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“Um, yeah [laughs]”
Challenges in opening up qualitative research data
Paula Goodale ¦ Information School ¦ University of Sheffield
@PaulaGoodale ¦ @LifeOfData
#iFutures 7/7/15
The Secret Life of a Weather Datum
www.lifeofdata.org.uk
Four contrasting, but inter-connected case studies
Data Production
Citizen Science Financial Markets
Climate Science
Thematic analysis
Policy issues
The journey of
the weather
datum
Socio-cultural
values
Open research data:
Web site, online data archive
Image: Jonathan Gray [Flickr]
Data collection:
“The best laid plans of mice and men…”
Data collection:
“Nothing to see here…”
Data collection:
Controlled access
Open research data:
Which data? Which licence?
Anonymising participants:
“Who’s that girl [boy]?”:
Redactions:
Commercially sensitive information, controversial points of view,
humour, personal information about 3rd parties
Modifications:
Personal & professional opinions. criticisms, humour,
3rd party anonymisation, clarifications…
“Umm, yeah [laughs]”
(or, a transcript is a transcript, is not a transcript…)
Audio:
All or nothing
No audio
Full audio
Clips
“Our technology, our machines, is part of our humanity. We created them to extend
ourselves, and that is what is unique about human beings.” (Ray Kurzweil)
People and places:
Individual permissions, public spaces
Lessons learned [1]: informed consent
Make sure participants read and understand the small print!
I have read the small print
Lessons learned [2]: Put yourself in their shoes…
No ‘one-size-fits-all’
Lessons learned [3]: Compromise
Some open data better than no open data?
Would I do it again?
$1 million
question?

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Challenges in opening up qualitative research data

Editor's Notes

  1. Limited advance notice of interviewees No / limited observation Accompanied by the press officer Use of powerpoint to steer the narrative No video
  2. Transcripts, audio recording of interview, photos, observation notes Full text/audio and quotes/clips Usage Attribution-Noncommercial-No Derivative Works 3.0
  3. Anonymising participants Person level – option – full details inc. name, title/org, org only, full anonymisation Some organisations could not be anonymised – e.g. the Met Office Citizens, academics, weather station not anonymised – Met Office, commercial, govt – mostly anonymised
  4. Not deleted, but changed in some way
  5. Figures of speech, colloquialisms, hesitations,
  6. Black and white Make sure they read and understand Follow up on permissions/multimedia release sooner rather than later Keep good records
  7. Citizens vs academics, vs scientists vs govt vs commercial Disciplinary differences Level of formality Level of risk
  8. Negotiate, compromise, flexibility, some data better than no data? We archived 73 images (most), 10 transcripts (half) and 5 audio files (quarter) – some edited