7. New Journalism Model
Social
Open Chaotic
Fast Shallow
Video
Audio
Text
Expert
Closed Structured
Slow Deep
8. New Journalism Model
Social
Video
Audio
Text
Expert
Story
Specialism
Story
Specialism
9. The Data Journalism Challenge
Social
Finding the signal in the noise
Finding patterns in the numbers
Expert
Expert
10. The Data Journalism Challenge
Social
Finding the signal in the noise
Make it connect
Personal, relevant, engaging
Finding patterns in the numbers
Expert
Expert
11. Data Journalism at the BBC
Focus on depth and analysis
Focus on government and public data sets
Provide personalisation and encourage
interactivity
16. How did we do it?
Lead Correspondent
External experts - health watchdog
Visual Journalism expert
Social Media Expert - Facebook Page
Community Manager
17. Learning
Lot of initial set up between BBC and NHS teams
Project management - RACI
Editorial issues - trust, taste, authority v authenticity
Cross media promotion boosts impact
Personalisation drives engagement
18. UNICEF Citizen Engagement
Mobiles distributed throughout Uganda
Citizen journalists answer surveys vie free SMS
Exchange views on social policy
Further discussion on radio and in print
Influencing policy makers
19.
20. Next Steps
Extending to many new countries
Improve website user experience and interactivity
Additional of rich media - photos, audio, video
22. What do you need to execute?
✤ Where does your expertise lie?
✤ Who can help you find, tell and sell your story?
✤ Cost/Benefit - how much time for how much impact?
✤ What are you going to stop doing?
……………..………now, where’s that story?!
23. What’s the story?
Can you summarise it in one simple sentence?
Who’s interested - do you really know your audience?
Can it create an emotional connection/engagement?
Who’s the story about, who are the characters?
Why, how - can the data tell us even more?
24. What’s the story?
Who’s best/worst?
What’s changed? Why?
Are you stretching the truth Mr/Mrs Representative?
Have you kept your promise? Is your plan working?
Look at the difference, depending where you live/work
Why is the data incomplete/missing?
What human effect is the data having, reactions?
Relationships - why does this go up and that go down?
What’s going up/what’s going down?
Ref: Paul Bradshaw, Data Journalism Heist 2013
25. It’s too complicated!
We work with data every day
Keep it simple, stay focused on one or two data sets
Don’t forget the journalism
Data is just one source - where’s your second?
26. What next?
Increasing use of video, particularly on mobile
Increasing use of data animation
Much better personalisation
The internet of things