To share or not to share: how
researchers handle data
Michael Jubb
RIN
Fourth Bloomsbury Conference: Valued Resources
24 June 2010
Some definitions
Data
‘evidence supporting research and scholarship’
DCC Charter and Statement of Principles
‘have no intrinsic meaning until converted into information
through some process of analysis, interpretation and description:
typically, the process by which experimental data become a
research paper’
Patterns of information use and exchange:case studies of
researchers in the life sciences, RIN 2009
researchers’ perspectives
skills and training
funder and institutional perspectives and
implications
1. Researchers’ perspectives
data and information in the research
process: some verbs
gather
evaluate
create
analyse
manage
transform
present
communicate
disseminate
But……….
gathering, creating, evaluating data not
usually the primary object of research
few career rewards from sharing data
how it’s done in different disciplines varies
greatly
big science not the norm
the research process: animal genetics
research process: transgenesis & embryology
research process: epidemiology
research process: neuroscience
why share?
completeness of the scholarly record
validation of results
re-use and integration
exploit what’s already been done
avoid duplication of effort
ask new research questions
researchers may have different interests as
creators and users
creators: motivations and constraints?
evidence of benefits
citation
esteem and
successful evaluations
funder requirements
altruism/reciprocity
cultural/peer pressures
enhanced visibility
opportunities for
collaboration, co-authorship
easy-to-do
no clear benefits/incentives
competition; resistance to
sharing intellectual capital
desire for/fear of
commercial exploitation
access restrictions desired
or imposed
legal, ethical problems
lack of time, funds,
expertise
practical and technical
difficulties
So do they do it?
80%
Percentage
60%
40%
20%
0%
Privately in ow n netw ork
Openly w ithin research
community
Publicly on a w ebsite or
blog
Degree of sharing
No
No, but I intend to in future
Yes
ownership, protection and trust
responsibility, protectiveness and desire for control
over data
concerns about inappropriate use
climate change data………..
preference for co-operative arrangements and direct
contact with potential users
decisions on when and how to share
commercial, ethical, legal issues
lack of trust in other researchers’ data
“I don’t know if they have done it to the same standards I would
have done it”
lack of standardisation
intricacies of experimental design and processes
some conclusions……
data are primary in the research process, but
secondary as research outputs
data management, curation and sharing not yet
embedded or the norm
genomics, bio-informatics, astronomy etc the exceptions
few career rewards from sharing data
resistance to open sharing of intellectual capital
real differences between researchers working in
different disciplines and contexts
impact of funder policies?
impact of FoI?
2. Training and skills
“This has been identified in every study as a major
problem, both training researchers to be eresearchers, and training the people running the
systems to deal with researchers, and to understand
the technology”
Researchers
“…a lot of scientists don’t get information and
structures at all. It’s not what they’re trained to
think about.”
“……..the idea of quality, provenance, and metadata
about data is woefully inadequate in most science
training.”
engagement between researchers and data
management professionals
“…….now we manage our data, whereas before we didn’t”
issues of scalability in training and support to meet
diverse needs of wide range of research groups
Curators
concern about low numbers of
people with specialist expertise
people from two kinds of
backgrounds
library/information professionals
researchers
need for co-ordination of effort
and funding for capacity-building
much depends at present on shortterm project funding
lack of career structure
“Who’s training these people?
We need training at the
professional level for people
who are actually going to run
these data centres”
“….the career structure for
those people with expertise is
miserable, because the
number of places they can
work is not large, and the
universities don’t treat them
as key staff”
“So there’s a real danger of
losing people to the private
sector”
some conclusions……
how to promote cultural change
building capacity and capability among both researchers
and information specialists
career paths and rewards
assessment of national requirement for skills
in data curation and support
3. Funder and institutional
perspectives and implications
Policy drivers
increasing the efficiency of the research process
avoid duplication
promoting scholarly rigour and enhancing research quality
review and testing of data
enhance scope and quality of the scholarly record
enabling researchers to ask new questions
re-use of data
development of ‘data-intensive science’
enhancing visibility of research
opening opportunities for engagement
“increasing the return on public investments in research”
OECD Principles and Guidelines for Access to Research Data 2007
Research Councils…..
BBSRC….. expects research data generated as a result of
BBSRC support to be made available with as few restrictions as
possible in a timely and responsible manner to the scientific
community for subsequent research
recognises that different fields of study will require different
approaches
expects that timely release would generally be no later than the
release through publication of the main findings
supports the view that those enabling sharing should receive full
and appropriate recognition by funders, their academic
institutions and new users for promoting secondary research
June 2010
Research Councils…….
NERC….requires that due consideration be given to the 'post
project' stewardship of data prior to approval being given for a
project
requires that recipients of NERC grants offer to deposit with
NERC a copy of datasets resulting from the research
supported, for research or other public good purposes, but
without prejudice to the intellectual property rights
ensures that individual scientists, principal investigator teams
and participants in programmes will be permitted a reasonable
period to work exclusively on, and publish the results of, the
data they have collected
Updated Feb 2010
Wellcome Trust
…..considers that the benefits gained from research data will be
maximised when they are made widely available to the
research community as soon as feasible, so that they can be
verified, built upon and used to advance knowledge.
….expects the researchers that it funds to maximise the
availability of research data with as few restrictions as possible
…..believes that data sharing for the benefit of the research
community as a whole will only proceed if those using the data
also adopt good research practice.…… [and] expects all users of
data to acknowledge the sources of their data and abide by the
terms and conditions under which they accessed [them].
2007
But do the policies work?
funding and infrastructure
compliance and engagement with
researchers
building an infrastructure: leadership
and co-ordination?
“….we need a more co-
co-ordination between different
funding bodies
Research Councils, Higher Education
funding bodies, JISC, universities
clarity about roles and
responsibilities
piecemeal initiatives with limited
take-up and impact
infrastructure ‘driven by the science’?
need for careful management of
relationships between specialists and
researchers
disciplinary and institutional
dimensions of scale and complexity
dangers of “solutions looking for
problems”
ordinated strategy and real
leadership to take things
forward.”
“…..it’s very easy in the current
framework to pass the buck and
do nothing.”
“Things are funded in silos. So I
just don’t think there is really a
national strategy.”
“…….you have to work pretty
hard to demonstrate there’s a
business case for reuse of
data………there’s no point in
paying to curate and store data
if nobody ever does use it
again.”
top-down and/or bottom-up: a real
tension
bottom-up
develop policies and local services in response to what
researchers themselves want
develop tools and environments within universities to
equip the research community with appropriate processes
and skills
top-down
national policy frameworks
national body/programme to catalyse change required for
sustainable and ubiquitous service
Some policy and service implications…….
policies and services need to be informed (but not determined) by an
understanding of the views and practices of researchers
different communities and contexts
single, one-size-fits-all approach won’t work
engagement with researchers
to identify and address constraints
to preserve exercise of informed choice
pragmatic and experimental policies
build on informal sharing already taking place
recognition of mutual needs
practicalities of sharing
what makes data intelligible and usable?
when is sharing useful enough to warrant the labour necessary to achieve it?
address barriers as well as drivers for change
incentives, self-interests and goals of researchers
sustaining of intellectual capital
professional recognition and reward structures
Some policy and service implications…..
the funding and sustainability challenge
sharing is not cost-free
co-operation needed between researchers, funders,
institutions
complexities of the dual support system
benefits and evidence of value
are the benefits realised in practice?
does making it available mean that it’s used?
scope for publishers to promote sharing?
carrots as well as sticks?
Questions?
Michael Jubb
www.rin.ac.uk