Data 2: Interrogating,    visualising, mashing   Online Journalism   City University   Paul BradshawMonday, 7 March 2011
Themes   5 things you need to know about each   Data journalism in action   WalkthroughMonday, 7 March 2011
Monday, 7 March 2011
5 things you need to know about    interrogating data   1. Data always needs cleaning up   2. Treat the ‘source’ like a so...
Monday, 7 March 2011
“What the Independent have done is confuse the UK’s deficit with our debt [making] the debt problem look around eight time...
Monday, 7 March 2011
1. Variance is interesting. 2. Variance is different for different variables and in different populations. 3. The amount o...
Getting data in the right form   Data > Text to columns   Find & replace   Conditional formulas:   =IF(condition, if met, ...
Walkthrough: cleaning data in    Google Refine   Edit cells > common transforms   Edit cells > split multi-valued cells   ...
Visualising data   .Monday, 7 March 2011
5 things you need to know about    visualising data   1. Choose the chart for the purpose   2. It can be used to spot a le...
or http://chartchooser.juiceanalytics.com/Monday, 7 March 2011
Monday, 7 March 2011
Monday, 7 March 2011
What is wrong with this picture?Monday, 7 March 2011
Monday, 7 March 2011
http://simplecomplexity.net/statistics-without-context/Monday, 7 March 2011
http://junkcharts.typepad.com/junk_charts/trifecta-checkup/Monday, 7 March 2011
Visualisation tools   ManyEyes   Tableau   Wordle, Tagxedo   BatchGeo   Gephi   Delicious.com/paulb/visualisation+toolsMon...
Walkthrough: visualising data in    ManyEyes   .Monday, 7 March 2011
Mashing data   .Monday, 7 March 2011
5 things you need to know about    mashing data   1. It is what a journalist does best   2. Look for a point of connection...
Monday, 7 March 2011
Monday, 7 March 2011
Mashup tools   Yahoo! Pipes   OpenHeatMap   Mapalist   xFruits   Scraperwiki   MaptubeMonday, 7 March 2011
Walkthrough: making mashups    with Yahoo! Pipes   Inputs - Fetch Feed, CSV, Data, Page,   YQL, Flickr, Form   Operators -...
Walkthrough: making mashups    with OpenHeatMap   Format the spreadsheet   Publish it as CSV   Copy link   Paste it at Ope...
Walkthrough: grabbing geo data    with Google Refine   Edit column > Add column by fetching   URLs   Use GREL (Google Refi...
Questions?  .Monday, 7 March 2011
Links   OnlineJournalismClasses.tumblr.com   Delicious.com/paulb/cityoj09   Delicious.com/paulb/datajournalism   Delicious...
Lab  Before the lab: play with these  techniques yourself, have problems,  find solutions, raise questions. Install  Googl...
Books   Kaiser Fung - Numbers Rule Your World   Ben Goldacre - Bad Science   Donna Wong - The WSJ Guide to   Information G...
Data Journalism 2: Interrogating, Visualising and Mashing
Data Journalism 2: Interrogating, Visualising and Mashing
Data Journalism 2: Interrogating, Visualising and Mashing
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Data Journalism 2: Interrogating, Visualising and Mashing

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Session for MA students at City University's Journalism School

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Data Journalism 2: Interrogating, Visualising and Mashing

