The art and science of data-driven journalism
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This document discusses the history and current state of data-driven journalism. It outlines how journalists have long used data and tools like calculators, graphs, and databases to support their work. In recent decades, new technologies like computers, the internet, mobile phones, and data visualization tools have enabled more sophisticated data-driven reporting. The document argues that while data journalism is not new, it is becoming increasingly important as data creation grows exponentially. It stresses the importance of ethics, transparency, and using data to tell compelling stories that shed light on important issues.
The art and science of data-driven journalism
- 1. The Art and Science of Data-Driven Journalism Alexander B. Howard Tow Fellow, Columbia University May 30, 2014
- 2. You know something, John Snow.
- 3. This John Snow knew something.
- 4. Newspapers have used data for centuries Source: The Guardian
- 5. 1960s: computer-assisted reporting (CAR) Bob Woodward, via Cliff1066
- 6. Traditional tools applying tech to journalism… • Calculators and Graphs • Mainframe and PCs • Spreadsheets • Databases • Text and code editors • Statistics • Programming
- 7. In the 1990s, government and civil society spread the Internet globally
- 8. In the 2000s, mobile phones and social networking connected us ever more
- 9. In the 2010s, data creation exploded. Image Credit: Real Time Rome from Senseable.MIT.edu
- 10. “Data-driven journalism is the future” Source: Tim Berners-Lee in the Guardian
- 11. …combined with new tools & context… • Online spreadsheets and wikis • Data visualization tools • Open source frameworks • Code sharing • Agile development • Cloud storage and processing (EC2 & Heroku) • More data and more access • Privacy and security riskss
- 12. 2014: data journalism is the present Gathering, cleaning, organizing, analyzing, visualizing and publishing data to support the creation of acts of journalism
- 14. Trendy but not new • The collection, protection and interrogation of data as a source, complementing traditional “shoe leather” investigative reporting relying on witnesses, experts and authorities
- 16. Dollars for Docs
- 17. The Guardian
- 18. Chicago Tribune • Flame retardants
- 20. A tangled web
- 24. La Nacion
- 29. Best practices?
- 30. Report it out
- 32. Show people something new about the world
- 34. Tell a story
- 35. Center for Public Integrity
- 36. Storytelling still matters. “We use these tools to find and tell stories. We use them like we use a telephone. The story is still the thing.” - Anthony DeBarros USA Today Source: Data Journalism and the Big Picture
- 37. Make it personal
- 39. Understand the context for the data
- 41. Show your data
- 43. Show your work
- 45. Share your code
- 47. Consider ethics
- 48. Questions • Is the data clean? • Is the data representative? • What biases might be hidden in the data? • Was the data legally obtained? • Does the data contain personally identifiable information (PII)?
- 49. Collection • Who gathered the data? How? • Was it clear how data would be used? • Can people opt-out of collection or usage? • “Notice and consent” is not enough • “Privacy by design” applies to news apps
- 51. Data Analysis & Numeracy • N = ? • Average vs Median • Statistical significance? • Correlation != causation • Regression to the mean
- 53. Presentation
- 55. Present data with context, in context
- 56. Be aware of de-anonymization risks
- 57. Emerging trends
- 58. geojournalism
- 59. Networked reporting of corruption ICIJ: Offshore Leaks
- 60. International Consortium of Investigative Journalists Offshoring $ 80 journalists 40 countries 260 gigabytes 2.5 million files
- 61. Create your data “If Stage 1 of data journalism was “find and scrape data,” then… Stage 2 was “ask government agencies to release data” in easy to use formats. Stage 3 is going to be “make your own data”, and those sources of data are going to be automated and updated in real-time.” -Javaun Moradi, Mozilla
- 64. Bus route in Nairobi, Kenya
- 68. Citizens as Sensors: Andhra Pradesh
- 69. Drones + data collection
- 72. Open Data, FOIA & Press Freedom
- 73. An expanding number of data sources
- 76. Social data and crisis data
- 77. Open government data platforms
- 80. Fauxpen Data In an age of “openwashing”… We need to: Evaluate licenses. Peruse the Terms of Service. Review the governance. Look at community. Check the format.
- 83. Center for Public Integrity
- 84. Accountability for “personalized redlining” • Gun map graphic
- 85. Transparency for geographic profiling • Gun map graphic WSJ: Websites vary prices, based upon user information
- 86. Monitoring predictive policing • Gun map graphic Verge: Chicago crime and profiling Geekwire: Predictive Policing
- 87. Investigating human tissue trafficking • Gun map graphic ICIJ: The data behind skin and bone
- 88. Data + journalism + activism + responsive institutions = social change
- 89. The fun part: predictions, prognostications and recommendations!
- 90. 1) Data will become even more of a strategic resource for media.
- 91. 2) Better tools will emerge that democratize data skills.
- 92. 3) News apps will explode as a primary way people consume data journalism.
- 93. 4) Being digital first means being data- centric and mobile-friendly.
- 94. 5. Expect more robo-journalism. Human relationships and storytelling still matter.
- 95. 6) More journalists will need to study the social sciences and statistics. Source: Ed Yong
- 96. 7) There will be higher standards for accuracy and corrections. Source: Jake Harris
- 97. 8) Competency in security and data protection will become more important. Source: Jake Harris
- 98. 9) Demand for more transparency on reader data collection and use. Source: eConsultancy
- 99. 10) More conflicts over public records, data scraping, and ethics will arise. • Gun map graphic
- 100. 12) Data-driven personalization and predictive news in wearables.
- 101. 13) More diverse newsrooms will produce better (data) journalism. SOURCE: The Atlantic A 2013 ASNE survey of 68 online news organizations found that 63% of them had no minorities.
- 102. 14) Be mindful of data-ism and bad data. Embrace skepticism.