News you can't print - Journalism beyond the article
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Sound effectTraffic reportingComputer animation
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Computer programVideoconferencingIRIS-TInformationPlane (geometry)MassWindowLine (geometry)Menu (computing)Video GenieOrder (biology)Computer architectureSelf-organizationContext awarenessElectronic mailing listEvent horizonBitContent (media)Web pageVector spaceExtreme programmingSound effectComputer animation
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Content (media)Cartesian coordinate systemGroup actionMultiplication sign
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Inclusion mapMetropolitan area networkDatabaseHome pageDifferent (Kate Ryan album)WebsiteComputer animation
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InformationCodeRootInternet forumINTEGRALContext awarenessSource codeComputing platformSystem callCodeForm (programming)Meeting/Interview
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Transcript: English(auto-generated)
00:14
Hello, and we stick to the subject of the change of journalism in digital times. After investigation 2.0, we are going
00:22
to listen to News You Can't Print. And we have two people from the Night Mozilla Open News program, which is Annabel Church, who is with the program at Cite Online. And we have Friedrich Littenberg, who is with Night Mozilla Open News program at Spiegel DE.
00:42
And they will show us what else you can do in journalism than only writing articles, maybe using databases, visualization. Anyway, have fun.
01:02
I'm Annabel. This is Friedrich, in case you got us mixed up. We thought that maybe we could do a small, intimate conversation about News You Can't Print. Maybe a little bit of a workshop? Maybe, sorry. We thought maybe we could do a bit of a workshop,
01:21
a little intimate workshop. But there's a few more of you than we expected, and we've only got 30 minutes. So we thought we'd do a presentation instead, OK? So this is News You Can't Print. We thought we would have a little hashtag in case you could answer some of the questions along the way.
01:42
So we are Night Mozilla Fellows. We are part of an open news program, which embeds technologists inside newsrooms. There are eight of us this year, and we are kind of all over the place. Some of us are in America, some of us in Germany. Got a few in the UK.
02:02
Yeah, we're everywhere. We're invading the newsrooms. My newsroom that I'm embedded in this year is Zeit online, and Friedrich's is Spiegel online. And we're collaborating on this together. So the things that we have come to understand about our tricks around the newsroom
02:20
so far is that we're still figuring this out. We're still adapting. So we were in the Boston Globe down in the picture archive, which is where one of our fellows took this photo, cut up articles and photos of everything they had
02:42
since the dawn of time. This is the old way. So it prompts a discussion about what an article is. An article is no longer a thing that we can cut up and put in a folder and reference by keywords
03:00
in the basement of an organization. It is a kind of a new thing that can be online. And I'm not really sure what it tells us. It tells us a headline and some context and perhaps the description of a singular event. But it doesn't necessarily tell us what the story is.
03:24
So what is the story? A story is a collection of events under a singular narrative. And we might want to move beyond the article as a kind of descriptor for what that story is.
03:42
The pieces of content that we can produce around this narrative could be video or live blogging or article. It could be a print magazine article or it could be online, on your iPad, on your iPhone. So we want to talk about what it means
04:02
to go beyond the article in terms of the story. So we all know snowfall, article plus plus, yeah. So it's the next thing. It's got a bit of extra description about the key players and the places. It's got a bit of elongated,
04:22
elongated storytelling. It is a feature. They're not the only people to do it though. This kind of explorative storytelling happens outside of the newsroom.
04:43
Airbnb Annual do this kind of narrative storytelling, including some of the parallax effect on their annual report. They bring in stories from their users and create a narrative around what has happened that year.
05:02
So clearly the solution is the parallax effect, right? There are other things about what is a story. What you need in order to create that story and explain that story to your readership or in your audience. You need key people.
05:21
You need to explain the context of the people that are inside that story. And you need to know where that story is taking place. You need to know how it's relevant to you and what you're gonna do with it. So we know that BBC here have a lot of context on their story, a lot of summary,
05:44
extra events underneath their articles. So we've explained a little bit about what a story is and how it's not just the article. It is about context and relationships. And it's about ongoing events
06:00
and the place that you wanna be reading inside those events. Where are you up to in the context of that story? There are a lot of intermediate solutions so far. We have tag pages where you can see a list of all of the articles that have ever been written, maybe all of the content if your news organization produces more than just the article.
06:21
And you can see that Google also produces a kind of aggregated story. So once you've decided what extra pieces around your article you can display in order to explain your story,
06:40
it just leaves the body of the article. How do we represent that as an ongoing narrative? So Lux is a way of showing you the evolving body of your article.
07:06
The only way to distribute this kind of news, this kind of story architecture is by re-imagining news architecture.
