Download The researcher`s perspective

Libraries and research data: Towards a new leadership role
LIBER conference workshop, London, June 2015
Andrew Cox
[email protected]
• Big business and highly competitive
• Project oriented
• Yet also very personal, often unfunded
• Symbolically significant – therefore raises issues of power and
identity
• Heavily evaluated and managed (according to some critics)
• A personal research plan aligned to that
of the department, faculty and funders
• An externally set research agenda
• Prefers applied research to conceptual and critical
research
• Targets of outputs, such as X peer
reviewed publications per anum
• “overextended,
underfocused,
overstressed and
underfunded”
(quoted in Becher
and Trowler, 2001)
• Preferred journal lists
• Evaluation of performance based on
• Income (despite dramatic disparities in available
research funding)
• Citation counts (even Altmetrics)
• Non-research active label could mean
heavy teaching load and block to
promotion
• Research is just one
part of the
academic’s role
• Applied research tackling
big societal challenges
• Interdisciplinary and
multidisciplinary
• Collaborative
• Involve Multiple institutions
• Have impact and community
engagement
• Open science
• Hard
• Risky
• Undermines criticality
• E-research and data
intensive science
• Crisis of replication: e.g.
psychology and
biomedicine
• Evidence that many
researchers need help
managing data: need
but no demand
• Answer: Not very much
• Funder policy driven by
need to justify research
spending to government
& the government’s
agenda is increasingly
economic benefit
• Compliance to a progressive policy narrative around RDM can
be seen as another threat to academic autonomy and identity
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End
• Many academics are deeply engaged with data issues
• Many academics are advocates of data sharing
• The over-taxed academic wants (timely, personalised) support
• The “performativity” critique is a bit extreme
• The natural scientist for whom data sharing is second nature
• The engineer working with corporate partners who want to
commercialise research outputs
• The medic who is acutely aware of information security issues
• The quantitative social scientist who re-uses government data as
a matter of course
• The qualitative social scientist who has concerns over re-use of
data by those who were not there at its collection
• The humanities scholar who never uses the term data (perhaps
genuinely does not have data)
•
•
•
•
“Volume, variety and velocity” … of researchers
Point of the disciplinary sub-culture is to be different
In flux
Centre of gravity of academic communities is beyond
institutional borders
• Cultural change means trying to influence communities whose
centre of gravity is outside the organisation
1. The domino conception, in which research is seen as an
ordered process in which different atomistic elements are
synthesised.
2. The layer conception, that sees research as more of a process
of uncovering layers to reach underlying meanings.
3. The trading conception, that sees research as about operating
in a kind of “social market place” and has a focus on products
such as projects and publications.
4. The journey conception, that sees research very much as a
personal, potentially transformational journey for the
researcher.
• Building empathy with the researcher’s experience
• Service development
• Pedagogic research
• Via professional
practices such as
collection, IL and the
reference inquiry
• CPD
• Aligns with the agenda
for research-based
practice in LIS
• How big are the data?
• “Big data, little data, no data” (Borgman, 2015)
• What are the data?
• Not always called “data”: eg “primary sources”
• Diverse: many different types and standards; print and digital
• Complex: The sound files of interviews, the transcripts, summaries of interviews,
notes on interviews, NVivo files???
• Complex: Assemblages of different forms of processed data, background
data, simulated data
• When are the data?
• Fleeting: “Moments of organisation” in a continuing flow of research activity
(Garrett et al., 2012)
• Where are the data?
• Mobile: (see Secret life of a weather datum,
https://secretlifeofdata.wordpress.com/blog/)
• Personal: The researcher’s “life work”
• Data are not (always) neat “things”
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End
• Ethnography: messy, non-linear realities
• Multi-sited
• Digital ethnography
•
Data leaking... Give away…
https://www.youtube.com/watch?v=N2zK3sAtr-4
The data is in the paper
– yes that is my
interpretation of the
topic
Have I published
everything I want
from this data myself
yet?
Who else would really
want this data
because its very
specific to my
research questions?
I wasn’t funded to do
this research… I wasn’t
funded to document the
data… what actually is
in this for me?
I don’t even know
where the data is…
which version is
quality checked?
I am not sure we followed
the methodology to the
letter – is this panda
going to check up on me?
I haven’t got time to
document the data fully…
anyway how could she
understand the data as
she wasn’t involved in
collecting it …?
What’s metadata?
My ethics application
didn’t mention data
sharing….I could go back
to the ethics committee
and then the participants but is it worth the hassle?
Could I be breaking
the DPA if I share this
data? Is it fully
anonymised?
The university tells me
they own the data…
how does that affect
whether I can share
it?
She has connections
with some companies
which frankly I am
suspicious of
Who might she share
the data with?
I’ve got to go and
teach class… and the
office are pestering
me for 150 exam
scripts to be marked…
• Concerns about “data sharing” are deep-seated
• Clarity about funder policy, institutional policy, the legal position –
acknowledging legitimate exceptions;
• Advocacy that recognises disciplinary differences;
• Prompts to plan data management and sharing from before the start of the
project;
• Advice around research ethics, at an early stage;
• Support with improving the data security of active data;
• Training in managing data and processing data for deposit; recognition of
these skills as part of standards of professionalism within research
communities;
• Places to deposit data that handle the legalities and effort around sharing;
Ability to control the release of data;
• Recognition of data deposit and citation as a contribution to knowledge and
impact;
• Help locating data sources researchers themselves could reuse.
Workshop
Libraries and research data: Towards a new leadership role
LIBER conference workshop, London, June 2015
Andrew Cox
[email protected]
RDM Insight
https://rdminsight.wordpress.com/