Review Article
Shifting Horizons: A Literature Review of Research
Data Management Train-the-Trainer Models for Library and Campus-Wide Research
Support Staff in Canadian Institutions
Dr. Felicity Tayler
Research Data Management Librarian
University of Ottawa
Ottawa, Ontario, Canada
Email: ftayler@uottawa.ca
Maziar Jafary
PhD Candidate and Part-Time Professor
School of Sociological and Anthropological Studies
University of Ottawa
Ottawa, Ontario, Canada
Email: Mjafary@uottawa.ca
Received: 4 Aug. 2020 Accepted: 16 Nov. 2020
2021 Taylor and Jafary. This
is an Open Access article distributed under the terms of the Creative Commons‐Attribution‐Noncommercial‐Share Alike License 4.0
International (http://creativecommons.org/licenses/by-nc-sa/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly attributed, not used for commercial
purposes, and, if transformed, the resulting work is redistributed under the
same or similar license to this one.
DOI: 10.18438/eblip29814
Abstract
Objective –
In consideration of emerging national Research Data Management (RDM) policy and
infrastructure, this literature review seeks answers to the following
questions:
1)
What
is the most effective way for a Canadian research university to build capacity
among library and campus-wide research support staff, with a view towards
providing coordinated RDM support services for our researcher community?
2)
What
international training models and course offerings are available and
appropriate for a local context?
3)
What
national guidelines and best practices for pedagogical design and delivery can
be adapted for a local context?
Methods – This
literature review synthesizes a total of 13 sources: 9 articles, 2 book
chapters, and 2 whitepapers. The whitepapers were selected for a narrative
literature review because of their focus on case studies detailing
train-the-trainer models. Within the 13 sources we found 14 key case studies.
This review serves as a supplement to the 2017 CARL Portage Training Expert
Group white paper, “Research Data Management Training Landscape in Canada,” the
focus of which was to identify RDM training gaps in order to recommend a
coordinated approach to RDM training in a national environment.
Results – The
narrative review of case studies revealed three thematic areas. Firstly,
pedagogical challenges were identified, including the need to target training
to RDM support staff such as librarians and researchers, as they comprise
distinct groups of trainees with divergent disciplinary vocabularies and
incentives for training. Secondly, the case studies cover a broad range of
pedagogical models including single or multiple sessions, self-directed or
instructor-led, in-person or online instruction, and a hybrid of the two.
Finally, RDM training also emerged as a key factor in community building within
library staff units, among service units on campus, and with campus research
communities.
Conclusion – RDM training programs
at local institutions should be guided by a set of principles aligned with the
training methods, modes of assessment, and infrastructure development timeline
outlined in a national training strategy. When adapting principles and training
strategies to a local context, the following trends in the literature should be
considered: librarians and researchers must have meaningful incentives to
undertake training in RDM or to join a community of practice;
disciplinary-specific instruction is preferable to general instruction; a
librarian’s own training opportunities will influence their ability to provide
discipline-specific RDM instruction to researchers; in-person training
opportunities improve learning retention and produce beneficial secondary effects,
whereas online instruction is most effective when paired with an in-person
component; generalized third-party RDM training should be adapted to local
context to be meaningful. Future directions for RDM training will integrate
into open access and digital scholarship training, and into cross-disciplinary,
open science communities of practice.
Introduction
This literature review was undertaken to help the Research Services
Division of the University of Ottawa Library determine effective training
methods for library and campus-wide research support staff, with a view towards
providing coordinated RDM support services for the researcher community. For
the last four years, University of Ottawa has held an annual, in-person,
campus-wide RDM training event, attended by researchers and a wider general
audience. The event was also attended by RDM-curious librarians and researchers
from other universities. By 2019 this event had gained national attention as
the Shifting Horizons training series. The 2020 edition presented a national
training program, developed through Canada’s CARL Portage Network. One of the
goals of the program is to provide basic RDM skills training for librarians and
for support staff in the Research Office, labs, faculty departments, and
Central IT. Despite the event’s success, the library’s Research Services
Division needed to evaluate whether a single annual event was the most
effective way to achieve the vision of campus-wide RDM awareness and a
coordinated service model. As was observed in the follow up documentation of
the event, the RDM Readiness
Report, the stakeholders of a coordinated RDM service model
at University of Ottawa continue to face the same challenges as those
identified by 241 librarians in a study by Tang and Hu (2019). Some of these
challenges include issues with staffing and upskilling, promotion of the
service, service quality, and shared understanding among campus
departments.
