Successfully reported this slideshow.
Your SlideShare is downloading. ×

Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)

Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)

Download to read offline

Data-driven journalism: Data in the newsroom

These are the slides from my talk at OK Con 2011. It provides a brief overview, then discussess barriers and challenges for data-journalism.

NOTE: This version is slightly edited, I primarily cleaned up missing image credits, etc. The message is the same.

CC-BY 3.0

Data-driven journalism: Data in the newsroom

These are the slides from my talk at OK Con 2011. It provides a brief overview, then discussess barriers and challenges for data-journalism.

NOTE: This version is slightly edited, I primarily cleaned up missing image credits, etc. The message is the same.

CC-BY 3.0

More Related Content

Similar to Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)

Related Books

Free with a 30 day trial from Scribd

See all

Related Audiobooks

Free with a 30 day trial from Scribd

See all

Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)

  1. 1. OKCON 2011 OPEN DATA IN THE NEWSROOM WHAT‘S THE STORY? Mirko Lorenz • Information Architect/Journalist • Deutsche Welle/Innovation Projects June 30, 2011 • Kalkscheune Berlin
  2. 2. THIS IS ALL BETA needs work
  3. 3. WELCOME. IF YOU ARE NEW, THIS IS THE CONTEXT This is a presentation from at OK Con 2011 in Berlin. The topic is „data-driven journalism“ (DDJ). Our idea of data-driven journalism is to view the analysis of data as a rich source for good stories. Data-driven journalism is inclusive, meaning that other forms of journalism (investigative, computer-assisted reporting) are surely part of the broader quest to find ways for relevant, insightful journalism in a world driven by data. Plus, we hope that by adding data to the newsroom there will be new models to finance journalism. And why not, if the story is good. Data-driven journalism @ Wikipedia: http://en.wikipedia.org/wiki/Data_driven_journalism
  4. 4. ME: TURNED JOURNALIST INFORMATION ARCHITECT FOCUS: TURNING IDEAS INTO PLATFORMS, WORKFLOWS, STORIES WORKING@DEUTSCHE WELLE INNOVATION PROJECTS JOURNALISM TRAINER
  5. 5. DATA IN THE NEWSROOM?
  6. 6. DATA IN THE NEWSROOM? NOW: OPEN DATA IS A WINNER
  7. 7. DATA IN THE NEWSROOM? NOW: OPEN DATA IS A WINNER NEXT: CHALLENGES AHEAD
  8. 8. DATA IN THE NEWSROOM? NOW: OPEN DATA IS A WINNER NEXT: CHALLENGES AHEAD FUTURE: PATTERN CHANGE?
  9. 9. #1: OPEN DATA IS A WINNER
  10. 10. WE ALL NEED THE DATA
  11. 11. THE IDEA ACCEPTED ON HIGH LEVELS
  12. 12. DATA INSIGHTS FOR EVERYONE? WORLD COUNTRY PEOPLE CITY GROUP OPEN + NOT-SO-OPEN DATA
  13. 13. DATA INSIGHTS FOR EVERYONE? MEDIA WORLD COUNTRY PEOPLE CITY GROUP OPEN + NOT-SO-OPEN DATA
  14. 14. #2: DATA-DRIVEN JOURNALISM: WHY BOTHER?
  15. 15. OBSERVATIONS: MUCH PROGRESS LAST YEAR SIMON ROGERS IS AN OUTLIER NEED TO TRAIN JOURNALISTS WHAT ARE LONG-TERM GOALS?
  16. 16. ON A GLOWING RECTANGLE NEAR YOU THE MOVIE? DATA STORY DIGGING DEEPER „Surprisingly helpful“ -- User „Our city is now a better place“ -- Local Authority „It‘s a wonder how we could do without it“ -- Government AN OPEN DATA PRODUCTION
