Knowledge management, research data management, and university scholarship. Towards an integrated institutional research data management support-system framework

DOIhttps://doi.org/10.1108/VINE-07-2014-0047
Date10 August 2015
Pages344-359
Publication Date10 August 2015
AuthorJoyline Makani
SubjectInformation & knowledge management,Knowledge management,Knowledge management systems
Knowledge management,
research data management, and
university scholarship
Towards an integrated institutional research
data management support-system framework
Joyline Makani
Killam Library, Dalhousie University, Halifax, Canada
Abstract
Purpose – The purpose of this paper is to synthesize existing research on research data management
(RDM), academic scholarship and knowledge management and provide a conceptual framework for an
institutional research data management support-system (RDMSS) for systems development,
managerial and academic use.
Design/methodology/approach Viewing RDMSS from multiple theoretical perspectives,
including data management, knowledge management, academic scholarship and the practice-based
perspectives of knowledge and knowing, this paper conceptually explores the systems’ elements needed
in the development of an institutional RDM service by considering the underlying data discovery and
application issues, as well as the nature of academic scholarship and knowledge creation, discovery,
application and sharing motivations in a university environment.
Findings – The paper provides general criteria for an institutional RDMSS framework. It suggests
that RDM in universities is at the very heart of the knowledge life cycle and is a central ingredient to the
academic scholarships of discovery, integration, teaching, engagement and application.
Research limitations/implications – This is a conceptual exploration and as a result, the research
ndings may lack generalisability. Researchers are therefore encouraged to further empirically
examine the proposed propositions.
Originality/value – The broad RDMSS framework presented in this paper can be compared with the
actual situation at universities and eventually guide recommendations for adaptations and (re)design of
the institutional RDM infrastructure and knowledge discovery services environment. Moreover, this
paper will help to address some of the identied underlying scholarship and RDM disciplinary divides
and confusion constraining the effective functioning of the modern day university’s RDM and data
discovery environment.
Keywords Knowledge management success factors, Knowledge management,
Knowledge integration, Knowledge management systems, Research data management,
Data management systems
Paper type Conceptual paper
Introduction
Universities today are:
[…] the wellspring of knowledge and understanding. And as long as scholars are free to pursue
the truth, wherever it may lead, there will surely continue to be a ow of new scientic
knowledge (Vannevar Bush, former president of the Massachusetts Institute of Technology, as
cited by Boyer, 1992).
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0305-5728.htm
VINE
45,3
344
Received 14 July 2014
Revised 17 February 2015
Accepted 6 April 2015
VINE
Vol.45 No. 3, 2015
pp.344-359
©Emerald Group Publishing Limited
0305-5728
DOI 10.1108/VINE-07-2014-0047
This viewpoint is evidenced by the heightened importance being placed by the
academic, government and industry communities on the long-term economic value of
effectively managing research data produced by researchers in universities (Belter,
2014;Wilson and Jeffreys, 2013). The focus today is on the theoretical and practical
aspects of research data management (RDM) as a prominent part of the research
productive landscape and an expected part of academic institutional organizations
(Wilson and Jeffreys, 2013;Patrick and Wilson, 2013;Government of Canada, 2013).
Several recent papers have begun to explore RDM in the disciplinary context (Tam et al.,
2014), and a number of communities are reported making progress in developing
discipline-specic data services (Wilson and Jeffreys, 2013;Gazit et al., 2013). However,
there is a signicant research gap on integrated cross disciplinary institutional
framework and supporting systems for “storing, sharing, and publishing data; for data
discovery; or for data verication” (National Data Service, 2014). More importantly, to
the author’s knowledge, not much research has been done on, for example, RDM
systems, standards, tools and the development of management language that can span
across disciplinary boundaries. The author believes this gap makes it difcult for
cross-disciplinary researchers to discover data, build on prior research and create new
knowledge. Needless to say “the promise of the data revolution – for rapid discovery,
cross-disciplinary research and increased reproducibility – remains largely unfullled”
(National Data Service, 2014).
In this article, data management is explored in the context of the knowledge
management triad, i.e. the data, information and knowledge (DIK) discourse. The author
takes the position that RDM in universities is at the very heart of the knowledge life
cycle and is a central ingredient to the scholarships of discovery, integration, teaching,
engagement and application. It is the author’s argument that effective RDM is one that
gives to innovative, diverse knowledge discoveries, knowledge use and knowledge
reuse. But for research data to be of value to a diverse user group, an institutional data
management framework has to be in place. In fact, research data are more valuable if its
management parameters, e.g. access, curation and verication parameters are
institutionalized at the systemic level, i.e. in the RDM’s “capacity to handle diversity and
dissensus, rather than simply at the componential level in terms of externally dened
variety of [discipline specic data sets] resources” (Spender, 1998). More importantly,
core to knowledge discovery, knowledge use and knowledge reuse at research
universities is the acknowledged need for scholars to access and produce data that are,
as Schon (1995) stated, “testably valid, according to criteria of appropriate academic
rigor and their claims to knowledge must lend themselves to intellectual debate within
academic (among other) communities of inquiry)”. Thus, the question that needs to be
answered at the institutional level is what are these so called “claims to validity and
criteria of appropriate rigor”? To answer this question, the author believes it is
important that we understand the forms of scholarship in the current research
university environment. In other words, we need to decipher what conceptions count as
legitimate knowledge in research universities today “how you know what you claim to
know” (Schon, 1995).
In this article, the initial steps are taken to gain an understanding of the systems
needed in the development of an optimal institutional RDM service by considering the
underlying data discovery, use and reuse issues, as well as the nature of academic
scholarship and knowledge creation, application and sharing motivations in a
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Knowledge
management

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