Data journalism
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This document provides an introduction to data journalism and some tools that can be used. It discusses how data journalism has existed for a long time but is now using new data sources and tools. Examples of early data journalism include Florence Nightingale and analyzing data from the Detroit riots in 1967. It provides examples of using data to analyze topics like sports, fashion, and politics. It also lists some free and open source tools that can be used for data scraping, visualization, and analysis like Excel, Google Fusion Tables, and ScraperWiki. Coding skills are becoming more important for data journalism but are not required to get started. It concludes with a 10 step plan for getting started in data journalism.
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Data journalism
- 1. Data journalism Why bits, bytes and stats are your friends
- 2. It’s nothing new The Manchester Guardian 1821
- 3. Florence Nightingale – data journalist
- 4. Detroit 1967
- 7. Deprivation and Manchester rioters
- 9. How we’d look under AV
- 10. The War Logs – IED attacks
- 12. Go beyond obvious applications • Sport – BBC’s Ollie Williams has done visualisations around events • Fashion – I helped Grazia to track the spread of a social media campaign by Twitter scraping
- 13. Tools and ideas GETTING STARTED
- 14. CAR vs Data journalism • Computer-Assisted Reporting is an old school name for what is sometimes now called data journalism • Data was in spreadsheets, databases and surveys • Also social network analysis tools
- 15. Key things to note • Not a quick process • Too many numbers can confuse your audience • Know your sources of data • Check it back with the source
- 16. Some of the tools of the trade • Excel • Access • Many Eyes (wikified) • Wordle • Tableau • Google Fusion tables • Google docs spreadsheet • Yahoo pipes • Scraperwiki
- 17. Coding is becoming part of journalism • Some journalists are learning Python, Django, or Ruby to analyse data • But it doesn’t have to be difficult or hard to work with
- 18. Empty properties site:gov.uk filetype:xls Bolton Map it
- 19. Google Fusion tables • Location, location, location • The Lords
- 20. Some sites of interest • Where does my money go • Information is beautiful • Guardian data blog
- 21. 10 step plan DATAMINER’S RECIPE FOR GETTING STARTED
- 22. Former JOMEC broadcaster Data mining and data journalism
- 23. Datamineruk’s Top 10 Things for getting Started in Data Journalism
- 24. Data follows @paulbradshaw - Paul’s list of Godlike Geniuses @jamesrbuk @StephenGrey @DataMinerUK @psychemedia @Coneee @clairemilleruk @kevglobal @bbcsport_ollie
Editor's Notes
- #5: Philip Meyer TheÌýDetroit Free PressÌýand theÌýDetroit NewsÌýthrew every resource they had into covering the uprising. And as the disturbance died down, journalists and commentators, most of them white, struggled to understand who the rioters were and why they had taken to the streets. One theory was that those who looted and burned buildings were on the bottom rung of society—riff raff with no money and no education. A second theory speculated that rioters were recent arrivals from the South who had failed to assimilate and were venting their frustrations on the city.But for many, those theories rang false.A survey had been done following the 1965 Watts riots. Meyer approached Nathan Caplan, a friend from graduate school at the University of Michigan in Ann Arbor. They both had a similar idea to see if a survey similar to the one done after Watts could be done in Detroit. One challenge was that the Watts study took two years, but Meyer wanted it done in three weeks. The ISR has an article that looks at the process in great depth, and what is clear is that the study of the 1967 Detroit riots and the journalism that followed had a lot of support not only from the newspapers but from the university, government and local foundations. They recruited and trained 30 teachers to conduct the surveys, drew up a random sample and interviewed 437 black residents.The survey debunked a number of theories put forward to explain the violence.One theory was that the rioters were poor and uneducated. No, the survey found otherwise. ¨There was no correlation between economic status and participation in the disturbance. College-educated residents were as likely as high school dropouts to have taken part.¨Another theory laid the blame at recent arrivals from the south who had little connections to the community. That theory was also wrong. ¨Recent immigrants from the South had not played a major role; in fact, Northerners were three times as likely to have rioted.¨Ìý
- #12: Red - 5 to 15 social houses per 100 households, orange 15 to 25, yellow 25 to 35, green 35 to 45 and blue 45 to 55Read MoreÌýhttp://www.walesonline.co.uk/news/datastore/local-authorities/2011/11/20/data-social-housing-stock-91466-29810079/#ixzz1ecDUnuAdÌý