07:21
So one of the groups of people who've been doing this is NPR. They have this beautiful idea of create once, publish anywhere. They create small pieces of content that describe their story. And they publish that out on their API. And any application that kind of consumes this
07:43
can get an idea of how that story is evolving in the medium for which their readers are reading that. So if I want to talk about NPR content on my phone, they will look very different from the NPR content on a website, on an iPad, and anywhere else.
08:08
Okay, so I mean we've looked a bit at how basically we may consider taking apart articles, taking this notion of having a stream of text that was useful in print and turning it into a more kind of modularized
08:23
and granularized set of items of content, right? And what I think is interesting about that is that it means that we can no longer only include bits of content that come from our own organization that we have produced ourselves, but of course also that we can take external pieces of content. And there's two parts in particular
08:42
that I think are worth looking at. One source of content, of course, and it's very established by now, I think is kind of user-generated content, starting with the comment boxes on your page, but going up to kind of sifting through all the social media reaction that happen outside of your news environment
09:02
and in the wild, kind of in Facebook and Twitter and Google Plus and whatever other media there are. And I think it's interesting to look at how we can consider new sources of content from this kind of social realm, and I'm gonna talk about the less social realm a bit afterwards. So for example, this is something that The Guardian has developed where basically they now have a platform
09:22
that's reusable for letting people contribute pictures and media to a particular topic. So basically the people themselves kind of bring together the pieces that they think need to be in the story. What's interesting, of course, is that I've picked out the one about election leaflets, where they collect what kind of propaganda
09:41
is being published by different actors, which is kind of interesting to look at. Is this kind of different by geography? Is it different by social demographic kind of criteria of the area where it's being distributed, all that kind of questions. But of course, the most popular category on that side is food. So you send in pictures of your food,
10:01
and you win a prize if you got the best food, which I think you have won already. Another kind of more, maybe a highbrow attempt at doing this is probably what The Economist does. They have one debate a week. In this debate, they try to really get the pro side and the con side to lay out their arguments, to make clear what their case is in each case,
10:21
and then have the public make their own comments, but also give a voting that's ongoing, that's proceeding, to kind of both give a general sentiment and introduce new points to the debate. And I think this is really interesting, and it's also, I think, an example for kind of taking your audience very seriously. And I guess that's the kind of interaction there, where basically it's between how serious you take your audience
10:41
and how serious your audience takes you. So that's on the feedback. What I want to talk a bit more about is this idea of information icebergs. For that, maybe a bit on my background, I used to mainly build data sites, so sites that take public information of some kind
11:02
and make it more accessible, more available on the web. Some examples here, often as parliament tries to take data that's coming out of the German parliament and make it easier for you to track what's happening in parliament. Open spending is basically allowing you to kind of go through public spending and analyze how different countries spend their money,
11:21
what the difference between the budget, the allocated political amounts, and the actual spending in individual transactions is. All this kind of really interesting political data, or in the back there, you've got something where we try to get data about the European Union and what kind of lobbying is going on there. So can we find out who is influencing decisions, how they're influencing decisions?
11:40
Of course, all of you know about Lobbyplag, which has done this in a very kind of interesting and informative way as well. So what's the difference really between this and this? What's the difference between what I like doing, which is kind of building these massive databases and what journalism is really about, which is building these narratives, right? Here you've got a piece of text.
12:01
It's almost all narrative. It's really a story that's supposed to be read by humans. And this is a thing that's barely accessible to humans still, right? This is something where, I mean, no news site that would self-respect itself would put a search bar in the middle of its homepage. That's not just not done, right? That's not how you communicate with people. That's how you communicate with databases.
12:23
So how do you make these two things integrate more seamlessly? And why would we want to do that? I've got here two pyramids. One of them, who in the room is a journalist or by any affiliation? Ah, we're all journalists here, aren't we? Fantastic.
12:41
So who in the room, basically, you all know this pyramid here, right? That's the one for news. And this is the one for data, I guess, right? So what I find interesting is basically, you used to have this idea that everything needed to happen in the first one or two or three sentences. But now basically, it's no longer true that we need to have this
13:00
because we can have all the common space we want, right? So the green area here is basically what news organizations are kind of used to publishing. You may have the very up-to-date news, the short article that just explains this and that has happened. This is the ongoing update from the court proceedings in this case. Or the more long-term kind of long-form journalism
13:21
that explains a bit more detail, contextualizes, gives perspective and all this stuff. But of course, there's a lot of stuff below that as well, right? There's your archives. There's what you have that you've published before but that you've kind of forgotten about maybe and that you're not trying to monetize any longer. And even that is still an open discussion over whether that should be on the web
13:42
or whether it should live somewhere else and whether to make it available. And then there's this whole realm of other data that can be found, right? There's more and more data available. If you want to know exactly how good the schools in your country are or in your district or in your city, there is tools to find this.
