Data Journalism 2: Interrogating, Visualising and Mashing
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This document discusses data journalism techniques including interrogating, visualizing, and mashing data. It provides examples of 5 things to know about each technique, such as choosing the right chart, cleaning data, and finding points of connection between datasets. Tools mentioned for working with data include Google Refine, Yahoo Pipes, and Tableau. The document encourages readers to experiment with these techniques and tools.
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Data Journalism 2: Interrogating, Visualising and Mashing
- 1. Data 2: Interrogating, visualising, mashing Online Journalism City University Paul Bradshaw Monday, 7 March 2011
- 2. Themes 5 things you need to know about each Data journalism in action Walkthrough Monday, 7 March 2011
- 3. Interrogating data . Monday, 7 March 2011
- 4. Monday, 7 March 2011
- 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 copies Monday, 7 March 2011
- 6. Monday, 7 March 2011
- 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 Ball Monday, 7 March 2011
- 8. Monday, 7 March 2011
- 9. What is the data worth? Measurement doesn't answer anything if there's only one variable Statistical significance Sample size and selection Controls and the placebo effect Read up. Monday, 7 March 2011
- 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 Journalism Monday, 7 March 2011
- 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. 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. Visualising data . Monday, 7 March 2011
- 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 classes Monday, 7 March 2011
- 15. or http://chartchooser.juiceanalytics.com/ Monday, 7 March 2011
- 16. Monday, 7 March 2011
- 17. Monday, 7 March 2011
- 18. What is wrong with this picture? Monday, 7 March 2011
- 19. Monday, 7 March 2011
- 22. Visualisation tools ManyEyes Tableau Wordle, Tagxedo BatchGeo Gephi Delicious.com/paulb/visualisation+tools Monday, 7 March 2011
- 23. Walkthrough: visualising data with Google Gadgets . Monday, 7 March 2011
- 24. Walkthrough: visualising data in ManyEyes . Monday, 7 March 2011
- 25. Mashing data . Monday, 7 March 2011
- 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 static Monday, 7 March 2011
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- 29. Mashup tools Yahoo! Pipes OpenHeatMap Mapalist xFruits Scraperwiki Maptube Monday, 7 March 2011
- 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, KML Monday, 7 March 2011
- 31. Walkthrough: making mashups with OpenHeatMap Format the spreadsheet Publish it as CSV Copy link Paste it at OpenHeatMap Fix any problems Monday, 7 March 2011
- 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 & examples Monday, 7 March 2011
- 33. Questions? . Monday, 7 March 2011
- 34. Links OnlineJournalismClasses.tumblr.com Delicious.com/paulb/cityoj09 Delicious.com/paulb/datajournalism Delicious.com/paulb/visualisation Delicious.com/paulb/statistics Delicious.com/paulb/mashups Monday, 7 March 2011
- 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 data Monday, 7 March 2011
- 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 Data Monday, 7 March 2011