Going with the (work)flow: tailoring data management protocols to a
complex research cycle
Rachel Watson Crossroads Project, SOAS
University of Rio de Janerio, August 2017 [email protected] @casamance_owl
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researchers
participants
transcribers
corpus managers 4
AUDIO/VIDEO RECORDINGS multiple participant multiple languages
multiple format
METADATA (ARBIL) file name
date participants
subject
ANNOTATION (ELAN) transcription
translation language note
participant note
CORPUS
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TYPES OF DATA
elicitation interview
experiments narratives, demonstrations, ‘staged communicative events’
participant observation, ‘left’ camera lavalier mic data
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CORPUS searcheable findable! comprehensible
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Thieburger & Berez 2012
Thieburger 2004
Nathan 2008
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DATA MANAGEMENT WORKFLOW
collect data
create metadata and annotations
deposit in corpus
analyse
THE END 11
DATA MANAGEMENT WORKFLOW
collect data
create metadata and annotations
deposit in corpus
analyse
THE END
unknown people, places, languages/ time consuming/tired
travel/”real work”/transcription lag/ interfaces
searchability/access/harmonized metadata
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DATA MANAGEMENT WORKFLOW
collect data
create metadata and annotations
deposit in corpus
analyse
THE END
unknown people, places, languages/ time consuming/tired
travel/”real work”/transcription lag/ interfaces
searchability/access/harmonized metadata
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PRINCIPLES OF WORKFLOW DESIGN 1. Let the data management flow be dictated by the natural cycle of
research and field trips – not the other way round.
2. Where a task must be carried out in a very specific way by multiple team members, have documents detailing this process in explicit detail. If it doesn’t really matter how it is done, don’t bother.
3. Apportion tasks according to knowledge and expertise, but…
4. Ultimate overseeing of the data and metadata should be ceded to a central manager (we have two – one in London and one in Senegal)
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DATA MANAGEMENT WORKFLOW
collect data
create metadata and annotations
deposit in corpus
analyse
THE END 15
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PRINCIPLES OF WORKFLOW DESIGN 1. Let the data management flow be dictated by the natural cycle of
research and field trips – not the other way round.
2. Where a task must be carried out in a very specific way by multiple team members, have documents detailing this process in explicit detail. If it doesn’t really matter how it is done, don’t bother.
3. Apportion tasks according to knowledge and expertise, but…
4. Ultimate overseeing of the data and metadata should be ceded to a central manager (we have two – one in London and one in Senegal)
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Let the data management flow be dictated by the natural cycle of research and field trips – not the other way round.
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STILL TO WORK ON….
better system for metadata – particulalrly for participants system for being online
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Thank you
Crossroads Project team and collaborators Leverhulme Trust
British Academy IPM Scheme Bruna and Kris
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