Research data management at an African medical university: Implications for academic librarianship

Chawinga, Winner Dominic; Zinn, Sandy

doi:10.1016/j.acalib.2020.102161

Cited by 11 publications

(21 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The knowledge, skills, and education gap involved limited RDS skill sets (Mani et al, 2021; Tenopir et al, 2017), limited RDS technical experience (Brown et al, 2015), lack of involvement in research processes (Bresnahan and Johnson, 2013; Chiware, 2020; Johnson, 2012), and discipline disparities (Corrall et al, 2013; Cox et al, 2019), which ultimately resulted in professionals’ vague understanding of RDM (Hamad et al, 2021; Mohammed and Ibrahim, 2019) and reluctant to accept the emerging data librarianship roles (Ashiq et al, 2021b; Corrall et al, 2013; Cox et al, 2019; Huang et al, 2021). The technical issues involved data scale, variety, and complexity (Johnson, 2012; Knight, 2015), no prober documentation and metadata (Chawinga and Zinn, 2020; Chiware, 2020; Knight, 2015; McBurney and Kubas, 2021; Si et al, 2015), data curation issues (Chiware, 2020; McBurney and Kubas, 2021; Yoon and Donaldson, 2019), data archiving, storage, and preservation (Ashiq et al, 2021b; Knight, 2015; Yoon and Donaldson, 2019), data security and privacy (Cox et al, 2019; Perrier and Barnes, 2018), and absence of data analysis and visualization support (Chiware, 2020; Cox et al, 2019; Hamad et al, 2021). The technological issues mainly related with the cost of RDS tools, software, and insufficient infrastructure (Chiware and Becker, 2018; Johnson, 2012; Mohammed and Ibrahim, 2019; Perrier and Barnes, 2018).…”

Section: Resultsmentioning

confidence: 99%

“…Some studies reported that leadership and institutional limitations are also affecting data librarianship. They stated that advocacy and support from the leadership as well as lack of shared vision was key hurdles (Chawinga and Zinn, 2020; Cox et al, 2017; Faniel and Connaway, 2018; McBurney and Kubas, 2021; Ohaji et al, 2019; Yoon and Donaldson, 2019), especially lacking policy making (Ashiq et al, 2021b; Huang et al, 2021; Mohammed and Ibrahim, 2019), inadequate cooperation and collaboration among services entities within or outside the campus (Cox et al, 2017), and limited staff, time, job description, and non-additional financial benefits who are involved in RDS (Chiware and Becker, 2018; Huang et al, 2021; Si et al, 2015). Few studies also reported the academic and library gap also affecting the RDS (Chawinga and Zinn, 2020; Jefferson, 2020) and researchers reluctant for depositing and data sharing (Ashiq et al, 2021b; Si et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

“…The drivers and motivational factors associated with data librarianship as an emerging paradigm have been reported in 11 studies (Table 3). There are various factors reported in these studies such as library value and visibility (Ashiq et al, 2021a; Cox et al, 2019; Huang et al, 2021; Tenopir et al, 2017), funder mandate (Ashiq et al, 2021b; Bresnahan and Johnson, 2013; Brown et al, 2015), learning and enjoying element (Faniel and Connaway, 2018), job responsibility (Tenopir et al, 2013), and support open access (Chawinga and Zinn, 2020; Si et al, 2015). Ohaji et al (2019) stated that RDS fall under LIS jurisdiction.…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

A systematized review on data librarianship literature: Current services, challenges, skills, and motivational factors

Ashiq

Warraich

2022

Journal of Librarianship and Information Science

View full text Add to dashboard Cite

Data librarianship is becoming more common as a means of developing and integrating data-driven library services. Consequently, the academic and research libraries’ traditional role in providing information support and training has been expanded to include support in all aspects of the research lifecycle. Hence, this study systematically reviews the data librarianship literature focusing on current data librarianship services, challenges, skills, and motivational factors. A systematic review was conducted following the PRISMA guidelines. A comprehensive search strategy was formulated to extract maximum relevant results. The bibliographic data were retrieved from the Scopus, Web of Science, Library, Information Science and Technology Abstracts (LISTA), and Library and Information Science Abstracts (LISA). Finally, 27 studies that fulfill the criteria were included in this study. The findings revealed that two main factors that contribute to the success or failure in this emerging data librarianship roles are skills, knowledge, and expertise; and limited support and advocacy from library leadership and higher authorities. One is on the part of library professionals who can develop the required skills, knowledge, and expertise and the other is on the part of library leadership. The library professionals are hesitant to embrace this new role due to non-additional benefits, no relevant job description, and lacking leadership support. Overall, the findings revealed that the data librarianship scope is dynamic and has been expanded, albeit the progress is slow. The theoretical, practical, policy, and social implications described that the data librarianship services tend to be improved, and the relevant skills, knowledge, and expertise should be developed. The policy initiatives need to be taken, improved, and expanded to advance technical services related to data librarianship.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A systematized review on data librarianship literature: Current services, challenges, skills, and motivational factors

Ashiq

Warraich

2022

Journal of Librarianship and Information Science

View full text Add to dashboard Cite

show abstract

“…It seems to be important that researchers see the library as counterpart for RDM, otherwise the demand for services will be low (Faniel and Connaway, 2018). Chawinga and Zinn (2020b) argued that libraries should be more proactive in promoting RDM services to influence this perception. In addition, libraries do not enjoy a good reputation in every country.…”

Section: Discussionmentioning

confidence: 99%

Research data management systems and the organization of universities and research institutes: A systematic literature review

Donner

2022

Journal of Librarianship and Information Science

View full text Add to dashboard Cite

New technological developments, the availability of big data, and the creation of research platforms open a variety of opportunities to generate, store, and analyze research data. To ensure the sustainable handling of research data, the European Commission as well as scientific commissions have recently highlighted the importance of implementing a research data management system (RDMS) in higher education institutes (HEI) which combines technical as well as organizational solutions. A deep understanding of the requirements of research data management (RDM), as well as an overview of the different stakeholders, is a key prerequisite for the implementation of an RDMS. Based on a scientific literature review, the aim of this study is to answer the following research questions: “What organizational factors need to be considered when implementing an RDMS? How do these organizational factors interact with each other and how do they constrain or facilitate the implementation of an RDMS?” The structure of the analysis is built on the four components of Leavitt’s classical model of organizational change: task, structure, technology, and people. The findings reveal that the implementation of RDMS is strongly impacted by the organizational structure, infrastructure, labor culture as well as strategic considerations. Overall, this literature review summarizes different approaches for the implementation of an RDMS. It also identifies areas for future research.

show abstract

“…Funders and publishers are instrumental in establishing the guidelines and processes we use for sharing data (Chawinga and Zinn, 2020). Education researchersdparticularly those who use existing data (or "secondary" data) sources in mixed methodsdcan benefit from the recent increase in accessible data, as the advantages of using existing data in education research are far and wide (Logan, 2020;Smith, 2011).…”

Section: Introductionmentioning

confidence: 99%

Advancing education research through mixed methods with existing data

Watkins

Johnson

2023

International Encyclopedia of Education(Fourth Edition)

View full text Add to dashboard Cite

Research data management at an African medical university: Implications for academic librarianship

Cited by 11 publications

References 37 publications

A systematized review on data librarianship literature: Current services, challenges, skills, and motivational factors

A systematized review on data librarianship literature: Current services, challenges, skills, and motivational factors

Research data management systems and the organization of universities and research institutes: A systematic literature review

Advancing education research through mixed methods with existing data

Contact Info

Product

Resources

About