Diffusion and adoption of research data management services

Pages117-133
DOIhttps://doi.org/10.1108/GKMC-05-2019-0057
Date06 September 2019
Publication Date06 September 2019
AuthorJinfang Niu
SubjectLibrary & information science,Information behaviour & retrieval,Information in society,Information literacy,Library & information services
Diusion and adoption of research
data management services
Jinfang Niu
School of Information, University of South Florida, Tampa, Florida, USA
Abstract
Purpose This paper aims to identifythe diffusion patterns, especially the communicationchannels, in the
diffusionand adoption of research data management services (RDMS) among libraries.
Design/methodology/approach Literature about the RDMS in individual librarieswas gathered and
analyzed.Data relevant to the research questions were extracted and analyzed.
Findings Early adopters conductmuch original research to create RDMS and they oftenserve as change
agents in diffusing their RDMS and related innovations to other libraries. Incontrast, late adopters usually
learn from early adopters and use their innovations for establishing their own RDMS. Communication
channels used in diffusing RDMS deviate slightly from those reported in general diffusion of innovations
(DOI) theories.
Research limitations/implications Gathered literatureprovides incomplete and uneven information
for RDMS adopters. This makes it difcult to identify adopter categories and test many generalizations in
DOI theories.To overcome these limitations, surveys and interviewswill be conducted in the future.
Originality/value Findingsfrom this project contribute to general DOI theories because RDMS is unique
compared with many other innovations. The diffusion of RDMS is a decentralized process that involves a
high-degree of reinvention and it involves the generation and diffusion of many relevant innovations. The
project also identied scholarly communication and inter-organization networks as new types of
communicationchannels that are not well accountedfor in existing DOI theories.
Keywords Libraries, Innovation, Diffusion of innovations, Research data management,
Communication channels
Paper type Research paper
Introduction
Over time, librariesand archives have experienced numerous cycles of innovations.Many of
these innovations improve existingoperations and services through new technologies, such
as library online public access catalogs (OPAC), online archival nding aids and digital
references services. Otherinnovations introduce new services that did not exist before, such
as institutional repositories. Technology is usually the driving force of library innovations.
In addition, government policies and economic pressures stimulate innovations as well
(Drake and Olsen, 1979).
During the past decade, research data management service (RDMS) has emerged as a
service innovation and diffusedamong university libraries and beyond[1]. RDMS, according
to the association of research libraries (ARL), includes providing information, consulting,
training or active involvement in data management planning, data management guidance
during research, research documentationand metadata, research data sharing and curation
(selection, preservation, archiving and citation) of completed projects and published data
(Fearon et al.,2013).The origin of RDMS can be traced to the development of e-science since
the end of the twentieth century. E-scienceproduces large quantities of data and makes the
management of research data a growing concern. Libraries, which have the tradition of
managing various kinds of information resources, are recognized as a natural t for RDM
Research data
management
services
117
Received10 May 2019
Revised4 June 2019
Accepted17 July 2019
GlobalKnowledge, Memory and
Communication
Vol.69 No. 3, 2020
pp. 117-133
© Emerald Publishing Limited
2514-9342
DOI 10.1108/GKMC-05-2019-0057
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2514-9342.htm
(Atkins et al., 2003;National Science Board, 2005). The development of RDMS was further
catalyzed by the funding agency requirement that data management plans (DMP) be
included in grant proposalsubmissions.
Numerous studies on RDMS havebeen published. Most of them are surveys, interviews,
participant observation and case studies of RDMS provided by libraries, RDM training
needed by librarians, and data management practices of researchers (Tenopir et al., 2012;
Tenopir et al.,2017;Reznik-Zellen et al., 2012;Yoon and Schultz, 2017;Briney et al., 2015;
Corrall et al.,2013;Brown et al., 2015;Chiware and Mathe, 2015). These studies mainly
report facts specic to particular libraries and researchers. Some articles present RDMS
models that are independent of individual cases. For example, Jones et al. (2013) developed
the components of RDM support services model that connects guidance, training and
support services to thedifferent stages of research. Pineld et al. (2014) developed a model of
institutional RDM that focuseson institutional drivers, stakeholders, inuencing factors and
program components. Thesemodels examine RDMS on an abstract level but are still bound
to a particular domain.Very few studies have examined RDMS through a generaltheoretical
framework that is independent of particular domains or disciplines. One such study was
conducted by University of Vermont librarianswho used the theory of planned behavior in
designing a survey questionnaire for evaluating researchersattitudes and beliefs towards
data management planning(Berman, 2017).
RDMS has been diffused among libraries for about a decade. The author believes it is
now a good time to look back and investigateits diffusion patterns. This paper will analyze
RDMS through the lens of the diffusion of innovation (DOI) theories. There are many
benets of examining RDMSthrough a general theoretical framework. As stated byRogers
(2003,p.12),the diffusion paradigm allows scholars to repackage their empirical ndings
in the form of higher-level generalizationsof a more theoretical nature.Thus, RDMS can be
understood in a more general context in comparison with the diffusions of innovations in
other elds. This information willnot only be useful to libraries but also stakeholders, such
as government agencies and professional associations who want to support innovations in
libraries, and also for vendorswho want to sell technology products to libraries. In addition,
DOI theories will be tested, and then conrmed, augmented or even refuted based on the
diffusion practicesin this particular eld.
Innovation studies in library and information science
Library and information science (LIS) researchers have conducted numerous studies to
investigate various issues related to the adoption of innovations among libraries. Many
studies attempted to identify factors that cause librarians or libraries to be more or less
innovative. For example, Howard (1981) tested the relationship between the structural
features of academic libraries, including complexity, centralization, formalization,
stratication and their innovativeness. Damanpour and Childers (1985) examined the effect
of the size of public libraries on their innovativeness. Jantz (2013,2015) reported the impact
of ve factors on the innovativenessof a research library, including strategy, organizational
structure and leadership. Leong and Anderson (2012)described a range of approaches used
by one academic library to increase its innovativeness. Goulding and Walton (2014) found
that distributed leadership couldhelp library services innovate. Luquire (1983) investigated
variables that affect librariansperceptions or evaluations of onlinecomputer library center
(OCLC) as an innovative system. Cervone (2007) studied the effect of individual librarians
professional advice networks on their innovativeness. Fowler (1998) investigated the
relationships between learning activitiesand the innovativeness of library work teams and
individual librarians. Xia (2012) applied the geographic concept of cultural diffusionism to
GKMC
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