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validating external data sets 	
	
	
	
	
	
	
what social scholars and data journalists can learn from each another
 
	
  
	
Hille van der Kaa	
@Hillevanderkaa	
	
  
missing data, no value stored	
“I need to solve this”
missing data, no value stored	
“I need to solve this”	

missing data, no value stored	
“I need to write a story about this”
forreporters.com/andrew-lehren/
“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)	

	
	
  
“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)
can I trust and use this dataset?
check the data source	
	
what are his/her/its intentions?
what is the citation index	
of the data owner?	
	
	
do other journalists	
cite the data owner?	
	
	
  
benefit	
	
do I really need this?	
	
	
	
do I really need to use it?	
	
	
  
check	
	
data gathering? 	
is this correct?	
	
	
clarification of the data?
do I understand?	
	
	
  
missing data	
	
what is wrong? 	
I need to solve	
	
	
what is the story?	
I need to write	
	
  
internal validation	
	
TEST!	
	
	
	
CALL!	
	
  
I need more sources! (do I?)	
	
give me data	
check consistency	
	
	
give me humans	
check my story	
	
  
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
scientist to journalist: “You twist everything”
“Dear datajournalist,	
	
Please take a look at the
research method yourself
and act a bit more like a
scientist.”
journalist to scientist: “Your articles are useless”
“Dear scientist,	
	
Try to avoid intellectual
arrogance. There are
other people who are just
as smart.”	
	
  
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.	
	
  
Gross Time Ranking versus Net Time Ranking	
  

	
  

‘The net time is the measured time from starting line
to finish line and the gross time is the measured time
from the starting shot until the finish line. 	
	
In photo's of the starting line of marathons one can
see thousands of runners who are eager to start.
However, when one stands in the last starting pen,
one can not directly run at full speed.	
	
A kind of human traffic jam arises when the
marathon starts. On the internet people complain
about this difference in time results, because the
ranking is based on gross times.’
missing values - solve	
	
	
‘We discovered that the data of 100
runners lacked. Apparently one scraped
page was added double. We removed
the 100 duplicates.’	
  
missing values - story	
	
	
‘Still, nineteen runners were missing in
the Amsterdam data set. 	
Perchance these are runners that have
been disqualified.’	
	
Or…
‘To calculate the average position
changes, caused by net ranking, we
converted the difference scores to
absolute figures.	
	
The average position change in the
Amsterdam Marathon was 281.6
places.’
scientific outcome	
‘We calculated the Kendalls Tau rank
correlation coefficient for the net and
gross ranking of the Amsterdam
Marathon. 	
This coefficient shows that despite of the
average differences between the
rankings, the net and gross time rankings
are almost equal to each other.’
journalistic outcome	
‘We spoke Patrick Schuerman from Tilburg
on the phone. Patrick had starting number
11797 in the Amsterdam Marathon of 2013
and had a gross time versus net time
difference of over 21 minutes. 	
	
In his opinion, the ranking of the marathon
should happen after net times since these
are the ‘real’ times people ran.’
we are both right
we can learn from each other
 
	
  
	
Hille van der Kaa	
@Hillevanderkaa	
	
  

current topic:	
	
a citizen view on the
credibility of machine
written news	
	
  
http://tinyurl.com/
research-uvt	
	
Part of PhD research 	
Human Component in 	
Machine Written Narratives

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Etmaal

  • 1. validating external data sets what social scholars and data journalists can learn from each another
  • 2.     Hille van der Kaa @Hillevanderkaa  
  • 3.
  • 4. missing data, no value stored “I need to solve this”
  • 5. missing data, no value stored “I need to solve this” missing data, no value stored “I need to write a story about this”
  • 7.
  • 8. “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)  
  • 9. “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)
  • 10. can I trust and use this dataset?
  • 11. check the data source what are his/her/its intentions?
  • 12. what is the citation index of the data owner? do other journalists cite the data owner?  
  • 13. benefit do I really need this? do I really need to use it?  
  • 14. check data gathering? is this correct? clarification of the data? do I understand?  
  • 15. missing data what is wrong? I need to solve what is the story? I need to write  
  • 17. I need more sources! (do I?) give me data check consistency give me humans check my story  
  • 18. 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
  • 19. scientist to journalist: “You twist everything”
  • 20. “Dear datajournalist, Please take a look at the research method yourself and act a bit more like a scientist.”
  • 21. journalist to scientist: “Your articles are useless”
  • 22. “Dear scientist, Try to avoid intellectual arrogance. There are other people who are just as smart.”  
  • 23. 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.  
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30. Gross Time Ranking versus Net Time Ranking     ‘The net time is the measured time from starting line to finish line and the gross time is the measured time from the starting shot until the finish line. In photo's of the starting line of marathons one can see thousands of runners who are eager to start. However, when one stands in the last starting pen, one can not directly run at full speed. A kind of human traffic jam arises when the marathon starts. On the internet people complain about this difference in time results, because the ranking is based on gross times.’
  • 31.
  • 32.
  • 33.
  • 34. missing values - solve ‘We discovered that the data of 100 runners lacked. Apparently one scraped page was added double. We removed the 100 duplicates.’  
  • 35. missing values - story ‘Still, nineteen runners were missing in the Amsterdam data set. Perchance these are runners that have been disqualified.’ Or…
  • 36. ‘To calculate the average position changes, caused by net ranking, we converted the difference scores to absolute figures. The average position change in the Amsterdam Marathon was 281.6 places.’
  • 37. scientific outcome ‘We calculated the Kendalls Tau rank correlation coefficient for the net and gross ranking of the Amsterdam Marathon. This coefficient shows that despite of the average differences between the rankings, the net and gross time rankings are almost equal to each other.’
  • 38. journalistic outcome ‘We spoke Patrick Schuerman from Tilburg on the phone. Patrick had starting number 11797 in the Amsterdam Marathon of 2013 and had a gross time versus net time difference of over 21 minutes. In his opinion, the ranking of the marathon should happen after net times since these are the ‘real’ times people ran.’
  • 39.
  • 40. we are both right
  • 41. we can learn from each other
  • 42.     Hille van der Kaa @Hillevanderkaa   current topic: a citizen view on the credibility of machine written news   http://tinyurl.com/ research-uvt Part of PhD research Human Component in Machine Written Narratives