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Data-driven journalism, every day

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This is a practical presentation from NODA 2017, the Nordic Data conference, this year held in Odense. The presentation discusses tools (specifically Datawrapper) and general editorial approaches to data-driven journalism. The presentation advocates a pragmatic approach - based on searching for data, questioning, visualisation and written texts. This approach could provide opportunities specifically for regional/local media.

Be aware that as this is a presentation from the people behind Datawrapper the tool is discussed and presented on a number of slides in this presentation.

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Data-driven journalism, every day

  1. 1. Odense, Denmark - January 27-28, 2017 Data-driven journalism, every day Mirko Lorenz, Cofounder and CEO
  2. 2. Background Daily #ddj Next level Three key points: Note: This is a slightly edited version of a talk given at NODA 2017 in Odense (Jan. 2017). Changes were made to make the presentation easier to understand when the spoken narrative is missing.
  3. 3. Datawrapper - background and 
 development so far Part 1
  4. 4. Datawrapper is a web-based visualisation tool, providing a workflow to create responsive charts and maps. The tool aims to focus on quality and is optimised for use in newsrooms.
  5. 5. D3.JS and other visualization libraries are great, but hard to use for journalists...When we started in 2011, the goal was to close a gap…
  6. 6. …because even with many new options to create charts most journalists simply are not trained to work with code.
  7. 7. https://www.datawrapper.de/gallery
  8. 8. http://dataviz.tools Positive feedback keeps us going.
  9. 9. In September 2016 
 Datawrapper 
 crossed the mark 
 of 1 billion chart views.
  10. 10. No outside investors No debt Popular in newsrooms worldwide Datawrapper today:
  11. 11. How Datawrapper works, in four main steps. Quick Walkthrough
  12. 12. User Dashboard: All drafts and charts 
 in one place. 
 Direct access to 
 blog & tutorials.
  13. 13. Importing data via copi & paste. This helps to clean the data for 
 visualisation.
  14. 14. Step 2 is to check and transform
 the data.
  15. 15. Select the output locale here Example: 
 Choose the output locale and all numbers 
 change ad once.
  16. 16. Output locale provides
 an easy way to transform 
 your numbers to the right
 format.
  17. 17. Click on the column1Select the options here2 Advanced options: Transform numbers.
  18. 18. Divide, round or add a $/€ sign.
  19. 19. Select colors.
  20. 20. Publish…
  21. 21. Part 2 Daily data-driven journalism: 
 Have we even started?
  22. 22. Example of one
 chart telling a 
 story of notable
 change. Source: Journalism That Stands Apart (New York Times, January 2017) Link
  23. 23. Data-driven journalism…
  24. 24. A workflow for daily data search, filtering and publishing in different ways. This is how Simon Rogers
 created the widely noted
 Guardian Data Blog. Source: 
 https://simonrogers.net/2013/01/27/a-data- journalism-workflow/
  25. 25. Source: 
 https://simonrogers.net/2013/01/27/a-data- journalism-workflow/ Not every data story is a complex interactive. There are multiple options to publish data, including simply making it more public. Even raw data can be very helpful for a community, if put into context in the right way.
  26. 26. Source: http://atlas.qz.com 
 Another good example:
 Atlas by vox.com is demonstrates the value of constant, daily digging for data to enrich the story. Why is hardly any regional/local medium working in this way?
  27. 27. Great current example how powerful data can be. If one economist from Oxford University can start something like this, what keeps media companies from doing the same?
  28. 28. „Our World in Data“ by Max Roser:
 Putting things in comparison, 
 for better understanding.
  29. 29. NZZ builds
 it’s own toolbox.
  30. 30. The Wirecutter shows how we can and should create value for users.
  31. 31. Building trust is through being trustable. Announce your intention, then stick to it. The Wirecutter makes money through affiliate links. A bit more background here.
  32. 32. Suggestions towards local, regional 
 data-driven journalism Why not combine Quartz Atlas, 
 „Our world in Data“ and The Wirecutter - for the benefit of local newsrooms?
  33. 33. We need this, because often statistics
 remain difficult to understand.
  34. 34. https://www.theguardian.com/politics/2017/jan/19/crisis-of-statistics-big-data-democracy By ignoring statistics and failing to 
 turn hidden facts into comprehensible stories
 we do damage to a source of truth…
  35. 35. Track regional numbers. Track numbers better than officials. Transform the numbers. Reduce need to search. Show what is not known. Be there when decisions are made. Do the math, because no one else does it for many people. How to do better
  36. 36. Source of article: The Guardian Example
  37. 37. Smart way to engage
 with the reader. Source: New York Times
  38. 38. Everyday I write the book
 Start doing daily data journalism.
 It is not a question of budget, 
 it’s a quest for depth and quality.
  39. 39. One search technique every journalist can use:
 Combine Google search with „data“, then look at results under „Images“.
  40. 40. Another way: 
 Be on the lookout when the statistical office
 (any) publishes new data. 
 ChangeDetection is just one service which can be used for that.
  41. 41. Visualizing data No map, no interactive - but well done, basic charts instead. When working with charts simplicity is often the better choice.
  42. 42. Archie Tse: Why we are doing fewer interactives. Presentation from Malofiej 2016 (PDF) The New York Times 
 thinks twice before 
 starting a big interactive data project - although they
 know how to it. Why is simplicity often better?
  43. 43. Nobody will look at a 
 line chart? Think again. This is the rise
 of beer prices
 at Octoberfest Munich.
  44. 44. Provide good comparison A key principle, demonstrated in three simple charts
  45. 45. http://www.businessinsider.com/the-future-of-digital-2013-2013-11?op=1
  46. 46. http://www.businessinsider.com/the-future-of-digital-2013-2013-11?op=1
  47. 47. Power of Proximity Talk about data close to home.
  48. 48. http://interaktiv.morgenpost.de/m29 Great story by Berliner Morgenpost: 
 Following social, political changes along a bus route in Berlin.
  49. 49. How prices for rent have risen, specifically in city areas with many
 low-priced flats (to the right).
  50. 50. Simple tools can help to 
 get the story right. Download PDF
  51. 51. Datawrapper New features added in 2016
  52. 52. Summary
  53. 53. Better tools Do the math (for everyone) Collaborate better
  54. 54. Mirko Lorenz Cofounder and CEO 
 mirko@datawrapper.de http://www.datawrapper.de @mirkolorenz Thanks.

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