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#DDJ at BabelTalk

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Data journalism after hype.

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#DDJ at BabelTalk

  1. 1. Data journalism after hype @jancibulka
  2. 2. Data journalism as a trend • Hype at Google Search: “data journalism”
  3. 3. Data journalism and newsroom pace • journalist produce few articles per day, #ddj few per (good) month • no time for failures and death ends (way to bigger ones, scientists will tell you) • outcome known on pitch (unbiased data? not really) • gov data obtaining is a long run (no way to throw away crappy ones)
  4. 4. Data journalism and readers • in many times, charts do not helping, only illustrating (know readers how to read it?) • hiding bias and flappy work behind science • can’t interpret without understanding (what correlation 0.53 means for reader?)
  5. 5. Data journalism little bit hard to read ! by-se-do-snemovny-nedostali ! kriminalita-optikou-mobilnich-dat
  6. 6. Data journalism and openness • open data • open code • open know-how, process… • (peer)review. lot of it. (missing community here)
  7. 7. To read • 189703/the-problem-with-data-journalism/ • journalisms-critics-and-the-roots-of-diversity-problems/ • Review us