  17. 17. CHALLENGES: DIRTY DATA DATA NEEDS STORY CREATING A NEW „CAMERA“
  18. 18. HOW DIRTY IS THE DATA? Tar Sands of Alberta. Image: Some rights reserved by NWFblogs
  19. 19. HOW DIRTY IS THE DATA? EXTRACTING MEANING FROM DATA WILL BE HARD WORK WON‘T COME AT ZERO-COST OR WITHOUT UNWANTED EFFECTS Tar Sands of Alberta. Image: Some rights reserved by NWFblogs
  20. 20. NOT ALL DATA-SETS CREATED EQUAL INCOMPLETE WRONG FOCUS COMPETITION WRONG FORMAT CREATED FOR DIRTY Text MARKETING, MISTAKES DATA NOT INSIGHTS WHEN COLLECTED INTENTIONALLY FORGED INSIGHTS KEPT SECRET
  21. 21. Journalists, where do you add value? - Jeff Jarvis
  22. 22. DATA + STORY = VALUE TO PUBLIC
  23. 23. DATA + STORY: EXAMPLE Source: Information is Beautiful, by David McCandless
  24. 24. A „NEW CAMERA“ TO VIEW THE WORLD Source: Information is Beautiful, by David McCandless, quoted from talk of David in Brussels @ Visualizing Europe, 2011
  25. 25. A „NEW CAMERA“ TO VIEW THE WORLD Source: Information is Beautiful, by David McCandless, quoted from talk of David in Brussels @ Visualizing Europe, 2011
  26. 26. DATA + STORY „NEVER COMING HOME“ Source: http://mediastorm.com//publication/never-coming-home
  27. 27. #3: WHAT‘S KEEPING US? BARRIERS FOR DATA JOURNALISM
  28. 28. REBUILDING THE NEWSROOM - WHY AND HOW?
  29. 29. TODAY‘S MEDIA MODELS Print Web Blogs * iPad Mobile Most media companies still think of data and digital formats as an extension, not as the foundation. *Blogs are red, because most media did not get the idea
  30. 30. FROM SINGLE STORIES...
  31. 31. ...TO DATA-BASED CONTEXT
  32. 32. DATA AS A FOUNDATION Database Web Print Overview Article Depth Articles Crime Maps Dossier Competency Background Data Statistics Context Relevance Analysis Audio Trustability Photo Video
  33. 33. SITUATION OF JOURNALISTS
  34. 34. MOST JOURNALIST‘S SITUATION NO ACCESS TO FAILING SERVER MODELS NO SUPPORT RISING NO Text WORKLOAD TRAINING TOO MANY DATA TOOLS TIME PRESSURE OLD-SCHOOL CMS
  35. 35. STRANGE TIMES: LAY-OFFS IN NEWSROOMS VS. TALENT SHORTAGE IN DIGITAL BUSINESS
  36. 36. #4: DEVELOPING THE FIELD
  37. 37. WHAT ARE THE TRAINING NEEDS?
  38. 38. WHAT WOULD BE A GOOD WORKFLOW? A workflow for video and data journalism using next-gen cloud storage Team Ingestion Filter Produce Publish Distribute Popularity Goals Teamwork vs. one-man-show Enabling use of data in newsrooms Workflow as driver of value, better integration Note: Deutsche Welle is a partner in this EU-project. Website here: http://www.visioncloud.eu Visualization inspired by „A Web Site Designed“, created by John Furness of Simple Square
  39. 39. WHAT WOULD BE A GOOD WORKFLOW? VISION Cloud Media Use Case A workflow for video and data journalism using next-gen cloud storage Team Ingestion Filter Produce Publish Distribute Popularity Goals Teamwork vs. one-man-show Enabling use of data in newsrooms Workflow as driver of value, better integration Note: Deutsche Welle is a partner in this EU-project. Website here: http://www.visioncloud.eu Visualization inspired by „A Web Site Designed“, created by John Furness of Simple Square
