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Exploring Data Journalism: From Concept to Compelling Storytelling

This comprehensive guide by Steve Doig from the Cronkite School of Journalism at Arizona State University outlines the essential components and processes of data journalism. It emphasizes the importance of data in storytelling, the steps to uncover data-driven ideas, and methods for data collection and analysis. The guide covers variable types, data cleaning techniques, and collaboration among various team members, such as reporters, editors, and designers. It encourages journalists to utilize public records and technological tools effectively, ensuring impactful storytelling through data.

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Exploring Data Journalism: From Concept to Compelling Storytelling

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  1. www.public.asu.edu/~sdoig/IJF2014/

  2. Data journalism:From idea to story Steve Doig Cronkite School of Journalism, Arizona State University steve.doig@asu.edu @sdoig

  3. Why do data journalism?

  4. What is “data”?

  5. Finding data story ideas

  6. datadrivenjournalism.net/

  7. IRE’s ExtraExtra feed

  8. theguardian.com/news/datablog

  9. Informants and whistleblowers

  10. Read documents

  11. Work backwards from your idea! • What statements do you want to make? • What variables are needed to make those statements? • Who would collect data with those variables? • How will you get the data from the collector?

  12. 1. Statements? • Lede = hypothesis • Bullet points = statements • Examples for a crime and courts data story: • “Crime has increased/decreased X % since...” • “The X per 100.000 violent crime rate of Y City is the worst ...” • “Only X % of reported crimes result in arrests...”

  13. 2. Variables needed? • Columns = variables • Rows = records • Two main kinds of variables • Categorical: Sex, city, postal code, type of crime, etc... • Numeric: Age, cost, population, weight, arrests, accident, etc...

  14. 3. Who collects those variables?

  15. 4. Get the data!

  16. Public records tools

  17. Data formats?

  18. Avoid PDFs

  19. Avoid PDFs...but if necessary... • Convert to *.xls with: • Acrobat Pro • Zamzar • CometDocs • (many others)

  20. You have data... ...Now what??

  21. Clean the data

  22. Data cleaning tools

  23. Look for patterns

  24. Excel tools • Sort • Filter • Functions • Pivot tables

  25. Brain tools – math and statistics

  26. Brain tools – math and statistics

  27. Friday 1130-1300 (Hotel Sangallo)

  28. EJC MOOC – free!!

  29. Data journalism story elements

  30. Data journalism story elements

  31. Data journalism team • You! • Other reporters • Editors • Graphic artists • Photographers • Videographers • Page designers • Web designers • App developers

  32. Other DDJ workshops

  33. Questions??

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