Adopting a situated learning framework for (big) data projects

Adopting a situated learning
framework for (big) data projects
Martin Douglas
martin.douglas@cranfield.ac.uk

Research Design
 Phenomenon: Generating insight from Data
 Unit of Analysis: Data initiatives/Project Teams
 Approach: Ethnography
 6th months embedded at 2 contrasting cases
 (1) A district council seeking to use Acorn data
 (2) A rail project producing data to improve maintenance
(focus of this paper)
 Data collection
 Interviews, observation and artefacts
 Communities of Practice (CoP) mapping exercise for the rail case
 Data analysis
 Various strands aimed at reflection & reflexiveness
 Used CoP & Sensemaking for initial coding strand of analysis
© Cranfield University 2

Why we adopted a situated
learning COP lens
Various perspectives on generating insight adopt different units of analysis
We wanted to focus on situated individuals undertaking data projects/initiatives

Focusing on InfraDig Case
Producing a ‘Virtual Railway’ (data artefact) for operators
to improve maintenance practice/effectiveness

CoP mapping exercise
(an illustrative extract)
InfraDig
Used Prezi to map groups and identify boundaries, boundary spanners and related forums
Also captured tools/systems used, boundary artefacts and issues

Findings using CoP
 A focus on data collection, tools & artefacts
 Not how data will be USEd to improve maintenance
 Engagement focused on requirements definition, deliverables
 Various group/community issues emerged
 Operator maintenance, finance, sustainability teams or CoPs missing
 Groups involved had different ‘frames’ & agendas, e.g. Audit trail
 Several key boundary artefacts identified
 Contracts and Design Documentation itself
 ‘Virtual Railway’ data artefact for operators
 ‘Cross-border’ contractual alignment/incentive tensions
 Contractors – InfraDig – Operators
 Highlighted role of/reliance on cross-border ‘evangelists’

Discussion – Using COP
 Helps bound the research context
 Situates learning from data within a practice & USE context
 Highlights practitioner groups & boundary spanning
 Integrates knowledge, data and practice dimensions
 Useful socio material lens for examining artefacts & their role
 Connects well with Strategy-as-Practice, Socio-Materiality/Knowing work
 Points to value creation through practice improvement
 However: doesn’t address tensions with formal structures
 Helps identify Data as both a reification of knowledge and
boundary artefact
/...

Informs an emerging wider
Framework for Data Projects
Phenomenon
Data
Tools
Sensemaking
Artefacts
Engagement
Purpose
Learning
Knowledge
‘Frame’
Ques ons
(direct)
(indirect)
Document
Controllers
Asset Data
Team
IT
Func on
Design
Engineers
Operators
Maintenance
Finance, etc.
Contractors
&
Theory
Construc on
Maintenance

Discussion
– Data Project implications
.../
 Relationship between Data-Phenomenon-Practitioner(s)
emerges as KEY
 Projects can start with either but both are important
 Data a snapshot of what’s relevant about a phenomenon of interest
 Co-evolves with knowledge and practice (context specific)
 Points to importance of research, domain & tool knowledge
 Not just quantitative skills or ‘data scientists’

Conclusions
 For researchers:
 Clear value in using CoP framework for data research focused on
generating insight and how value is crystallised through use
 The framework presented can be used to position data research and
as a basis for further theorising about such initiatives
 Also value in engaging with Knowledge Management
and Organisational Learning fields for data insight work
 For practitioners:
 The framework is useful to help plan and articulate data projects,
addressing the elements highlighted and how value will be created
 Highlights the need to support boundary activities and practitioners

Adopting a situated learning framework for (big) data projects

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