Aims
The articles reviewed here supplement the CARL Portage Training Expert
Group white paper, “Research Data Management Training Landscape in Canada” (Fry
et al., 2017). The purpose of this white paper was to identify “significant
issues and gaps in RDM training in Canada” and to recommend a national,
coordinated approach to RDM training (Fry et al., 2017, p. 2). This
recommendation is driven by the understanding that expertise in data
stewardship is unevenly distributed across higher education institutions and is
often isolated within disciplinary areas. In contrast to RDM infrastructures
elsewhere, which cohere around disciplinary or national service centres, a critical mass of RDM expertise in Canada is
organized within the academic library community. To date, this report’s
holistic multi-platform vision of a coordinated national training curriculum,
to level the “playing field” has been enacted in a modest capacity through best
practices, data primers and ad-hoc webinar training, supplemented by
single-day, in-person sessions reflecting the individual expertise of members
of the Portage Training Expert Group (Fry et al., 2017, p. 7). The day-long
training event at University of Ottawa, led by James Doiron, who is both an
author of the training landscape white paper and the RDM Services Coordinator
at the University of Alberta Libraries, is one example of the in-person
sessions currently offered through CARL Portage. Once an institution has
participated in the training, the next steps are unknown. For example, there is
no clear direction, recommended strategies, or coordinated curriculum
resources, at the national level, to support the long-term development of
highly qualified personnel (HQP) providing RDM services at libraries selected
to play a leadership role in this area.
Methods
This literature review synthesizes a total of 13 sources, including 9
articles, 2 book chapters, and 2 whitepapers from a larger sample of 35 texts
published within the last ten years (2010-2020). The authors cited seven
additional supporting sources in the analysis in order to provide the
contextual framing for the thematic approach of this narrative review. Keyword searches
such as “research data management (and) training” were undertaken in databases
including LISTA and Library and Information Science Source. Because RDM
training is an emerging field, contingent upon variable jurisdictional
challenges, policy, and funding environments, the aim was not to be exhaustive,
nor systematic in our searches. Instead, a “snowball” search for key articles,
white papers, and reports shared by colleagues on RDM-themed listservs such as
CANLIB-DATA, or IASSIST, or referenced at annual RDA Plenaries supplemented
these keyword database searches. In addition to the snowball searching, the
authors contacted various content experts to review the abstracts collected to
ensure that no important sources were missed. Though the number of sources
reviewed is minimal, this is an indicator that RDM is an emerging area of
librarianship, which is also interdisciplinary in nature. There are simply not
that many articles out there yet, and this literature review aims to address
this gap while recognizing that there is still work to do in this area.
In the 13 sources selected for synthesis, we found 14 key cases for analysis.
Out of the 13 sources selected for synthesis, as outlined above, 9 of the
selected sources had a single case study focus (Baker et al., 2016; Grootveld & Verbakel, 2015;
Haddow, 2014; Helbig, 2016; Papadopoulou
& Miller in Clare et al., 2019; Papadopoulou
& Grabauskiene in Clare et al., 2019; Wittenberg
et al., 2018; Southall & Scutt,
2017; Read et al., 2019). Out of the original 13, 2 of the selected sources
covered multiple case studies (Bryant et al., 2018; Surkis
& Read, 2015), while 2 of the sources dealt with the same case study (Tang
& Hu, 2019; Shipman & Tang, 2019). In choosing the case
studies, the authors prioritized European, North American, and Australian
examples as their social and academic contexts are comparable to those of
Canada. However, this geographic limitation and focus on English-language
sources introduces a bias to this review. This selection bias does not reflect
a deliberate exclusion of other regional models, rather it echoes a trend to
build Canadian digital research infrastructure on existing models such as the European Open Science Cloud (EOSC), or to look to best practices in RDM established by the Digital
Curation Centre in the UK, and American RDM
service models as outlined by OCLC.
