Data is relatively young.
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17:55 - 17:58This vast outpouring, for example, of government data,
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17:58 - 18:02that anyone can freely use, reuse, and redistribute, is really new,
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18:02 - 18:03even if it's done three years ago.
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18:03 - 18:06For example, in the UK, much of the most useful data that could be released
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18:06 - 18:09has only been released in the last six months or a year.
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18:09 - 18:10You want prescription data?
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18:10 - 18:12Are you a pharmaceutical company,
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18:12 - 18:15and you want to know what kind of prescription habits are going on in the UK?
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18:15 - 18:19I would emphasise: at an anonymised or somewhat aggregate level.
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18:19 - 18:21Do you want to know about what crime is going on?
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18:21 - 18:24Are you building a real estate website and you want data on environment,
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18:24 - 18:26or you want data on unemployment,
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18:26 - 18:29or other information about where properties are situated?
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18:29 - 18:30You can now get that.
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18:31 - 18:33So I think there's going to be a lot more use from business.
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18:34 - 18:35There'll be a lot more use from everyone.
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18:35 - 18:39But I think particularly business is going to wake up to the opportunities here.
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18:39 - 18:40I think it's also going to lead to more data.
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18:40 - 18:42One is, government is going to be more data.
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18:42 - 18:46I think also businesses are going to realise, and communities,
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18:46 - 18:48that they want to share back some of that data,
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18:48 - 18:49some of the data they have.
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18:49 - 18:51It's not going to be their kind of crown jewels,
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18:51 - 18:54and it's not going -- often start out with data that's not core to their business.
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18:54 - 18:58It's like. kind of Nike, they realised that by opening and sharing data,
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18:58 - 19:01they can scale in a way they can't on their own.
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19:01 - 19:03And does it mean that richer data, going back
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19:03 - 19:06-- how could I leave out Hegel and Marx in a talk like this --
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19:06 - 19:09"Quantity changes quality" as Hegel told us.
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19:09 - 19:14And more data, going back to that woven ball, more data actually means better data.
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19:14 - 19:18It means richer data, it's a qualitative difference in what we can do.
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19:18 - 19:20Geodata on it's own isn't that useful.
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19:20 - 19:22Transport data on it's own isn't useful.
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19:22 - 19:24Geodata plus transport data is useful!
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19:25 - 19:26And we're going to be seeing data refining.
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19:26 - 19:27Data is the new oil, right?
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19:27 - 19:29So, we're going to refine it.
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19:29 - 19:32And that's going to be a big business: higher quality data.
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19:32 - 19:34I want to leave you with a couple of thoughts.
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19:34 - 19:36So, one is, some people say:
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19:36 - 19:38"Well, okay, but, you know, selling data is big business".
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19:38 - 19:41And it is, but going forward in some of these things like software,
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19:41 - 19:42data is going to be a platform.
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19:42 - 19:44It's not a commodity.
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19:44 - 19:46Businesses built purely on selling data,
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19:46 - 19:48I just don't think are going to make it.
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19:48 - 19:52You need to be building on your data, not attempting to purely sell it.
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19:53 - 19:55And the other answer is to be modest.
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19:55 - 19:57So I said: where are we going?
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19:57 - 19:58I don't know if people know
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19:58 - 20:02-- and this takes us back to an earlier age, an age of electricity and steam -- of Faraday.
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20:02 - 20:05So he's demonstrating electricity at the Royal Society,
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20:05 - 20:08and Gladstone, the future Prime Minister of England, sees him do this stuff, you know,
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20:08 - 20:10the frog legs move, and Gladstone's like:
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20:10 - 20:12"Well, I mean, this is party trick, Faraday.
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20:12 - 20:16It's great, but, what's really, you know, what's electricity going to amount to?" (20:16)
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20:16 - 20:21And Faraday says to him: "Well, what's the use of a baby?"
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20:21 - 20:24You know, a baby when it's young is not very useful.
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20:24 - 20:26[scattered laughter]
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20:26 - 20:27But it grows up into something!
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20:28 - 20:30And that is where we are going today.
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20:30 - 20:32We are the beginning of the Open Data journey.
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20:33 - 20:36And partly is, we don't know what it's going to grow up into.
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20:36 - 20:37Thank you very much!
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20:37 - 20:41[Applause]
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20:41 - 20:45[Questioner] Um, citizens and I guess patients at hospitals,
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20:45 - 20:49assume that the institutions have all this data and it's very well organised,
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20:49 - 20:50and it's a question of will.
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20:51 - 20:54Have you encountered cases in which they simply don't have it,
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20:54 - 20:57or they have it, and it's just such a mess that they're too embarrassed to give it out?
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20:57 - 20:59[Rufus Pollock] Absolutely.
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20:59 - 21:01I mean, one story that kind of intrigues me,
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21:01 - 21:04is we've been building this "Where Does My Money Go?" open spending project.
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21:04 - 21:07And one of the things the government mandated was giving out,
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21:07 - 21:09rather than just high-level financial information,
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21:09 - 21:11giving out information at a detailed level, you know,
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21:11 - 21:13so they now publish, for example,
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21:13 - 21:16spending data from each government department monthly,
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21:16 - 21:18every transaction within 5,000 pounds (check).
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21:18 - 21:22Every purchase they make, every mobile phone provider they contract with, we get that data.
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21:22 - 21:26And one of the intriguing things, of their mandating this, was it turned out,
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21:26 - 21:30before, they had no way, before they did this, of actually seeing, on any regular basis,
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21:30 - 21:31what their department spent money on.
