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Etmaal
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Etmaal

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  • 1. validating external data sets what social scholars and data journalists can learn from each another
  • 2.     Hille van der Kaa @Hillevanderkaa  
  • 3. missing data, no value stored “I need to solve this”
  • 4. missing data, no value stored “I need to solve this” missing data, no value stored “I need to write a story about this”
  • 5. forreporters.com/andrew-lehren/
  • 6. “Trustworthiness and data management are vital to the success of qualitative studies … There is a lack of scientific literature regarding the structures and processes for managing large qualitative data sets.” (White, Oelken, Friesen, 2012)  
  • 7. “A simple answer to objective reporting is the kind of reporting that uses relevant and reliable sources which is not bias or slanted to a certain party.” Ibrahim, Pawanteh, Kee (2011)
  • 8. can I trust and use this dataset?
  • 9. check the data source what are his/her/its intentions?
  • 10. what is the citation index of the data owner? do other journalists cite the data owner?  
  • 11. benefit do I really need this? do I really need to use it?  
  • 12. check data gathering? is this correct? clarification of the data? do I understand?  
  • 13. missing data what is wrong? I need to solve what is the story? I need to write  
  • 14. internal validation TEST! CALL!  
  • 15. I need more sources! (do I?) give me data check consistency give me humans check my story  
  • 16. scientists data journalists check the source (citation) check the source (citation) check the data check the data check benefit check benefit check data gathering check clarification TEST! CALL! more data sources more human sources
  • 17. scientist to journalist: “You twist everything”
  • 18. “Dear datajournalist, Please take a look at the research method yourself and act a bit more like a scientist.”
  • 19. journalist to scientist: “Your articles are useless”
  • 20. “Dear scientist, Try to avoid intellectual arrogance. There are other people who are just as smart.”  
  • 21. journalistic data mining The process of finding correlations or patterns in large relational databases. It is the process of analyzing data from different perspectives and summarizing it into useful and reliable information.  

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