Stijn DeBrouwere: Information Architecture for News
We’re not using the implicit structure of news articles to inform the readers.

Burt Herman – Hacking the News
Applying computer science to journalism
Https://hackshackers.com

The story as data.

Standard in computer science: Object-oriented programming and model-view-controller (MVC), but how to apply it to a story? Dissect the story: headline, lede, quote, background, analysis – standard news items. Storify is a new service that pulls in different elements from social media to tell stories. Giving tools to curators to pull together social media bits to tell a story. Pingback the user they are in a story. MVC is used to plot the elements in different views, or on a timeline. A new type of journalism, geekily called: Object oriented journalism in contrast to standard content management systems that focus on flat text.

Ultra Knowledge
TweetWall, also shows chronological view of an event on Twitter, instead of the reverse-chronological view that a search will serve you.
NewsWall, the iconic way to browse the news.
Critique from New York Times: Flattening of editorial decision making

Julian Burgess – Moving towards realtime
MrDoob
Etherpad (Google Wave like, bought by Google but still available as source code)
PubSubHubbub
Getclicky
Woopra
3wise-solutions
Chartbeat

Algorithmic page optimisation
Google News
Feedafever
Flipboard

Cynthia O’Murchu (Investigative Reporter), The Financial Times  
 
The era of the innumerate journalist is over. Is the era of technology-averse journalist also heading to a close? WikiLeaks, Scraperwiki, Theyworkforyou.org and other organisations advocating transparancy. But (how) will journalists and media handle it?

Rhetoric versus reality: Open government … But data is not always prsented in a user-friendly way. Eg Register of Member’s financial interest: locked down (PDF). Nor do governments always really want to release it.

“CAR (computer assisted reporting) is the use of computers and social science methods to acquire and analyze information to do stories that otherwise would be difficult or impossible” – Steve Doig

Telling Stories With Data
Alan McLean (Designer and Interaction Developer), The New York Times

Interactive news technology. New relationship between developers and journalists. Use the web to tell a story, not just as a delivery medium. Syndication does not really honor the content really well.

Data dumps: Large collections of source material thatat aim to inform, but ultimately over-saturate.
- fail to inform clearly
- it’s very easy to get lost
- they take up preciosu time
- low impact
- pretty bland

It’s far too easy to distract or confuse an already compromised online attention span, editing is crucial online.

Van Ham was part of the IBM team who developed and created Many Eyes. 

Data visualization is the use of: computer-supported, interactive, visual representations of data (to “amplify cognition”). 

“Cognition amplificators”
Any representation technique that allows you to distort the truth is a medium. Data visualization as such is a medium and people have used it for propaganda, expression of self, art and communication of complex issues. 

Uses for data visualization in journalism are two-fold: explorative, transforming data into information. Communicative, transforming a story into a medium.

Data > information nuggets > story > representation of the story > consumption.

Transforming data into information, possible issues: messy data (government pdfs anyone?) data format and scale, which tools?, tiime constraints, structures (tables) vs unstructured formats (text).

Tag clouds: Analysis method maps directly to the presentation method.

Some insights for explorative data visualization
On data formats: from interview with data professional. Q: Do you need support for XML? a: What is XML?
Preferred: Tab delimited format. Copy and paste from Excel. The most important data interface in practice is that your tools allow easy copy and paste from and to Excel.

Transforming a story into an interactive medium. Print media already have a lot of experience in infographics. Possible issues: complexity of coding, exposing the data source, linking to other visualizations, to what extent do you want to take users by the hand when exploring, discussion and commentary.

On fostering discussion around visualization: allowing users to find and bookmark data points within the visualization is a great way to get them to interact. Combine structured view with free-range exploring. Integration with other technologies: sharing of visualizations is so much easier if you can just mail or Tweet a URL to a specific view.

Session 1: Data Production, Usage and Integration

The Guardian was collecting data all the time, not doing anything with it. So we set up a blog (Guardian Data Blog) and we thought people who would be using this blog would be developers. However, “real people” want the data, not only developers. Putting raw data on the blog, putting it out as a Google Spreadsheet, easy for people to download, and high traffic friendly. Using known tools, such as ManyEyes (quick and easy). What we try and do is engage the public, journalists used to be people who used to create stories, but it is now a mutualized process. Eg, there is a Flickr group where people post visualizations. Invite the public to participate: Investigate your MP’s expenses. Ask the people to help review/classify the expenses, crowdsourcing the investigative work. We want to be a source for data and information. Most popular dataset: Dr Who.

Session 1: Data Production, Usage and Integration

Showing the partisanship or issue commitment of an actor. Tool is named after Walter Lippmann. In “A Test of the News” he argues that publics don’t exist, but publics need to be created through tools, eg by being polled. He proposed a series of tools, one of which we tried to address in The Lippmannian Device tool.

First use scenario: Querying sources for actors (built on top of Google). The output are source clouds. Example project: Climate Change Sceptics. Sceptic friendly sources and watchdogs. Which sources mention which individual names?

Second use scenario: An organization’s issue agenda (or commitment). The output are issue clouds. Example project 1: NGO, Public Knowledge. 2: Greenpeace issues taken from their website. What is Greenpeace’s issue agenda?

Third use scenario: multiple sources, multiple issues. what is the agenda of a human rights organizations? Take three good lists of human rights organizations (global south, global north, UN). Triangulate lists. Scraped all websites for all their issues. Top box: all URLs of the websites, bottom: all issues. The tool is actually batch querying Google.
Bottom of the tagcloud, which issues a neglected by the human rights organizations?

Italian journalists who were doing critical reporting used the tool. Impression: the same experts on tv, no matter what the issue is. Use the tool to verify that indeed actors are affliliating with multiple issues. 

Session 1: Data Production, Usage and Integration

Background: Builds political applications so citizens can understand what their government is doing. One of the founders of the open data network in Germany.

- access to or production of structured datasets
- provide raw data dor the users alogn with the story: as a spreadsheet, and/or interactive environment (eg map-mashup with a timeslide and filters). Provide the reader with a research environment.

The Wikileaks Warlogs were a wakeup call for DDJ in Germany.

OpenGov data is a subsection of open data but there is no OpenGov initiative in Germany like data.gov. The data available is not very detailed and not in a machine readable format. OpenData in Germany is happing from bottom-up: several groups and people are working on gathering (scraping) data from government sites and developing applications. There is an evolving ecosystem of citizen apps, eg:
OpenBudget offener-haushalt.de
OpenParliament openbundestag.de
Lobbyregister lobbypedia.de

We can use this ecosystem as weatherstations or seismographs:
Measuring political temperature, pressure, etc.
Journalists could find stories in the data and usage of this application
Newspapers/media should sponsor or develop apps like this for reader/user environment as a watchdog position.