Datajournalists and scientists use similar insights to validate an external dataset. Although the interpretation may differ.
As presented @ICA2013. Steps mentioned are based on the insights of 20 scientists and datajournalists.
3. missing data, no value stored
“I need to solve this”
Tilburg
University
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data
journalism
4. missing data, no value stored
“I need to solve this”
missing data, no value stored
“I need to write a story about this”
Tilburg
University
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data
journalism
8.
“I am right”
Tilburg
University
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data
journalism
9. can I trust (and use) this dataset?
Tilburg
University
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data
journalism
10. “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)
Tilburg
University
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data
journalism
11. “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)
Tilburg
University
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data
journalism
25. “Dear datajournalist,
Please take a look at the
research method yourself
and act a bit more like a
scientist.”
Tilburg
University
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data
journalism
26. “Dear scientist,
Try to avoid intellectual
arrogance. There are
other people who are just
as smart.”
Tilburg
University
-‐
data
journalism
NameWork at university – work as a writer / data journalistSomewhere in between – I do research something with a scientific goals and soething with a journalustic aim
If you are in between – it is interesting that the worlds of social science and datajournalism in the field are sometimes really different – but sometimes notIf we take fo example this dataset – which is the dataset Andrew Lehren from te New York Times used in Pullitzer prize winner story about the New York Marathon you can see a blind spot
… if a scientist sees this, in gereneral his first reponse it that the dataset is technically not right. There us some missing data. A problem which needs to be solved
While, if a journalist sees a white spot, he is really interested in the story behind the missing data. Why is the data missing?
In this case, both appriaches were all right; some runners missed checkpointBut also some technical flaws
If I talk about journalists with scientists not always as ethustaistic as they could be- They can’t de al with data – they use data in a superficial
Journalists – scietists are really egocentric – and their stories are not useful for the real world. They just do research to please themselves and their collegues at university
At least o eon thing they agree; they assume they aee both right
Because I live in both worlds, I am interested to see the real differences or notAnd one of the differences or not, is how scnetists as well astdatajournalists decide if they trust and use a dataset or not. And what I would like to discuss today is really just a startig point of this topic
So if you dig into the literature of the trustworthiness of data from the perspective of a scientists – you will find a broad variety of articles in different different scietif field. Anf it’s not easy to dtect a specific line in the ariety of articles n all these different field. And there is a lack in specific guidelines how scinetists determine the trustworthiness a scientist
And if you readscientifartciles about what makes a datasettrustworthy for journalists – you will find nothinhYou will only find general readings about the trustwothiness of a news source and general. Like the main principles of Gans. And a dataset could simply be one of these news sources. But on a literature level. Its is hard to compare
So, with no clear starting oint, it seemed right to start with a very general question. And that’s what I did. I asked ten of me scirntif as well a
Are the intentions of any influence on the dataset?
So they both use their collegues as peers
Using a dataaet from another source is not really common in social science -