  1. 1. Data 2: Interrogating, visualising, mashing Online Journalism City University Paul BradshawMonday, 7 March 2011
  2. 2. Themes 5 things you need to know about each Data journalism in action WalkthroughMonday, 7 March 2011
  3. 3. Interrogating data .Monday, 7 March 2011
  4. 4. Monday, 7 March 2011
  5. 5. 5 things you need to know about interrogating data 1. Data always needs cleaning up 2. Treat the ‘source’ like a source 3. Use the right ‘average’ and percentage 4. Variation over time & space: context 5. Spreadsheet tools are your friend - but always backup copiesMonday, 7 March 2011
  6. 6. Monday, 7 March 2011
  7. 7. “What the Independent have done is confuse the UK’s deficit with our debt [making] the debt problem look around eight times worse than it is. And it used the whole of its front page to do so.” - James BallMonday, 7 March 2011
  8. 8. Monday, 7 March 2011
  9. 9. What is the data worth? Measurement doesnt answer anything if theres only one variable Statistical significance Sample size and selection Controls and the placebo effect Read up.Monday, 7 March 2011
  10. 10. 1. Variance is interesting. 2. Variance is different for different variables and in different populations. 3. The amount of variance is easily quantified. - Philip Meyer, Precision JournalismMonday, 7 March 2011
  11. 11. Getting data in the right form Data > Text to columns Find & replace Conditional formulas: =IF(condition, if met, if not) =COUNTIF(range, test)Monday, 7 March 2011
  12. 12. Walkthrough: cleaning data in Google Refine Edit cells > common transforms Edit cells > split multi-valued cells Facet > text facet Export...Monday, 7 March 2011
  13. 13. Visualising data .Monday, 7 March 2011
  14. 14. 5 things you need to know about visualising data 1. Choose the chart for the purpose 2. It can be used to spot a lead 3. Good design is when there’s nothing more to take away 4. It should be self-contained & have refs 5. Be careful with scales and classesMonday, 7 March 2011
  15. 15. or http://chartchooser.juiceanalytics.com/Monday, 7 March 2011
  16. 16. Monday, 7 March 2011
  17. 17. Monday, 7 March 2011
  18. 18. What is wrong with this picture?Monday, 7 March 2011
  19. 19. Monday, 7 March 2011
  20. 20. http://simplecomplexity.net/statistics-without-context/Monday, 7 March 2011
  21. 21. http://junkcharts.typepad.com/junk_charts/trifecta-checkup/Monday, 7 March 2011
  22. 22. Visualisation tools ManyEyes Tableau Wordle, Tagxedo BatchGeo Gephi Delicious.com/paulb/visualisation+toolsMonday, 7 March 2011
  23. 23. Walkthrough: visualising data with Google Gadgets .Monday, 7 March 2011
  24. 24. Walkthrough: visualising data in ManyEyes .Monday, 7 March 2011
  25. 25. Mashing data .Monday, 7 March 2011
  26. 26. 5 things you need to know about mashing data 1. It is what a journalist does best 2. Look for a point of connection: place? Person? Company? Date? 3. What an API can do 4. What APIs there are 5. Mashups can be live, updated or staticMonday, 7 March 2011
  27. 27. Monday, 7 March 2011
  28. 28. Monday, 7 March 2011
  29. 29. Mashup tools Yahoo! Pipes OpenHeatMap Mapalist xFruits Scraperwiki MaptubeMonday, 7 March 2011
  30. 30. Walkthrough: making mashups with Yahoo! Pipes Inputs - Fetch Feed, CSV, Data, Page, YQL, Flickr, Form Operators - Filter, Sort, Unique, Union, Count, Split, Rename, Regex, Unique, Location extractor, URL Builder Outputs - Map, Gallery, List, XML, KMLMonday, 7 March 2011
  31. 31. Walkthrough: making mashups with OpenHeatMap Format the spreadsheet Publish it as CSV Copy link Paste it at OpenHeatMap Fix any problemsMonday, 7 March 2011
  32. 32. Walkthrough: grabbing geo data with Google Refine Edit column > Add column by fetching URLs Use GREL (Google Refine Expression Language) Search web for help & examplesMonday, 7 March 2011
  33. 33. Questions? .Monday, 7 March 2011
  34. 34. Links OnlineJournalismClasses.tumblr.com Delicious.com/paulb/cityoj09 Delicious.com/paulb/datajournalism Delicious.com/paulb/visualisation Delicious.com/paulb/statistics Delicious.com/paulb/mashupsMonday, 7 March 2011
  35. 35. Lab Before the lab: play with these techniques yourself, have problems, find solutions, raise questions. Install Google Refine and Tableau on your laptop to use. - Visualise, interrogate or mash dataMonday, 7 March 2011
  36. 36. Books Kaiser Fung - Numbers Rule Your World Ben Goldacre - Bad Science Donna Wong - The WSJ Guide to Information Graphics Brian Suda - A Practical Guide to Designing with DataMonday, 7 March 2011

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