Download as KEY, PPTX
Uploaded byMirko Lorenz
Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)
The document is a presentation on data-driven journalism from the OK Con 2011 conference, emphasizing the need for open data as a resource for storytelling in journalism. It discusses the challenges faced by journalists in harnessing data, the importance of training, and the potential for new workflows and models in newsrooms. The presentation also calls for collaboration between developers, journalists, and visualizers to enhance data journalism's effectiveness.
More Related Content
Similar to Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)
![Coded Agents – with UiPath SDK + LangGraph [Virtual Hands-on Workshop]](https://cdn.slidesharecdn.com/ss_thumbnails/codedagentsdeck-251215155422-5497c599-thumbnail.jpg?width=640&height=640&fit=bounds)
Open Data in the Newsroom: What's the story? (Talk from OK Con 2011 in Berlin)
- 1. OKCON 2011 OPEN DATAIN THE NEWSROOM WHAT‘S THE STORY? Mirko Lorenz • Information Architect/Journalist • Deutsche Welle/Innovation Projects June 30, 2011 • Kalkscheune Berlin
- 2. THIS IS ALL BETA needs work
- 3. WELCOME. IF YOU ARENEW, 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. ME: TURNED JOURNALIST INFORMATION ARCHITECT FOCUS:TURNING IDEAS INTO PLATFORMS, WORKFLOWS, STORIES WORKING@DEUTSCHE WELLE INNOVATION PROJECTS JOURNALISM TRAINER
- 5. DATA IN THENEWSROOM?
- 6. DATA IN THENEWSROOM? NOW: OPEN DATA IS A WINNER
- 7. DATA IN THENEWSROOM? NOW: OPEN DATA IS A WINNER NEXT: CHALLENGES AHEAD
- 8. DATA IN THENEWSROOM? NOW: OPEN DATA IS A WINNER NEXT: CHALLENGES AHEAD FUTURE: PATTERN CHANGE?
- 9. #1: OPEN DATA ISA WINNER
- 10.
- 11. THE IDEA ACCEPTED ON HIGH LEVELS
- 12. DATA INSIGHTS FOREVERYONE? WORLD COUNTRY PEOPLE CITY GROUP OPEN + NOT-SO-OPEN DATA
- 13. DATA INSIGHTS FOREVERYONE? MEDIA WORLD COUNTRY PEOPLE CITY GROUP OPEN + NOT-SO-OPEN DATA
- 14. #2: DATA-DRIVEN JOURNALISM: WHY BOTHER?
- 15. OBSERVATIONS: MUCH PROGRESS LASTYEAR SIMON ROGERS IS AN OUTLIER NEED TO TRAIN JOURNALISTS WHAT ARE LONG-TERM GOALS?
- 16. ON A GLOWINGRECTANGLE 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. CHALLENGES: DIRTY DATA DATA NEEDS STORY CREATING A NEW „CAMERA“
- 18. HOW DIRTY ISTHE DATA? Tar Sands of Alberta. Image: Some rights reserved by NWFblogs
- 19. HOW DIRTY ISTHE 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. NOT ALL DATA-SETSCREATED EQUAL INCOMPLETE WRONG FOCUS COMPETITION WRONG FORMAT CREATED FOR DIRTY Text MARKETING, MISTAKES DATA NOT INSIGHTS WHEN COLLECTED INTENTIONALLY FORGED INSIGHTS KEPT SECRET
- 21. Journalists, where do you addvalue? - Jeff Jarvis
- 22. DATA + STORY= VALUE TO PUBLIC
- 23. DATA + STORY:EXAMPLE Source: Information is Beautiful, by David McCandless
- 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. 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. DATA + STORY „NEVERCOMING HOME“ Source: http://mediastorm.com//publication/never-coming-home
- 27. #3: WHAT‘S KEEPING US? BARRIERSFOR DATA JOURNALISM
- 28. REBUILDING THE NEWSROOM- WHY AND HOW?
- 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.
- 31.
- 32. DATA AS AFOUNDATION Database Web Print Overview Article Depth Articles Crime Maps Dossier Competency Background Data Statistics Context Relevance Analysis Audio Trustability Photo Video
- 33.
- 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. STRANGE TIMES: LAY-OFFS INNEWSROOMS VS. TALENT SHORTAGE IN DIGITAL BUSINESS
- 36.
- 37. WHAT ARE THETRAINING NEEDS?
- 38. WHAT WOULD BEA 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. WHAT WOULD BEA 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. Text WHAT ARE THESTEPS? 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. 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.
- 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. QUIZ: WHAT ARE ARTHE INSIGHTS & TOOLS FUTURE GENERATIONS WILL THINK ARE OBVIOUS?
- 45. WHAT CAN BEDONE? (MOST EXAMPLES ON THIS PAGE ARE LINKED) SURPRISE CLARITY TRUST
- 46.
- 47. THE FUTURE: INSTANTCLARITY BEFORE WE MAKE DECISIONS Source: Visua.ly
- 48. THE FUTURE: INSTANTCLARITY BEFORE WE MAKE DECISIONS Source: Visua.ly
- 49. THE FUTURE: INSTANTCLARITY BEFORE WE MAKE DECISIONS Source: Visua.ly
- 50. FINALLY: THE CALLTO ACTION (1) LET‘S WORK TOGETHER (2) DEVELOPERS/JOURNALISTS/VISUALIZERS (3) SMALL TEAMS CAN ROCK THIS PLACE
- 51. Caution: There’s nostandard 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. 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. HOUSEKEEPING: HOW TOCONNECT 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. 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)