A seminar by Mirko Lorenz @MIRKOLORENZ (EJC European Journalism Center) on Data Driven Journalism topics at Ordine dei Giornalisti del Veneto, Venezia. 14 April 2015 #DDJ
Mirko Lorenz Data Driven Journalism Overview Seminar Ordine dei Giornalisti del Veneto European Journalism Center 14 apr 2015 #DDJ
1. A D E E P E R L O O K
F O R B E T T E R S T O R I E S
D A TA D R I V E N J O U R N A L I S M S E M I N A R
O R D I N E D E I G I O R N A L I S TA • V E N E Z I A 2 0 1 5 • E U R O P E A N J O U R N A L I S M C E N T E R
2. O V E R V I E W:
- I N T R O D U C T I O N T O D D J
- E X E R C I S E : 3 X 3 - W H AT, W H Y, H O W
- T O O L : D ATA W R A P P E R
- T I P S : E X C E L F O R M U L A S
- Q U E S T I O N S & D I S C U S S I O N
3. @ M I R K O L O R E N Z
J O U R N A L I S T / I N F O R M AT I O N A R C H I T E C T
F O C U S : C R O S S M E D I A / D ATA - D R I V E N J O U R N A L I S
D ATA W R A P P E R
D ATA D R I V E N J O U R N A L I S M . N E T
D E U T S C H E W E L L E I N N O VAT I O N T E A M
Brief introduction
4.
5. B I G D ATA
S M A L L D ATA
R E L E VA N T D ATA
6. W H AT I S
D ATA - D R I V E N
J O U R N A L I S M ?
9. Data is a new camera
(Replace as many stock photos with charts as you can)
10. T H R E E K E Y TA S K S
• Collect national, regional, local data
• What does it mean for readers/users?
• Enable comparisons, look for outliers
11. S E E : W I K I P E D I A „ D ATA - D R I V E N J O U R N A L I S M “
data-driven journalism
S E E : D ATA J O U R N A L I S M H A N D B O O K ( F R E E )
Tipp: #ddj (Twitter)
13. Edward Tufte: To be truthful and revealing, data graphics must bear on the
question at the heart of quantitative thinking: “Compared to what?, from:
The Visual Display of Quantitative Information
START WITH THIS QUESTION:
COMPARED TO WHAT?
19. W H Y
D ATA - D R I V E N
J O U R N A L I S M ?
20. IN A DATA-DRIVEN WORLD NEWSROOMS
NEED TO ADAPT
‣ Online Publishing
‣ Data as a source of exclusive reporting positions
Früher
Daten,
Studien,
Umfragen
Redaktion
Heute
Redaktion
Open Data
„Not-so-open“
Data
21.
22.
23. R E D A K T I O N E N U N D A R C H I V E M Ü S S E N
G L E I C H Z I E H E N , A R B E I T V E R E I N FA C H E N …
24. Q U E L L E : V I S U A L LY - H T T P S : / / W W W. Y O U T U B E . C O M / WAT C H ? V = A I V K F N E R B P Q
25. Q U E L L E : V I S U A L LY - H T T P S : / / W W W. Y O U T U B E . C O M / WAT C H ? V = A I V K F N E R B P Q
26. A LIST OF REASONS FOR DATA-DRIVEN WORK:
‣ Help our readers to make important decisions in life:
Election, Economy, Education/Profession, Real Estate, Retirement,
Health
‣ Users expect competent support and guidance
‣ Investivative projects to tackle corruption and big issues
‣ Chance to build a unique regional reporting position
‣ Services for trust and decision making to complement reporting
‣ Outlook: From Attention to Trust
27. BIG OPPORTUNITIES
Let people search less
Reduce the time they need to search
Help to make decisions
Detect big changes/issues earlier
Be part of trust economy
28. A R E A S O F
A P P L I C AT I O N
T E L L I N G S T O R I E S
B A S E D O N D ATA
29. GO THROUGH THE KEY QUESTIONS - FIVE W & ONE H
http://www.slideshare.net/stsanto/the-back-of-the-napkin-dan-roam
WHAT? (WHO’S COUNTING?)
HOW MUCH? (COMPARE)
WHERE? (MAP)
WHEN? (TIMELINE)
HOW? (FLOWCHART)
WHY (ANALYSIS)
30. – C H R I S T I A N B A U E R
„Zitat hier eingeben.“
D ATA R E S E A R C H L E A D
T O T H I S S T O RY
34. – C H R I S T I A N B A U E R
„Zitat hier eingeben.“
D ATA - D R I V E N S T O RY /
L O C A L N E W S PA P E R
35. „Zitat hier eingeben.“
The project is an excellent example of journalists intervening to put
a largely neglected issue on the political agenda, and providing
decision-makers and the public with the evidence they need to
take action to stop these tens of thousands of deaths at Europe’s
borders. This is data journalism at its best. We need more projects
like this.
B I G I N V E S T I G AT I O N ,
M U LT I - P U B L I C AT I O N A C R O S S
E U R O P E
36. – C H R I S T I A N B A U E R
„Zitat hier eingeben.“
I M P R E S S I V E I N T E R A C T I V E ,
D O N E B Y L O C A L
N E W S R O O M
41. 1. Data Story 2. Data Special 3. Data App
Find Small datasets Complex data Big data
Clean Excel Open Refine Database
Visualize Line, Bar, Pie Interaction & Filters Dashboards
Publish Embed Special URL App or service
Who? Journalist Journalist + Designer
Journalist + Designer
+ Developer
THREE TYPES OF PROJECTS
47. A P P R O A C H
Start with simple questions:
- How many participants?
- Outliers?
- Winners? Cheaters?
Dig deeper:
- Wie viele wurden disqualifiziert?
- Möglichkeit: U-Bahn nehmen
- Welche anderen Möglichkeiten?
- Weitergabe der Anmeldung
48. W H E N U S I N G D ATA :
G O F I N D A L A N M I L L E R
Source: Andy Lehren, The New York Times
Die Geschichte: Alan Miller
49. E X A M P L E :
O LY M P I C S
1 0 0
M E T E R
R A C E
unknown derivative work by Durova - derivative work of
Image:Jesse_Owens.jpg - reproduction of photograph in
"Die Olympischen Spiele, 1936" p.27, 1936.
66. D AT E N :
E X C E L
G O O G L E S H E E T S
O P E N R E F I N E
S C R A P E R
F O R M E L N ( Z . B . I N F L AT I O N , A R B E I T S M I N U T E )
V I S U A L I S I E R E N :
D 3 . J S
J U I C E L A B S C H A R T C H O O S E R
D ATA W R A P P E R
76. One user, multiple publishing options for 30 days.
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Full customization of data input,
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Newsrooms and workgroups.
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