Results
The review of the literature is divided into three sections, reflecting
themes within the articles and case studies. The first section discusses
challenges and opportunities for RDM training in universities. Outreach and
pedagogical issues were identified by several authors, including the
development of targeted RDM training to two distinct groups of trainees: RDM
support staff, including librarians, and researchers. These two groups differ
in their incentives for training participation and their use of discipline-specific
vocabulary. With these challenges in mind, the evaluation of training models
for success and areas of improvement will be discussed. The second section
explains different approaches to curriculum and pedagogical design in RDM
training. The case studies cover a range of pedagogical models and whenever
possible evaluations of these training methods and formats of pedagogical
engagement for RDM training are highlighted. Finally, the third section looks
at how RDM training operates as a means of community building within library
staff units, between service units on campus, and within campus research
communities. This final section also covers internal and external partnerships
which are necessary to develop RDM training.
Discussion
Challenges and Opportunities for RDM Training in Universities
While many of the texts that were retrieved in the searches addressed
developing RDM services around best practices, or outlined approaches for
broader data literacy training strategies, this literature review focuses on
train-the-trainer models as a unique subset of the RDM training landscape.
Because the literature in this area is emerging, this review presents a
combination of conclusions drawn from train-the-trainer models alongside
approaches to training researchers. In a train-the-trainer model, the targeted
audience of trainees are librarians and other research support staff. In the
researcher trainer model, the targeted audience members are typically faculty,
student research assistants, and other affiliates of disciplinary research
projects. However, in practice the line between these roles is blurry, as
trainers often become a secondary audience of the training for researchers, and
researchers can also benefit from train-the-trainer sessions as they can
perform a trainer role as part of their own research team. Furthermore, as this
review demonstrates, there is a correlation between the pedagogical model
applied to train-the-trainer sessions and the effectiveness of these trainers
to then shape learning experiences for researchers. By outlining the challenges
to providing RDM training to researchers in this section, the recommended
best-practices can inform approaches to train-the-trainer models. We begin with
the principle that RDM is not generic. Instead, librarians and other research
support staff need a fundamental understanding of how data flows and data
management differ between disciplinary research methods, and how to recommend
relevant engagement with local, national, and international infrastructure
contexts.
RDM training for librarians and other research support staff will have
an impact on the success of RDM services delivered. Both Tang and Hu (2019) and
Surkis and Read (2015) identify significant barriers
and pedagogical challenges of RDM training for librarians and other research
support staff, beyond the administrative concerns of budget and capacity. For
example, librarian language and vocabulary does not translate well to the
disciplinary environment of researchers and other stakeholders. Such
specialized RDM vocabulary might not be well received or even understood by
researchers. Another challenge could be a lack of training for librarians and
research support staff on different approaches to research data management
within the field of study, as defined by the researchers’ peers and funding
bodies. Tang and Hu’s (2019) needs assessment highlighted the need for key
training in strategic communication of RDM service models to library and
university administration, while Surkis and Read
(2015) instead stress that when the goal is the improvement of training
offerings for researchers, instructors from the library sector (and related
fields), as part of their own training, should engage in interviews with
researchers in different fields. This exercise would help librarians better
understand researchers’ needs and expectations from RDM services. A later study
by Read et al. (2019) further explored this lack of disciplinary knowledge as a
high barrier to librarian engagement with RDM services in biomedical fields,
due to a “lack of comfort engaging with researchers” (p. 2). Read et al. (2019)
also noted a double gap in the training landscape, identifying that a “lack of
satisfactory curricula” (p. 2) to train both librarians and researchers
in RDM further contributed to the lack of RDM service offerings in biomedical
fields.