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21:31 - 21:35Because in fact, the only thing they reported up on to, in central government to Treasury,
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21:35 - 21:39was kind of like, how much did you spend against Project X that you were allocated budget for?
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21:39 - 21:41You know, departments, were actually really intrigued, they [say]:
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21:41 - 21:43"Oh, that other department's going with Vodafone,
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21:43 - 21:46and we're with Orange, and look how much they're paying per month!"
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21:46 - 21:49So I think in essence, it is really driving changes in government,
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21:49 - 21:53and yeah, there are people, I think you'd been worried about giving out data quality.
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21:53 - 21:55I was just talking to the Department of Education last week and they said
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21:55 - 21:58-- you know, one of the things -- they had financial information from schools,
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21:58 - 22:00and which they were slowly being mandated to publish.
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22:00 - 22:01And schools are suddenly all ringing up, saying:
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22:01 - 22:04"Well we never really bothered to really update that information to be accurate!
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22:04 - 22:06Uh, we really want to do it right now".
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22:06 - 22:08So I think that definitely does happen, yep.
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22:08 - 22:12[Questioner] Are you seeing now new roles in government, to help facilitate this?
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22:13 - 22:16[Rufus Pollock] Yeah. I mean, to take another example, I, sorry.
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22:16 - 22:19Both in government, so the UK government has a transparency kind of 'czar' if you like.
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22:19 - 22:23Also I learnt, is Nike hired an Open Data evangelist.
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22:23 - 22:25One of the things they, while they were implementing this programme,
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22:25 - 22:28they actually hired explicitly, an Open Data evangelist.
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22:28 - 22:30So yeah, I think we are, we're definitely seeing this in government.
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22:30 - 22:32Both in the tech level, but also at the policy level.
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22:32 - 22:35And I think it's not just government,
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22:35 - 22:38it will also be companies doing this, and so on, who will be saying:
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22:38 - 22:39"We need an Open Data expert.
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22:39 - 22:44We need to be aware of what's going on here and be able to plan it as part of our strategy."
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22:44 - 22:45[Questioner] A final question.
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22:45 - 22:49You mentioned that, kind of outsourcing, almost, some of this data refining,
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22:49 - 22:51outside government or the big institutions, has helped them.
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22:51 - 22:54Can you tell us any stories of kind of gratitude being expressed by the government? I mean...
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22:55 - 22:57[Rufus Pollock] Well, I mean, to kind of, yeah.
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22:57 - 22:59I mean there was an interesting example actually
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22:59 - 23:02where we had some complaint because the open spending data I told you about
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23:02 - 23:05where we're aggregating the government spending and financial data
-
23:05 - 23:11-- you know, the site had a few performance issues, occasionally, as we loaded more data in.
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23:11 - 23:13I remember kind of getting this call kind of going :
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23:13 - 23:16"Well, you know, we're a little bit upset, you know, data.gov.uk,"
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23:16 - 23:19and it turned out the reason was, the Treasury kept looking at this data,
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23:19 - 23:21and they were annoyed when the site was going down.
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23:21 - 23:23So that was really intriguing to me
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23:23 - 23:26that we were kind of one of the best, at least, up-to-date aggregators out there.
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23:26 - 23:29Um, I think you are already seeing people doing stuff with the data
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23:29 - 23:31and kind of doing stuff, sometimes for free, you know.
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23:31 - 23:33You don't have to have the shiny front-end.
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23:33 - 23:35I mean, one of the things we went about, on about,
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23:35 - 23:36I know Tim Berners-Lee went on about --
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23:36 - 23:41raw data now, you know, you can build fewer shiny front-ends, and just release raw data.
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23:41 - 23:46And you know, someone else will help you build the app, the front-end, the interface,
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23:46 - 23:48and help you innovate about it.
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23:48 - 23:51What is the best way to provide healthcare data to citizens,
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23:51 - 23:52or education data to citizens,
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23:52 - 23:54so they make better and more informed choices?
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23:54 - 23:57I don't know, and the government probably doesn't know.
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23:57 - 23:59But somewhere out there, someone is going to innovate
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23:59 - 24:03and really provide the best way for us to deliver that kind of information to citizens.
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24:03 - 24:04[Questioner] Thank you very much.
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24:04 - 24:05[Rufus Pollock] Thank you.
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24:05 - 24:07[Applause]
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24:07 - 24:09lift _ Video Production ACTUA
-
24:09 - 24:11Copyright (c) 2012 Lift conference
- Title:
- Open Data: How We Got Here, and Where We’re Going
- Description:
-
Rufus Pollock at the Lift 12 conference. More info in http://okfn.org/opendata/ , where the video is embedded.
See also http://blog.okfn.org/2012/04/02/talk-at-lift-2012-open-data-how-we-got-here-and-where-were-going/ , where Rufus Pollock's slides can be downloaded.
- Video Language:
- English
- Team:
Captions Requested
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Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
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Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
![]() |
Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
![]() |
Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
![]() |
Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
![]() |
Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
![]() |
Claude Almansi edited English, British subtitles for Open Data: How We Got Here, and Where We’re Going | |
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Claude Almansi commented on English, British subtitles for Open Data: How We Got Here, and Where We’re Going |
Claude Almansi
These are Argus' "English" subtitles, reuploaded in revision 1. I'm using this "English, British" track to try and split some of his longer ones when they hide a slide shown on the video. Not finished yet.