Introduction to Data Journalism          Peter Verweij            Wits University         Johannesburg Aug 27
An example: Olympic Rankings                 Lessons                 Official Ranking                 Other Factors:   ...
Numbers in Journalism             Writing a story about              ICT and Economic              development          ...
Statistics Matter            Digging deeper            Finding Background            Official Explanation
Traffic Accidents           From Database:            2000 accidents           Top ten           Dangerous junctions   ...
What is Data Journalism?Producing stories truth seeking stories in the   public interest without a legal foundation       ...
Shoot out and licenses              7 dead; 17 wounded              Check the licenses              What do you want to...
Mayors: gender and political party                    Appointment of                     mayors                    Formu...
Finding Data    WHERE:                                              HOW:    National Bureau for                       ...
Mother of all Data Journalism    Spreadsheets                                  Ordering data    MS Office: excel      ...
Visualize!        ManyEyes        Fusion Tables        Tableau        Qgis
Data Journalism: team work and              important    IMPORTANT                                             TEAM WORK...
Thank you!        This is the map for         Saturday Sept 15.        Peter@d3-media.nl
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Wits dataj intro

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Wits dataj intro

  1. 1. Introduction to Data Journalism Peter Verweij Wits University Johannesburg Aug 27
  2. 2. An example: Olympic Rankings  Lessons  Official Ranking  Other Factors: Population, GDP, Team  Corrected Ranking
  3. 3. Numbers in Journalism  Writing a story about ICT and Economic development  Internet user In southern Africa  Google Public data
  4. 4. Statistics Matter  Digging deeper  Finding Background  Official Explanation
  5. 5. Traffic Accidents  From Database: 2000 accidents  Top ten  Dangerous junctions  Map is the story
  6. 6. What is Data Journalism?Producing stories truth seeking stories in the public interest without a legal foundation FROM A PILE OF DATA
  7. 7. Shoot out and licenses  7 dead; 17 wounded  Check the licenses  What do you want to know?  Methodology: formulate and hypothesis
  8. 8. Mayors: gender and political party  Appointment of mayors  Formulate your ideas first  Test them of the data  Look at the level of measurement
  9. 9. Finding Data WHERE:  HOW: National Bureau for  Download statistics  Copy-paste NGOs  scraping Web: find excel Web: tables
  10. 10. Mother of all Data Journalism Spreadsheets  Ordering data MS Office: excel  Simple calculations Open Office for key figures  Graphs
  11. 11. Visualize!  ManyEyes  Fusion Tables  Tableau  Qgis
  12. 12. Data Journalism: team work and important IMPORTANT  TEAM WORK More data  Writer More use of data for  Researcher policies  Hacker Check  Designer Find hidden trends
  13. 13. Thank you!  This is the map for Saturday Sept 15.  Peter@d3-media.nl

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