Engaging Researchers with Data Management: The Cookbook (Clare et al., 2019), includes several case studies of RDM engagement
and collaborations among researchers. The case studies demonstrate how
librarians and other research support staff with disciplinary awareness can
encourage researchers to consider research data management practices and
services as an extension of their disciplinary peer communities. In one of the
chapters focusing particularly on RDM training, Papadopoulou
and Miller evaluate the format of training “mini-events” for their impact on
building a community of RDM supports and data management best practices at the
Vilnius University Library in Lithuania. Each of these mini-events (delivered
either as half-day or full-day workshops) consisted of three incremental
phases: familiarity of the participants with RDM support services; learning how
to use various available tools; sharing research data in practice (Papadopoulou & Grabauskiene,
2019). Papadopoulou and Grabauskiene
specify that one of the challenges faced by these RDM training sessions is
reaching out to, and persuading, the uninterested researchers to attend. One
proposed strategy is to do peer outreach rather than through a generic unit,
such as Information Services. Secondly, based on their study of a conference at
the University of Edinburgh, Papadopoulou and Miller
propose that the events should include presentations by researchers from
multiple university faculties. Such presentations might discuss RDM best
practices and their impact on researchers’ work, thereby encouraging their
disciplinary peers to participate. Thus, the presentations can also be
interactive sessions among the researcher peers themselves (Papadopoulou
& Miller, 2019).
Approaches to Research Data Management Training
The previous section outlined challenges of RDM training such as the gap
in terminology shared by research support staff and the researcher community
that they support, and the researchers’ lack of interest in RDM if it is
perceived to be beyond the scope of methodologies shared by their disciplinary
community. These challenges support the Research data management training
landscape in Canada: A white paper finding that pedagogical design needs to
me mapped to trainee needs and is a necessary learning objective for librarians
and other research support service providers (Fry et al., 2017). This review
has revealed multiple approaches to RDM training, specific to the trainee
contexts. Although we focus here on librarians and other research support staff
as “trainees”, it is with an understanding that their training opportunities
have an impact on the quality of RDM training and service provision available
to researchers. Further, this review notes several approaches to pedagogical
design for RDM training, which can be broadly categorized as: generalized
instruction or discipline-specific, single or multiple sessions, self-directed
or instructor-led, in-person or online instruction (and most often, a hybrid of
the two).
The literature shows that there are significant advantages to delivering
discipline-specific or targeted RDM training. However, a generalized approach
to RDM training may be favoured due to perceived scalability. As mentioned, Read et al. (2019) note that available online training for
librarians is inadequate to build RDM service capacity in biomedical fields, as
none have the necessary disciplinary focus. This focus on general RDM training
for librarians further contributes to a gap in disciplinary-specific training
curricula for researchers. After reviewing Humboldt University of Berlin’s RDM
initiative, launched as a joint venture between Computer and Media Service, the
Research Service Centre, the University Library, and the Vice President for
Research, Helbig (2016) similarly concludes,
“Although general workshops on research data management are more scalable in
comparison to discipline-specific workshops, the advantages of a tailored
approach outweighed this concern” (p. 2). Humboldt University’s RDM training
initiative consisted of one-day workshops aimed at helping PhD students and
researchers in the Geography Department. Groups of six to eight trainees were
formed in order to facilitate the learning process. RDM specialists at the
University felt that a targeted approach would be advantageous. Through a
priori surveys and interviews with researchers and graduate students, the
workshops were designed for the specific needs of that department. By
understanding the nature of RDM in geography, specialists were able to provide
an interactive session encouraging the full participation of the trainees.
