Data Journalism 101 - Day 2 by Michael J. Berens
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Data Journalism 101 - Day 2 by Michael J. Berens

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Michael J. Berens presents the final part of the free, two-day webinar, "Data Journalism 101," hosted by the Donald W. Reynolds National Center for Business Journalism. ...

Michael J. Berens presents the final part of the free, two-day webinar, "Data Journalism 101," hosted by the Donald W. Reynolds National Center for Business Journalism.

For access to the webinar materials, visit http://bit.ly/datajourn101.

For more information about training for business journalists, please visit http://businessjournalism.org

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Data Journalism 101 - Day 2 by Michael J. Berens Presentation Transcript

  • 1. Data Journalism 101 (Part II) Donald W. Reynolds National Center for Business Journalism at ASU Michael J. Berens – The Seattle Times
  • 2. Meet my editor – a guy who thought a special project was something that took two hours instead of one
  • 3. Database types •  Obtained from a public agency or other institutional source (Part I)] •  Scrapped from the web or digital document – copy and paste (Part I) •  Created from scratch using any mixture of paper records •  Hybrid data analysis – layering existing data with your own database
  • 4. Poll Question: Have you ever created a database from scratch?
  • 5. Every database begins with a single cell
  • 6. Cells, fields and headers, oh my
  • 7. Segregation is good Address number from street name Middle initial from first name First name from last name
  • 8. Basic fields
  • 9. Bad Sorry, dude
  • 10. Good Not bad, grasshopper
  • 11. Better Brilliant. You rock!
  • 12. Hiding in plain sight •  A health care professional was administratively charged with sexual misconduct with patients. •  His punishment? •  He was only allowed to treat women age 50 or older (re: public record posted on Wa. Dept. of Health website)
  • 13. Basic Fields •  License # •  Name •  Occupation •  Offense type •  Dates of action •  Sexual misconduct; unprofessional conduct; moral turpitude
  • 14. Paper to Excel
  • 15. Paper to Excel
  • 16. Poll Question: What is your suggestion for a unique field?
  • 17. Tapping the power of Excel •  Sorting •  Filtering •  Basic calculations
  • 18. Pick the column
  • 19. Alphabetized by name
  • 20. Filtering
  • 21. Chevron marks
  • 22. Filtered by profession
  • 23. Calculations •  Always begins with an equal sign •  Basic math structure using names of cells •  =A1+A2
  • 24. Data training resources Investigative Reporters and Editors: www.ire.org http://www.ire.org/nicar/ Reynolds Center http://businessjournalism.org http://businessjournalism.org/registration/llc/
  • 25. Keep the trash – everything has value
  • 26. Look for signature cases
  • 27. The strategy •  Get the basic data •  Get the basic files •  Create a spreadsheet – add on categories •  Dive deeper for paper records – understand the system
  • 28. Elephants and zoos
  • 29. Adult family homes
  • 30. The federal government has launched a grant program that pays states to relocate seniors. They call it “rebalancing.” Poll Question: What would you do with this information?
  • 31. Develop your nose for data