  40. 40. Text WHAT ARE THE STEPS? Team Ingest Filter Produce Publish Distribute Measure Note: Deutsche Welle is a partner in this EU-project. Website here: http://www.visioncloud.eu Visualization inspired by „A Web Site Designed“, created by John Furness of Simple Square
  41. 41. SMART INTERACTION Scraperwiki Open Calais Video editing Data Visualization Tools Story Presentation Multi-platform Collecting STORLETS Needlebase Google Refine Final Cut R Studio Storify Wordpress Distribution usage data over time, Protovis Document Cloud Memolane File Conversion based on & APIs Fullstory Flash files, not pages Gapminder Other CMS in use HTML5 iTunes VIDEO/DATA VIDEO/DATA PRODUCTION WITH TEAMS iPod FILTERING INGESTION Android METADATA SET-UP Nokia TEAM RIM PROJECT NAME Team Ingestion Filter/Metadata Produce video oder data story Publish Multi-platform distribution Popularity FIND SNIPPETS OF VIDEO/DATA FOR RE-USE ING F RAIS TION O C NAL DAT STORAGE TRA E ) ATIO A MO ABS TORAG SULES ADVANCED CAPABILITIES FOR CLOUD-BASED STOR PUT GE COM ORA FED BILITY A ACCESS S AC AP AGE ST ERA TION ND RIGHTS DAT (M ETA SECURITY CLOUD PURE STORAGE LAYER - KEEPING FILES AND VERSIONS OF FILES OVER TIME Visualization inspired by „A Web Site Designed“, created by John Furness of Simple Square
  42. 42. #5: PATTERN CHANGE
  43. 43. Q: PATTERN CHANGE? A: LOOKING INTO THE DATA, USING WHAT WE FIND FOR GOOD PURPOSES CAN RESULT IN A BIG SHIFT OF POWER
  44. 44. QUIZ: WHAT ARE AR THE INSIGHTS & TOOLS FUTURE GENERATIONS WILL THINK ARE OBVIOUS?
  45. 45. WHAT CAN BE DONE? (MOST EXAMPLES ON THIS PAGE ARE LINKED) SURPRISE CLARITY TRUST
  46. 46. #HOPE: MEDIA COMPANIES BECOMING TRUSTED DATA HUBS
  47. 47. THE FUTURE: INSTANT CLARITY BEFORE WE MAKE DECISIONS Source: Visua.ly
  48. 48. THE FUTURE: INSTANT CLARITY BEFORE WE MAKE DECISIONS Source: Visua.ly
  49. 49. THE FUTURE: INSTANT CLARITY BEFORE WE MAKE DECISIONS Source: Visua.ly
  50. 50. FINALLY: THE CALL TO ACTION (1) LET‘S WORK TOGETHER (2) DEVELOPERS/JOURNALISTS/VISUALIZERS (3) SMALL TEAMS CAN ROCK THIS PLACE
  51. 51. Caution: There’s no standard career path to become a deconstructor of wrongness Quote from David H. Freedmann, „Wrong“, Review of Book http://www.nytimes.com/2010/06/11/books/excerpt-wrong.html
  52. 52. THANK YOU! Brian Storm Simon Rogers Walter Mossberg Rafat Ali Ariana Huffington Aron Pilhofer Jeff Jarvis Nicolas Kayser-Bril Michelle Minkoff Mercedes Bunz Mathias Eberl Lorenz Matzat Tracy Boyer Paul Bradshaw Amanda Cox
  53. 53. HOUSEKEEPING: HOW TO CONNECT Twitter: #ddj Please use this hashtag for „data-driven journalism“ - it‘s nicely short Survey: The survey to find out about training needs for data journalists is still open (as of July 2011) http://www.surveymonkey.com/s/data_journalism Data-driven journalism group @ EJC +150 people discussing and developing. http://community.ejc.net/group/datadrivenjournalism Data-driven journalism website http://datadrivenjournalism.net/ My website: http://www.mirkolorenz.com
  54. 54. IDEAS, DISCUSSION, ARGUE? TWITTER: #DDJ @MIRKOLORENZ Some ideas and concepts presented here have received funding from the European Community's Seventh FrameworkProgramme (FP7/2007-2013) under grant agreement n° 257019 (VISION Cloud)

Editor's Notes

  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n

×