Knowledge Transfer at the Canadian Research Data Centre Network

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Information about Knowledge Transfer at the Canadian Research Data Centre Network
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Published on June 19, 2013

Author: ckforum

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2013 Canadian Knowledge Mobilization Forum
Sarah Fortin
Knowledge Transfer Coordinator Canadian Research Data Centre Network (CRDCN)

Sarah FortinKnowledge Transfer CoordinatorCanadian Research Data Centre Network (CRDCN)2013 KT ForumMississauga, June 3-4 2013Knowledge Transfer at theCanadian Research Data Centre Network

Today’s PresentationWhat 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 forresearch purposes: longitudinal and transversal surveys; census;administrative datalocated on a university campusdirected by a faculty memberstaffed by a StatCan analystoperated under Statistics Act ( “deemed employees”)fully equipped for data analysisresearchers with an approved project

The CRDCN in 2013

What is the CRDCN?Main Partners:Universities; Statistics Canada (Micro Access Division); SocialSciences and Humanities Research Council (SSHRC); CanadianInstitutes for Health research (CIHR)Staff (2+ EFT):Executive director; network coordinator (2010); knowledge transfercoordinator (2006), webmasterMandate (2002-)Improve data accessExpand the pool of trained quantitative researchers Make research count

Making Research Count: What Did we Do?Three Periods:2003-2006: early years annual conferences2006-2011: stepping stones KT Coordinator; website2011- : consolidation Strategic plan KT and traditional communication issues synthesis; webinars; new social media

Making Research Count: Four challenges1. not mandated to develop a research agenda.The research carried on through the Network is not restricted to one issue, but rathercovers 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 knowledgetransfer.3. research output is not user-friendly.Social statistics is not easy for non-experts to understand and requires sophisticatedcapacities to fully appreciate its contribution.4. the Network is decentralizedmakes it more difficult to develop mechanisms for reporting/monitoring outputs to allowdoing KT activities on a timely basis at the Network level

Making Research Count: What Did We Do?Reaching OutAnnual 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 InStrategic Plan (2011): CRDCN identity (‘branding’) is weakIt is not easy to explain what it is and to distinguish it from Statistics Canada and from itsconstituents (RDCs)Presence of two logos and several websites and absence of mutual linkages amongthemThe research output is not easily recognizable as a CRDCN outputNeed to reinforce inreach among RDCs users themselvesWill in turn facilitate KT undertakings in the long run.

Making Research Count: Reaching InInternal communication and visibility issues (2012-)The Networker: quarterly newsletter (2012-)Website Connection with Statistics Canada and RDCsLogoConnection & partnership with compatible research groups andorganizations: CHNET-works; CLSRN; CEA; PLCC; IRPP…Promotional material: flyers, postersTwitter; YouTubeFurther developments on the website

Making Research Count: KT ModelsKT = means and processes that facilitate the uptake of researchevidence 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 twocommunities. (Davies et al., 2008) KT plan must identify who will benefit from the research, how they willbenefit, and what needs to be done to ensure that they do benefit fromresearch (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 – toaccelerate the capture of the benefits of research for Canadians…” (Grahamet al. 2006: 15)

Making Research Count: KT as a ContinuumThese models are not mutually exclusive: moving towards greaterinteractionAmong peers KT: Teaching; academic publishing; congressEnd-of-project KT: Highlights; Syntheses; participation of users inconferencesFront-end-KT: Integration of users from the very beginning of theresearch process

Making Research Count: Some MetricsCRDCN Website Activity, 2010- 2012 (N)Webinars: registration (up to 170) and participation (up to 85)Health related with CHNET-worksNewsletter: + 1,800 subscribersNew social mediaYear Visits Downloads Outgoing links2010 8,925 457 3,6192011 20,457 1,300 5,3752012 28,724 2,385 7,020

Making Research Count: Lessons?Carefully assess your available resources and use them strategicallyCRDCN Knowledge synthesisStrategic PlanWhenever possible: Change the incentivesIntro of output measurement into calculation of funding formulaOnline questionnairesReaching in and reaching outBreak silo approachQuality and effective KT takes time and resources: be ambitious in youraims but modest in your expectations!

Thank you!Visit our website at : www.rdc-cdr.caSubscribe to The Networker, our newsletter, onthe home pageContact me at: sarah.fortin@crdcn.orgFollow us on Twitter athttps://twitter.com/CRDCNVisit us on You Tube athttp://www.youtube.com/user/TheCRDCN

ReferencesDavies, Huw; Sandra Nutley; and Isabel Walter. 2008. “Why ‘knowledge Transfer’ is Misconceived for 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; WendaCaswell; 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 forKnowledge Translation: A Researchers Guide,” Evidence and Policy: Volume 6, Number 4,pp. 527-541.

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