Other universities such as Monash University in Australia, University of
Edinburgh in the United Kingdom, and University of Illinois, in the United
States, offer courses to targeted campus groups based on their needs. Such
needs are identified through consultation with strategic research management
services at these universities, as well as in-person discussions with
individual researchers around the campus. Bryant et al. (2018) explain that the
integrated instruction model in a semester-long course is a preferable method
because it is sustainable, as they observe, “the most resource-intensive
approach to supporting RDM education is through in-person, instructor-led
workshops” (p. 10). However, if a workshop approach is taken over a course
integration approach, Bryant et al. (2018), argue that RDM educational services
should strategically align their workshops with course content and with broader
institutional policies of the respective university (such as conforming to the
requirements of Data Management Plans).
Within the literature, the choice between disciplinary focus or
generalized curriculum models, is paralleled by the choice of delivery mode
through online modules, in-person sessions, or a hybrid of the two. Online
training modules are among the most popular among RDM professionals because
they are thought to allow flexibility for accommodating work schedules (Tang
& Hu, 2019). Read et al. (2019) note that the required time commitment is a
strain on working librarians and there is a significant rate of non-completion
of online training. Read et al. (2019) also showed that while online modules
improve the “understanding of and comfort level with RDM” in-person instruction
resulted in “improved RDM practices” (p. 1). The differing experiences between
online and in-person learning led Read et al. (2019) to develop a hybrid, or
“two-tier” coordinated approach to RDM training for health sciences librarians,
and for biomedical researchers that the librarians will, in turn, train and
support. There were seven self-paced, multi-media, online modules produced to
train librarians. The modules covered general RDM topics and applications of
RDM in health science methodologies and discipline-specific data standards. An
evaluation form embedded at the end of each module was included for
self-assessment. Once a librarian indicated comfort with the content, they
received a Teaching Toolkit which included a lesson plan and related materials
to teach RDM to biomedical researchers via a 60-90 minute in-person session.
This hybrid, coordinated model improved the librarian’s ability to deliver an
RDM session for researchers; as Read et al. (2017) observe, “the online modules
were concise and directly tied to the Teaching Toolkit, a curriculum
specifically created for use by the librarians to teach RDM locally, thus
addressing the time constraints of working professionals…” (p. 8).
The learning objectives of online training options are improved when
paired with in-person instruction. Bryant et al. (2018) explain that
the MANTRA Research Data Management Training modules, promoted on the website
as “a free online course for those who manage digital data as part of their
research project” (p.10), is a series of eight generic self-paced modules and
tutorials that are supplemented by in-person training courses by RDM
professionals, at the University of Edinburgh. The
online modules, initially built for researchers and graduate students, have
influenced pedagogical design of RDM training for librarians and research
support staff, not only at the host institution, but also for researchers and
staff at other institutions. In 2013, MANTRA launched a DIY Training Kit for
Librarians to facilitate the remote training modules. Built for the UK research
and funding environment, the course can be adapted locally to include online
and in-person instruction, covering data management planning, organizing and
documenting data, data storage, data sharing and ethics, and questions around
data management. In a blog post, Haddow (2014) writes of the experience of
adapting and delivering the MANTRA DIY Training Kit for Librarians at the
Sterling University of Edinburgh. According to Haddow (2014), the subject librarian
members of a dedicated local RDM Task Force, “found it beneficial to set time
aside as a team to look at this issue;” (para. 2) however, they noted
challenges and significant time investment for the local facilitator to adapt
the course content. As Haddow (2014) explains: “the instructions were sometimes
not clear but by the end I figured out that I just needed to look at the
manual.” (para. 4)
The “Data Intelligence 4 Librarians course” was released in 2011 by
3TU.Datacentrum, a partnership among three universities in The Netherlands (the
partnership was later called 4TU.ResearchData (2020)). This course
provides another example of a learning platform targeted to digital
preservation professionals and included two in-person sessions at the beginning
and the end of the training period. During the in-person sessions, coaches
would teach the trainees, while during the online sessions, trainees were expected
to be prepared for each unit and complete assignments by themselves or in
pairs. Throughout the online portion, trainees could reach out to their
respective coaches through an established online platform. Later, the course
was transformed into “Essentials 4 Data Support” whose target group was a more
widely-defined group of professionals identified as “data supporters,” further
defined as “people who support researchers in storing, managing, archiving and
sharing their research data” (p. 244). Trainees from multiple institutions
attended and worked mostly in pairs, learning how to write research data plans
for fictional scenarios. Participant surveys and networking through online
forums following the training were completed (Grootveld
& Verbakel, 2015). Feedback indicated that
homework assignments were the most valuable element of the course, as the
pairing of trainees led to enjoyable discussions. Participants also appreciated
learning from researchers, including how they deal with data management issues
and about differences between disciplines (Grootveld
& Verbakel, 2015). Trainees admitted that the use
of audio-visual elements was helpful for their learning experience. Current
versions of 4TU.ResearchData consist of three variants: a combination of
in-person sessions and online training platforms, supervised by coaches and
open to online discussion forums; a self-directed, online course, open to
online discussion forums; a self-directed, online course with no access to
coaches or discussion forums.
