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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