Presentation to the South African National Editors Forum 22 November 2010 Johannesburg, South Africa

1. "Analytic Journalism:
Digital Evolution in the
Datasphere"
Tom Johnson
Managing Director
Inst. for Analytic Journalism
Santa Fe, New Mexico USA
tom@jtjohnson.com

2. Presentation to the
South African National Editors Forum
22 November 2010
Johannesburg, South Africa

3. Today’s conversation
• Journalism past [briefly] and present
• What is Analytic Journalism
• Where we think journalism is (should be?)
heading
3

4. What’s Changed in Journalism?
• Old:
“News” = spoken word, text, images
• Today: “News” = Data = 1s & 0s
• Global ubiquity and fluidity of data
• 5 billion cell phones [July ’10]
• Africa: 1/3 pop. have cell phones
• Metadata
• Editors  Database administrators
• Is the Mass Media dead?
4

5. What’s Changed in Journalism?
• Datasphere Basic Process:
Data In  Analysis  Info Out
• Former “basic process”
– Superficial research
– Gather anecdotes & quotes & AV
– Write, i.e. String together in “acceptable
form”
– Publish/broadcast soonest
– Do it again tomorrow
5

6. What’s Changed in Journalism
Industrial Age Journalism
– High capital investment: presses, paper, delivery,
broadcasting equipment
– Low investment in “wet ware,” i.e. employees and
their skills
Digital Age Journalism
• Low capital threshold for data, analytic tools,
“publishing”
• High educational threshold for data, analytic
tools, “publishing”
• Power shift from authority and institutional
power to sub-groups and individuals

7. What’s Changed in Journalism?
• Constant deadlines, but …
• Breaking news has already broken
• If people already have the “news,” what do
we have to contribute?
7

8. What is “Analytic Journalism”
Traditional Journalism
•Quick & Dirty research
•Gather quotes
•Harvest anecdotes
•Get some video
•String together in a 30,
60, 90-sec story
•Repeat tomorrow
8
Analytic Journalism
•Not events, but context & trends
•Define phenomena of interest as a
SYSTEM
•Employ RRAW-P process
Research  Reporting Analysis 
Write  Publish”‟
•Non-traditional analytic tools:
GIS, data mining, forensic
accounting, Social Network Analysis

9. Cornerstones of IAJ
• General Systems Theory
• Statistics
• Data visualization
- www.niceone.org/lab/refugees/
• Simulations
- Simtable Fire Model
- St. Marks Square
- Venice boats
- Zozobra park

10. Cornerstones: IAJ version of Analytic
Journalism
• General Systems Theory
1. System boundaries
2. Variables
3. Relationships between variables
4. System has goals
5. System capable of “learning”
6. System exists in an environment
• “System” can be self defined; can be
defined by outside observer(s)
• System is “scaleable”
10

11. Newspaper as a system

12. Theory of Journalistic Process
12
Data In Analysis  Info
Out

13. Theory. It’s important, valuable.
13
Data In  Analysis  Info Out
•Notes
•Text
•Numeric
•Images
•Charts/Graphs
•Maps
•Audio
•Video
•Atoms  Bits
•How? Who?

14. Theory. It’s important, valuable.
14
Data In  Analysis  Info
Out• Notes
• Text
• Numeric
• Images
• Charts/Graphs
• Maps
• Audio
• Video
• AtomsBits
How? Who?
• What are we looking
for? How can we be
surprised?
• Source
• Definition
• Context
• Estimating
• Counting
• Statistical
• Geostatistical
• Social Network Analysis
• Forensic accounting

15. Theory. It’s important, valuable.
15
Data In  Analysis  Info
Out• Notes
• Text
• Numeric
• Images
• Charts/Graphs
• Maps
• Audio
• Video
• AtomsBits
How?
• What are we
looking for? How
can we be
surprised?
• Source
• Definition
• Context
• Estimating
• Counting
• Statistical
• Geostatistical
• Social Network
Analysis
• Forensic
accounting
• Broadcast
• Web
• Audio
• Video
• Text
• Data visualization
• Maps
• Dynamic databases
• Archives

16. Theory. It’s important, valuable.
16
Data In  Analysis  Info
Out
• Notes
• Text
• Numeric
• Images
• Charts/Graphs
• Maps
• Audio
• Video
• AtomsBits
How?
• What are we
looking for? How
can we be
surprised?
• Source
• Definition
• Context
• Estimating
• Counting
• Statistical
• Geostatistical
• Social Network
Analysis
• Forensic
accounting
• Broadcast
• Web
• Audio
• Video
• Text
• Data visualization
• Maps
• Dynamic databases
• Archives
Contributed content
Contributed content
& analysis

17. Developing Tools for Collaboration
• Who is using wikis? Google Docs? Zoho?
• Intra-nets
• Inter- and intra-nets

18. Goals for Journalism Education
• Raise basic admission standards
– Applicants already can write; can do basic arithmetic
• Develop/improve tools for newsroom and citizen
journalism collaboration
– Intranets
– Wikis
– Google Docs
– Blogs, social media, Flickr, etc.
– Research customization for journalism
• Develop tools for story telling

19. Community & Collaboration
• Citizen Journalism and Democracy
in Africa:
“Periodismo Ciudadano y Democracia en África”: Un libro en línea de
Fackson Banda
• UK: The Guardian uses the citizen
journalist to great effect in
Expenses Scandal
• Investigate your MP’s expenses
• Oldweather.org Oldweather.org
• NYTimes Knowledge Network
El New
York Times ofrece un curso online de periodismo ciudadano
19

20. Online learning; online tools
• ICFJ Anywhere
Global source for high-quality, online journalism courses
taught by seasoned professionals.
• Google Refine
Google Refine is a power tool for working with messy
data, cleaning it up, transforming it from one format into
another, extending it with web services, and linking it to
databases like Freebase.
• Many Eyes
Site is set up to allow the internet community to upload
data, visualize it, and talk about their discoveries with
other people.
20

21. Storytelling R&D? Innovation?
21

22. Storytelling R&D? Innovation?
22
• Potential for “drill-down” dynamics
• Reach URLs
• Show data for statistical analysis
• Ask questions; capture answers

23. Tomorrow?
• Our job is to “monitor the centres of
power.”
-- Amira Haassaid
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24. Tomorrow?
• In a democracy, news media
harvest data; become central
warehouse of citizen’s data
• A “public library” on steroids
• Digital resources for in-house
journalists
• Create “dashboards” to monitor gov’t.
• Potential to create specialized, non-
journalism “products”
• Provide data to app creators

25. Tomorrow?
• Paying for news rapidly declining
market.
• So what can journalists offer?
25

26. "Analytic Journalism:
Digital Evolution in the
Datasphere"
Tom Johnson
Managing Director
Inst. for Analytic Journalism
Santa Fe, New Mexico USA
tom@jtjohnson.com

27. Theory. It’s important, it’s valuable.
27
Nothing is as valuable as a
good theory.