A recent example of generalized, online RDM training includes the
Research Data Management Librarian Academy (RDMLA), for librarians from
multiple institutions around the globe (Shipman & Tang, 2019). The
curriculum was based on needs gathered from interviews and a survey conducted
by Tang and Hu (2019), as previously discussed, and its intent was to fill gaps
training for librarians in higher education, through online training. Although
its success cannot be confirmed at this time, the online-only format of RDMLA
should be assessed in terms of its ability for librarian trainees to translate
their knowledge into researcher training, in consideration of completion rates
and the findings of studies on hybrid or in-person models. It is important to
note that the RDMLA training is underwritten by the publisher Elsevier, with
modules promoting tools in which Elsevier has a vested interest, while the
other trainings reviewed are developed through public or local institutional
funding streams.
Despite available online solutions to local training gaps, in-person
instruction remains a popular approach, as it catalyzes communities of practice
around complex skillsets. Wittenberg et al. (2018) discussed workshops launched by a research data management team at the
University of California in Berkeley, and show that in-person, ongoing, and
discipline-based consultations on RDM by specialized liaison librarians are
among the most successful methods of RDM support by university libraries. As
they mention, “participants, on average, were more satisfied with domain-based
RDM training than they were with general RDM training” (p.328). At the same
time, Wittenberg et al. (2018) admit that the success of discipline-based training depends on a
scientific community built around RDM, which is mainly based on continuous
connections between liaison librarians and researchers.
The Library Carpentry workshops with RDM-focused content, as
discussed by Baker et al. (2016), are a worthwhile comparison to the online or
hybrid teaching models available to librarians, due to the strong emphasis
placed on in-person skill sharing and long-term community building. The multi-session
workshop took place in the fall of 2015 over four, three-hour weekly evening
sessions at the City University London Centre for Information Science. The
workshops had three aims: to blend non-library specific software skills
training with existing library specific programs; to collect data on software
skills in university libraries; and to build the foundations of a distributed
community model for embracing and sustaining software skills in the library.
Prior to the sessions, attendees were asked to make a name badge, also
identifying their level of knowledge of RDM and related software, for
presenters to better guide the attendees. Participants were also encouraged to
note the level of knowledge of others to better assist them during the
workshop, if needed. In this way, peer-to-peer collaborations were built into
the workshop design. Participants shaped workshop content. Session one began
with an introduction to basic programming concepts and attendees were asked to
reflect on words and phrases associated with programming, code, and software
from which they could benefit. Baker et al. (2016) note that many universities
around the world use “Data Carpentry Workshops” formats and materials adapted
to their local needs, which demonstrates the success of the project. However,
they still recognize the need to develop a set of resources to enable workshop
attendees to share software skills in their home libraries. It is anticipated
that these resources would be predicated on the idea that the best way to reinforce
one’s own software skills is through teaching others.
