Christian Radler of ARD (Germany) presented a data journalism project focusing on global warming. This project attracted 2 millions visitors online.

1. Better verticals through AI
&
How we made a map that 2 million
users klicked on

2. Better verticals through AI
&
How we made a map that 2 million
users klicked on

3. Better verticals through AI
&((sort of)
How we made a map that 2 million
users klicked on

4. Better verticals through AI
&
How we made a map that 2 million
users klicked on
HIER

5. How we made a map that 2 million
users klicked on

6. Better verticals through AI
• December 2016: tagesschau-App 2.0
• Vertical videos w/ headlines
• Pictacrop: automated video analysis
• Automated scene detection
• Suggestions on where to crop video
• Editor makes corrections & writes headlines
• Save: Cropping metadata and headlines
• < 20 verticals / day
• Dual use for TV format „tagesschau in 100
seconds“

8. Better verticals through AI

9. Better verticals through AI

10. Better verticals through AI
• How does it work?
• APPSFactory: „Our algorithm analyses scenes
and calculates a score based on three
parameters:
1. form, frequency and density of picture edges
2. saturation and color strength
3. skin tone (to detect faces)
The secret sauce is how we weigh
the three parameters.“

11. Better verticals through AI
• APPSFactory: „Our algorithm was trained with
thousands of videos and images. It is not a self
learning algorithm; no deep learning is
involved.“
• APPSFactory: „Developing correct scene
change detection was a lot harder.“

12. Better verticals through AI

13. Better verticals through AI
• How well does it work?
• Editor 1: „Most of the time, scene detection is
working fine. Also, the cropping suggestions need
little to no corrections.“
• Editor 2: „Center of attention wise Pictacrop does
its job. Only if say, there are two people of similar
size in the video, naturally the tool sometimes
picks the wrong one.“
• Editor 1: „If only we had less limitations
for the headlines!“

14. Better verticals through AI
&
How we made a map that 2 million
users klicked on

15. Better verticals through AI
&
How we made a map that 2 million
users klicked on

16. How we made a map
that 2 million users klicked on
• Data journalism is hard
• Crossmedia data journalism is even harder
• Add interactive to that
• Plus relatable
• Sharable
• Scalable
• = Checklist

17. How we made a map
that 2 million users klicked on
• If you do not have data scientists and
developer - hire (or rent) them
• Pick an event at a safe distance (at least two
months away)
• Get everyone to sit at the same table every
two weeks
• Enter tagesschau‘s data project
Klimadoppel (Climate Twin)

18. How we made a map
that 2 million users klicked on
• Climate Twin answers simple questions.
• How warm will summers be in my home town
60 years from now?
• What place has a similar summer maximum
today?
• Scenario A: 4 degrees global warming
• Scenario B: 2 degrees global warming
• Let me show you:

19. How we made a map
that 2 million users klicked on

20. How we made a map
that 2 million users klicked on

21. How we made a map
that 2 million users klicked on
• Checklist
• Crossmedia: online, social, messenger bot & tv
• Interactive: where applicable
• Relatable: we did the math for 14.000 places in
Germany; 28.000 combos
• Sharable: fb & Twitter
• Scalable: up to 20.000 users simultaniously; in
the first two days more than one million
unique users; 7 TB of data moved

22. Shameless self promotion

23. Shameless self promotion

24. Shameless self promotion

25. Shameless self promotion
• New map project
• Putting Europe on the Map – through Data
• Assist Europeans with data literacy
• All European data
• Starting in March
• Online before European Elections end of May
• Open for EBU members to join

26. Questions?

27. Contact
Christian Radler
c.radler@tagesschau.de
+49 40 4156 4152