knowledge transfer at the canadian research data centre network
DESCRIPTION
2013 Canadian Knowledge Mobilization Forum Sarah Fortin Knowledge Transfer Coordinator Canadian Research Data Centre Network (CRDCN)TRANSCRIPT
Sarah Fortin
Knowledge Transfer Coordinator
Canadian Research Data Centre Network (CRDCN)
2013 KT Forum
Mississauga, June 3-4 2013
Knowledge Transfer at the
Canadian Research Data Centre Network
Today’s Presentation
What is the CRDCN?
CRDCN specific challenges in knowledge transfer (KT)
What did we do?
Any lessons?
What is the CRDCN?
25 Research Data Centres (RDC) or branches (2000-)
A secured facility housing Statistics Canada microdata files for
research purposes: longitudinal and transversal surveys; census;
administrative data
located on a university campus
directed by a faculty member
staffed by a StatCan analyst
operated under Statistics Act ( “deemed employees”)
fully equipped for data analysis
researchers with an approved project
The CRDCN in 2013
What is the CRDCN?
Main Partners:
Universities; Statistics Canada (Micro Access Division); Social
Sciences and Humanities Research Council (SSHRC); Canadian
Institutes for Health research (CIHR)
Staff (2+ EFT):
Executive director; network coordinator (2010); knowledge transfer
coordinator (2006), webmaster
Mandate (2002-)
Improve data access
Expand the pool of trained quantitative researchers
Make research count
Making Research Count: What Did we Do?
Three Periods:
2003-2006: early years
annual conferences
2006-2011: stepping stones
KT Coordinator; website
2011- : consolidation
Strategic plan
KT and traditional communication issues
synthesis; webinars; new social media
Making Research Count: Four challenges
1. not mandated to develop a research agenda.
The research carried on through the Network is not restricted to one issue, but rather
covers very diverse fields and involves several disciplines.
2. it is an infrastructure, similar to some extent to a library.
The Network is not, intuitively, thought of as an organisation that should do knowledge
transfer.
3. research output is not user-friendly.
Social statistics is not easy for non-experts to understand and requires sophisticated
capacities to fully appreciate its contribution.
4. the Network is decentralized
makes it more difficult to develop mechanisms for reporting/monitoring outputs to allow
doing KT activities on a timely basis at the Network level
Making Research Count: What Did We Do?
Reaching Out
Annual conferences: researchers and policy makers (2003-)
Bilingual Website (www.rdc-cdr.ca) and online bibliography (2009)
CRDCN publications and activities:
Knowledge syntheses: policy implications and research gaps (2008,2013)
Research Highlight: Two-page summaries (2010-)
Webinars (2012-)
Annual conferences: output (2011-)
Making Research Count: What Did We do?
Reaching In
Strategic Plan (2011): CRDCN identity (‘branding’) is weak
It is not easy to explain what it is and to distinguish it from Statistics Canada and from its
constituents (RDCs)
Presence of two logos and several websites and absence of mutual linkages among
them
The research output is not easily recognizable as a CRDCN output
Need to reinforce inreach among RDCs users themselves
Will in turn facilitate KT undertakings in the long run.
Making Research Count: Reaching In
Internal communication and visibility issues (2012-)
The Networker: quarterly newsletter (2012-)
Website Connection with Statistics Canada and RDCs
Logo
Connection & partnership with compatible research groups and
organizations: CHNET-works; CLSRN; CEA; PLCC; IRPP…
Promotional material: flyers, posters
Twitter; YouTube
Further developments on the website
Making Research Count: KT Models
KT = means and processes that facilitate the uptake of research
evidence by decision makers and practitioners.
Two models:
Traditional rational-linear model: from research producers to research users
cast the problem as one of lack of connection between these two
communities. (Davies et al., 2008)
KT plan must identify who will benefit from the research, how they will
benefit, and what needs to be done to ensure that they do benefit from
research (Ward et al., 2010).
inform potential users of research results in an accessible format.
Iterative or “co-production” model: involving both researchers and users
“knowledge is created through social interactions” (Davies et al.)
“The exchange, synthesis and ethically-sound application of knowledge –
within a complex system of interactions among researchers and users – to
accelerate the capture of the benefits of research for Canadians…” (Graham
et al. 2006: 15)
Making Research Count: KT as a Continuum
These models are not mutually exclusive: moving towards greater
interaction
Among peers KT: Teaching; academic publishing; congress
End-of-project KT: Highlights; Syntheses; participation of users in
conferences
Front-end-KT: Integration of users from the very beginning of the
research process
Making Research Count: Some Metrics
CRDCN Website Activity, 2010- 2012 (N)
Webinars: registration (up to 170) and participation (up to 85)
Health related with CHNET-works
Newsletter: + 1,800 subscribers
New social media
Year Visits Downloads Outgoing links
2010 8,925 457 3,619
2011 20,457 1,300 5,375
2012 28,724 2,385 7,020
Making Research Count: Lessons?
Carefully assess your available resources and use them strategically
CRDCN Knowledge synthesis
Strategic Plan
Whenever possible: Change the incentives
Intro of output measurement into calculation of funding formula
Online questionnaires
Reaching in and reaching out
Break silo approach
Quality and effective KT takes time and resources: be ambitious in your
aims but modest in your expectations!
Thank you!
Visit our website at : www.rdc-cdr.ca
Subscribe to The Networker, our newsletter, on
the home page
Contact me at: [email protected]
Follow us on Twitter at
https://twitter.com/CRDCN
Visit us on You Tube at
http://www.youtube.com/user/TheCRDCN
References
Davies, Huw; Sandra Nutley; and Isabel Walter. 2008. “Why ‘knowledge Transfer’ is Misconceived f
or Applied Social Research,” Journal of Health Services Research and Policy, Volume 13,
Number 3, pp.188-190.
Graham, Ian D.; Jo Logan; Margaret B. Harrison; Sharon E. Straus; Jacqueline Tetroe; Wenda
Caswell; and Nicole Robinson. 2006. “Lost in Knowledge Translation: Time for a Map?,”
The Journal of Continuing Education in the Health Professions, Volume 26, Number 1, pp.
13–24.
Ward, Vicky; Simon Smith; Robbie Foy; Allan House; and Susan Hamer. 2010. “Planning for
Knowledge Translation: A Researcher's Guide,” Evidence and Policy: Volume 6, Number 4,
pp. 527-541.