RDM Training as a Means of Community Building
Research data management training landscape in Canada: A white paper (2017) outlined eight principles for developing a coordinated national
training curriculum. Several of these principles foreground the community of
practice approach adopted by the librarian-led Portage Network RDM Expert
Groups. The notion of RDM as a set of skills and practices shared by a
community, whether disciplinary, institutional, professional, or otherwise, is
consistent with several of the articles reviewed in this paper, as well as the
“data communities” model of researcher behaviour in data sharing, described by
Danielle Cooper and Rebecca Springer (2019). However, while communities of
practice may be wrapped in a myth of informal organizing, in reality they
require leadership and intentional cultivation, particularly as Etienne and
Beverly Wenger-Trayner (2015) observe, if they are
used for developing the “strategic capability” of an organization or its
personnel. Indeed, the strategy of nurturing national RDM infrastructure,
training, and support by “building partnerships in the face of complexity” has
been carefully crafted by Portage since its early stages (Humphrey, 2020, p.
2). From this perspective, RDM Librarians and other research support staff have
a key role in training, as universities develop capacity to comply with RDM
requirements of national and international funding agencies. For this reason,
this literature review will conclude with the seven principles of RDM training
developed at TU Delft (2019), as well as new approaches to librarian RDM
training that build upon the intersections of research data management with the
workflows, best practices, and scholarly communities of open science.
The TU Delft (2019) principles provide a framework whereby RDM training
becomes the mechanism for cultivating a community of practice that is both
campus-wide and disciplinary-focused, while reaching beyond the campus into the
information circuits of the scholarly community. Significantly, these
principles encourage a researcher-focused RDM vocabulary; they foster
collaboration between faculty and research support staff across multiple
university departments and service providers; and furthermore, there is
recognition that the university must provide meaningful incentives that
motivate trainees, whether they are administrators, librarians, research
support staff, researchers, or students, to join the community of practice. The
TU Delft “Open Working” website (2019) outlines some principles including:
“whenever possible, data and software management training should be built upon
the existing faculty-specific courses”; “building and delivering such training
must be a collaborative effort between faculties, the library, graduate school
and other university services”; and “library and graduate schools should
continuously engage in consultation processes with PhD students and
researchers.” (para. 2, 4, 6) At the same time, the principles recommend
engagement with organizations outside universities as vital in making training
resources sustainable. In order to successfully implement this vision, the TU
Delft principles recognize that researchers must receive the proper incentives
to participate and contribute to the training. The library should also solicit
feedback from researchers to iteratively improve and update the training
content. Finally, the principles reinforce that courses should be accompanied
by clear learning objectives, a lesson plan, and a description of the methods
selected for the training (TU Delft, 2019).
Looking forward, one can imagine integrated training for librarians and
researchers that establishes RDM as the foundation for data-sharing workflows
and other best practices of open science scholarly communications. The
international principles of FAIR data, findability,
accessibility, interoperability and reuse, can be a shared method between
cross-disciplinary open scholarship practices due to a common engagement with
digital assets. As Higman et al. (2019) argue,
“Researchers often want to be FAIR, and sometimes open; they are noble
aspirations... By using the language of FAIR and open, we can engage people in
data management too” (p. 2). The Bodleian Libraries at the University of Oxford
offers a model of how the integration of RDM training with other areas of open
scholarship might be achieved for librarians. Library RDM services are led by
one specialist who has developed an RDM training series for researchers
addressing key issues, such as working with confidential data, secondary use of
data, and data deposit and preservation. This training series is often
team-taught with IT representatives or library staff with complementary
expertise, highlighting the need for researchers to first contact their subject
librarians with queries. RDM platforms are also supported by multiple members
of library staff, not only the RDM specialist. The collaborative approach to
RDM training for researchers, and a distributed technical RDM service “serves
to reinforce the message of the training aimed at library staff, namely that
RDM is an area that library staff across the board can support to some extent”
(Southall & Scutt,
2017, p. 307). RDM training for librarians and library staff mirrors the
content of training for researchers. There are two workshops that cover basic principles
of RDM, trends in scholarly communications, and concrete examples of data
management, with an emphasis placed on an “increased understanding of digital
scholarship, RDM issues and where these sit in relation to the work of the
academic library and new areas of scholarly activity such as Open Access (Southall & Scutt, 2017, p.