14:00
There is more and more data out on that. And what I'm trying to argue for here is basically the idea that more journalists should start looking at building these databases. That basically, if you have a database, you have an ongoing source of stories, you have an ongoing source of narratives, and that you still are required to build this bridge from here,
14:21
the stuff that's really down in the details, to up there where it turns into something that's easily readable, that's easily digestible, that's easily accessible. But still there are advantages of this because you may want to allow people to climb down the chain. So one thing that people may want to do is to personalize that information, right?
14:41
To find out not only what is the general story for all of Germany, for all of Europe, but to find out what is the story for me? How does this affect me in practice? Another thing that you may want to do is to allow people who are freaks for some topic, who are just interested in some topic, to find that information that they're really interested in, right?
15:01
I mean, the old assumption about news organizations is that they need to cater to a mainstream audience, that they need to cater to everyone. And that's still true to some extent, but you can also allow yourself to cater to more specific audiences if you can automate the process of getting at the information that's lower down here more. And the final thing is that having this data,
15:22
having it in an understood form, being the maintainer of a database may actually be something that's even more profitable than journalism. There are some organizations that already kind of base their business models of this, such as Bloomberg or Reuters, who are mainly based on keeping databases. And then the journalism that's on top almost becomes the advertising for the underlying database.
15:44
And I think that in many senses, you can develop that as a model where basically the journalism you release is really a showcase for how good the information you have is. And then you can think about whether you can monetize that information. And by the way, for that, you need public open data.
16:04
So for some examples of this, this one is the classical example. I don't know how many people here are familiar with ProPublica and their work. Not that many, okay. So ProPublica is a nonprofit organization. They're not a news organization in a traditional sense,
16:22
in that most of the time when they publish stories, they don't publish them on their own pages. They publish them together with another newspaper, with another news organization. What they do is they have a fantastic team of coders and investigative journalists, and they do long investigations into particular databases, into particular news sources.
16:42
And in this example, for example, they took data about nursing homes and brought it together so that not only can you get a picture of how nursing homes are in terms of quality across the entirety of the United States, but you can also then go down, enter your own zip code, and find out what grandma's nursing home is like, right?
17:01
This is why I wish I could scroll right now, but it doesn't work. So this has both levels. It has kind of the general narrative, and it has this layer below where it really affects me, where it really concerns me. A similar thing here. They basically just took this very kind of real-time information about the disaster recovery efforts
17:21
that happened after the hurricane last year, I think in November, September, November, October, around Hurricane Sandy, where basically a lot of property and places were destroyed in the US, and they very quickly went in there and found out what the FEMA was financing in terms of repairs. And that's a fantastic database, right?
17:41
Because number one, you can find out exactly what stuff is already being repaired in my town, so it's good stuff for that, but also you may be able to find misallocation in some cases. An even more interesting example is the Texas Tribune. How many people here are familiar with them?
18:00
Not that many. Basically, they used to be, hey, they used to be a normal news organization, but now they've basically died and been reborn as something that basically tries to get databases about Texas. So their core business almost is trying to get these different databases and having them in a great format, having them running well for them, and then they do investigative work based on top of that,
18:22
and they really make that into an art form. So that would be the example. There's, of course, a fantastic example from Germany also. This is like the flight radar for Berlin, where basically you can type in exactly where you live, and then you'll see how many flights
18:41
are passing above my house today, what kind of noise level do I have to expect? But of course, it's not just personal information. It also goes back up again to this level where you want to ask, okay, what kind of flight routes are okay? What is really the impact of opening this new airport? How does the new flight routes compare to the old flight routes in terms of how many people they affect
19:01
and what kind of pollution they cause? So I think these are really nice examples of using basically the vast amount of public data that's available and making it into a foundation that has value of itself, but then can also be used as a foundation for reporting in more and more interesting ways.
19:21
And the best part about it, it can all happen out in the web where it's accessible to everyone, and people can really find out more for themselves. So that's already the quick intro we wanted to give you. Some more information if you want to find out more, there's a discussion space that we have going
19:41
called Source. And we try to bring together people there who are involved in general coding, who are involved in creating code and creating narratives and stories that relate to kind of journalism in some way. And we'd love to invite you to all come there and discuss with us how basically we can have a tighter integration between code and journalism
20:03
so that it's no longer the platform that stands there and then the journalism happens on top, but that there's more kind of roots going between these two things that connect them and that really make them interact in meaningful ways. So that's our context. And if you have any more ideas, basically we can't have this place forever,
20:22
but we're gonna go outside and have a drink and maybe then we can start a debate on how do we kind of take apart the article, how do we get it into a new form so that it becomes an up-to-date document of what's happening that can both give me the latest information and contextual information that I really need. Thank you.