FROM SECTION 1
A new "flavor" of information that reaches a new group of consumers
In the same way that consumers of the arts might prefer painting to poetry, fashion to film, consumers of information find it easier, or more fun, to consumer information of one type vs. another. A long essay on the Arab Spring reaches a different audience than a 90-second news segment on the same topic. The addition of meaningful and substantial data as a ``format'' for information that could also be delivered in other ways reaches a new segment of information consumers.
As a source of new perspectives
Good data journalism allows information consumers to see relationships, proportions and other qualities in ways that other formats do not, and different portrayals of information tell different stories, even with the same data.
As a teaching tool for journalists
In the same way that learning a new language allows a person to begin to make a different set of concepts concrete, learning the skills and tools associated with data journalism improves the thinking of journalists who take the time to do it. The process of adding data journalism to the "toolbox" of the average journalist also forces collaboration with categories of professionals with which journalists are usually not accustomed to working such as developers or designers.
As a forensic tool for readers
Journalists, and news outlets generally, betray their perspective in the data that they choose to present, and how they choose to present it. A discerning reader can see the output as a "tell" of a journalist’s or organization’s political or intellectual disposition.
Redressing the balance of power
"The task of journalism is to hold power to account. The corporate sector and governments have Big Data, and they know more about you than you know about them. Data journalism can help redress the balance of power."
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Mapping LA- Los Angeles Times http://projects.latimes.com/mapping-la/neighborhoods/
What the example is: an interactive map of Los Angeles with: Crime, Schools, and Demographics data from which a Blog post and social media content is produced as data updates are released. http://projects.latimes.com/mapping-la/neighborhoods/ Why you like it: it´s a different way of telling many many stories, almost without words starting from an interactive map and datasets. For eg. Crime LA: focuses on crime detecting different zones of risk of categorized crimes: http://projects.latimes.com/mapping-la/neighborhoods/neighborhood/hollywood/crime/ Why it is new/interesting/important/distinctive: because it tells so many stories as the data model allows, and automatically generates basic reporting with main rates for calculations on crime or deaths, besides showing census demographics data. The human reporting goes for the main stories, but in one way or the other, everyone is informed.
Dollars for Doctors http://www.propublica.org/series/dollars-for-docs
What the example is: it´s a news application that gathers drug companies data and produces many stories on doctors in the US who receive payments from this companies , to act as speakers, consultants or advisors. What does it do: besides reporting, it allows people to seach by doctor´s name, by drug company or by state. The company comparison chart exhibits the level of disclosure of each company http://projects.propublica.org/docdollars/companies
Why you like it: this news application started with 7 and now features 12 drug companies. It shows data in context, it allows people to search and extract reports by companies, doctors or state. The payments per state charts are easy to use and navigate : http://projects.propublica.org/docdollars/states/colorado
Why it is new/interesting/important/distinctive: because it builds and shares data that is unique presented in a friendly way , allowing the audience to ask questions to this datasets and report locally for what is relevant to each one. The open tools (including a widget!) and mindset of Propublica´s team , and the generosity to share their knowledge are part of their success.
MP´s Expenses - The Guardian http://mps-expenses.guardian.co.uk/
What the example is: the example consists in a crowdsourcing application developed to make the audience help detect, classify and priorize investigative paths in two different MPs expenses documentation sets released by Parliament after a long battle of FOI requests by different parties. What does it do: the application offers users who volunteer a way to help filter PDFs presented at random and to categorize them topically and classify those who need further investigation. Why you like it: I like it because it mixes a large unstructured data set with the a large audience, offering to participate to get a structured output, a database. Why it is new/interesting/important/distinctive: learning experience: from the first to the second phase, in which the dataset was smaller, they got it fully reviewed. Impact: the MPs returned up to 500.000 pounds and now they are more careful about the expenses they register, someone else is watching…
FROM SECTION 2
note: overview: what changes there are in the newsroom, division of labour, information landscape means need news skills, who has these skills, in-house or contracted, journo-coder collaborations, or more technically sophisticated journalists?
note: possible material from booki?
todo: add material from abc, el mundo, and others
todo: ask for material on cross-organisational collaboration
note: to add Guardian Data Journalism Process: http://www.opendatacookbook.net/wiki/recipe/guardian_workflow and http://www.guardian.co.uk/news/datablog/2011/apr/07/data-journalism-workflow
todo - little overview in frame narrative
How is it done: journo-developers vs. coders for hire
Overview In-house expertise How the news apps team at Chicago Tribune works Projects realized with external experts In-house resources plus external open data & visualisation expertise: the ZEIT-ONLINE model How to hire a hacker: Where to look The Hackathon Model: RegioHack, a 30 hour datajournalism hackathon with regional subjects (Netherlands)
To incorporate into short intro:
A survey on training needs for data journalism circulated by the European Journalism Centre between April and August 2011 showed that 39% of the 234 respondents envisioned their organisation to start engaging in data journalism through engaging a combination of external experts and existing staff. 36% envisioned training existing staff.
In the following chapter journalists involved in data journalism projects explain models for doing data journalism in their newsroom.
In-house expertise
Some datasets or methods require special skills i.e. programming skills to manage the data and visualize it. Don’t stop your passion for your idea because of missing these skills in your newsroom. There are a lot of highly motivated developers and designers out there to come into your project.
So you have the data… what next? Where do you start and where could you end?
In this section, top data-journalists take us through useful tips and tricks for how they have produced their data-powered stories before diving deeper into what made them determined to work on a particular project, why they chose the methods they did, the barriers they encountered, lessons learned and the eventual impact the stories made….
More case studies
MPs expenses scandal in the UK is an example of how a simple Freedom of Information (FOI) request can trigger a large scale investigation. An FOI request uncovered some interesting stories about how elected officials spend taxpayers' money. Subsidies for the Bus Transportation System: Angelica Peralta Ramos , LA NACION (Argentina)
case study 1
You’ve poured hours into tidying up and working with your data and got your story. What do you do with the data now? In this chapter, we take a look at cases where journalists have decided to open up their datasets and publish them along with their stories: What role did the datasets play in the original story? What was the motivation for opening them up? What did others choose to do with the data?
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Roles of visualisation in journalism by Lulu Pinney
The function of data visualisations in reportage is twofold. Firstly they are a tool for exploring the data to find where any stories are. Their second use is for telling a story. And it is worth noting that - for the same set of data - it is more than likely that the visuals best suited to finding a story will not be best suited to the telling of it.
Using visualisations to explore data is a more objective exercise, and sometimes it is appropriate to create an interface so your audience can have a go themselves. Alternatively having explored and interpreted the data yourself, you can choose just to present the stories you have found in a more subjective - or editorial - manner to your audience, with or without supporting visualisations.
more on this from Sarah Cohen at the end of Feb.; more specifically Mainly on the use of it inside the newsroom to hone the story — expanding on that handout you found. The real weakness there is that there are not good, free tools to use when you’re not willing to make your data public.
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