308).
Conclusion
The aim of this literature review of 13 sources, containing 14 case
studies, was to survey a range of RDM training and capacity-building
approaches, in order to determine the next steps for our own local context at
the University of Ottawa. A method of looking at international training models
was used in order to identify and supplement a gap in the emerging national RDM
policy, infrastructure, and training environment. For instance, a notable
challenge in the Canadian RDM training space is that many institutions have not
yet developed the RDM Institutional Policies that are anticipated by the Draft Tri-Agency Research Data Management Policy (2018). This layer of institutional strategy will enable the building
of RDM into graduate-level curricula for both researchers and librarians. In
the meantime, the next steps for building a training program at our local
institution will begin with establishing a set of principles based on the
findings of this literature review. The plan is to align these principles with
the training methods, modes of assessment, and infrastructure development timeline
outlined in a national training strategy anticipated for release in fall 2020
by the Portage Training Expert Group as a follow-up to the 2017 white paper,
tentatively titled, Building a Portage
Network Training Strategy: A Canadian Approach to Research Data Management.
The following trends emerged though this literature review, which have
informed the national training strategy, and will be taken into consideration
when building local training options for librarians, research support staff,
and researchers at the University of Ottawa. Librarians and researchers must
have enough incentive to undertake training in RDM or to join a community of
practice. Training requires a significant investment of time, whether online or
in-person, and librarians are unlikely to take on additional training, or to
complete the training once enrolled, without a perceived benefit or
reinforcement through regular RDM service provision. Disciplinary-specific
instruction is preferable over general instruction for both librarians and
researchers, however, a librarian’s own training opportunities will influence
their ability to provide discipline-specific RDM instruction to researchers.
There is a double gap in the training landscape, as the lack of
disciplinary-specific training opportunities for librarians further contributes
to a lack of training options and service offerings for distinct research
areas.
The range of pedagogical designs reflected in the case studies make it
difficult to draw conclusions as to whether intensive events, or a series of
shorter time-commitments over a longer time period, is preferable for learning
outcomes. In-person training opportunities emerged as the preferred option for
learning retention and secondary effects of building a community of practice.
For the same reasons, online instruction was found to be most effective when
paired with an in-person component. The sources in this literature review
predate the global COVID-19 pandemic, which has shifted higher-education into
online delivery in historically unprecedented ways. This context may present an
opportunity to apply the best practices of online learning design to close the
gap between the benefits of in-person training and the low retention in online
learning environments. Initiatives such as the University of British Columbia’s
RDM Fall Series 2020 are early responses to virtual RDM instruction during the pandemic,
demonstrating the importance of the adaptation to local contexts, for example.
The literature review highlights the recommendation that in order to be
meaningful, generalized RDM training offered by third parties must be adapted
to local contexts. Discipline-specific training, in-person training, and
adaptation to local contexts are all resource intensive activities but they are
worth the investment. Librarians and other research support staff with
disciplinary awareness will be more successful as they engage with researchers
and help them to adopt research data management practices as an extension of
their disciplinary peer communities. Finally, future directions for RDM
training will be integrated into open access and digital scholarship awareness
training, as well as cross-disciplinary, open science communities of practice
that reach beyond local campuses.
Author Contributions Statement
Felicity Tayler: Conceptualization (lead),
Methodology (lead), Writing – original draft (lead) review & editing
(equal) Maziar Jafary:
Methodology (supporting), Writing – original draft (supporting), Writing
- review & editing (equal)
Acknowledgements
The authors would like to thank Chantal Ripp,
Jane Fry, James Doiron, Lindsey Sikora and Kim Powroz
for valuable feed-back on drafts of this review.
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