Research Data Management in Research Institutions in Zimbabwe

Chigwada, Josiline Phiri; Chiparausha, Blessing; Kasiroori, Justice

doi:10.5334/dsj-2017-031

Cited by 42 publications

(54 citation statements)

References 5 publications

(2 reference statements)

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“…Without research data management policies, it is cumbersome to practice FAIR data principles (Wilkinson et al, 2016) during the research data life cycle. There has been increasing effort toward understanding research data management practices in Africa to promote good data management practices (Chigwada et al, 2017;Zotoo and Liu, 2019;Mushi et al, 2020). The research data management policies also need to focus on incentivizing researchers to share their data by considering issues that affect data sharing (Fecher et al, 2015;Kidwell et al, 2016;Ali-Khan et al, 2017).…”

Section: Lack Of Policies and Incentives From The Government Local Funders And Institutionsmentioning

confidence: 99%

Open Science in Kenya: Where Are We?

Mwangi

Mainye²,

Ouso

et al. 2021

Front. Res. Metr. Anal.

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According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20–50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign toward open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.

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Section: Lack Of Policies and Incentives From The Government Local Funders And Institutionsmentioning

confidence: 99%

Open Science in Kenya: Where Are We?

Mwangi

Mainye²,

Ouso

et al. 2021

Front. Res. Metr. Anal.

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“…RDM activities in most academic libraries of emerging economies have been described as lacking, rudimental and unstructured (Chigwada, Chiparausha, & Kasiroori, 2017). Similarly, very little research was conducted to examine how the libraries capture, describe, manage, and make available research data for discovery, sharing, and reusing (Josiline, Hwalima, & Kwangwa, 2019).…”

Section: Research Problemmentioning

confidence: 99%

“…They guide RDM operationalization. The policies also build stakeholders' confidence by ensuring research data retention, storage, and availability for use, reuse, sharing, or disposal in line with the ethical, legal, statutory, and donor requirements (Chigwada et al, 2017). Section 2 of Australia's Code for the Responsible Conduct of Research states that policies are necessary to guide ownership, storage, and preservation of research data, retention after project completion, and access convenience (Australian National Data Service, 2016).…”

Section: Policy Guidelinesmentioning

confidence: 99%

Research Librarians' Experiences of Research Data Management Activities at an Academic Library in a Developing Country

Masinde

Jing

Wambiri

et al. 2021

Data and Information Management

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University libraries have archaeologically augmented scientific research by collecting, organizing, maintaining, and availing research materials for access. Researchers reckon that with the expertise acquired from conventional cataloging, classification, and indexing coupled with that attained in the development, along with the maintenance of institutional repositories, it is only rational that libraries take a dominant and central role in research data management and further their capacity as curators. Accordingly, University libraries are expected to assemble capabilities, to manage and provide research data for sharing and reusing efficiently. This study examined research librarians’ experiences of RDM activities at the UON Library to recommend measures to enhance managing, sharing and reusing research data. The study was informed by the DCC Curation lifecycle model and the Community Capability Model Framework (CCMF) that enabled the Investigator to purposively capture qualitative data from a sample of 5 research librarians at the UON Library. The data was analysed thematically to generate themes that enabled the Investigator to address the research problem. Though the UON Library had policies on research data, quality assurance and intellectual property, study findings evidenced no explicit policies to guide each stage of data curation and capabilities. There were also inadequacies in skills and training capability, technological infrastructure and collaborative partnerships. Overall, RDM faced challenges in all the examined capabilities. These challenges limited the managing, sharing, and reusing of research data. The study recommends developing an RDM unit within the UON Library to oversee the implementation of RDM activities by assembling all the needed capabilities (policy guidelines, skills and training, technological infrastructure and collaborative partnerships) to support data curation activities and enable efficient managing, sharing and reusing research data.

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“…A vast literature studies data management practices (Tenopir et al, 2011(Tenopir et al, , 2015Unal et al, 2019), including governance (Grant, 2015), and infrastructures (Knight, 2015;Bugaje and Chowdhury, 2018). Studies show little awareness of RDM (Mancilla et al, 2019), a lack of technical skills (Aydinoglu, Dogan and Taskin, 2017) and missing institutional guidelines (Chigwada, Chiparausha and Kasiroori, 2017). There is staggering variability in practices, infrastructures, approaches (Akers and Doty, 2013) and data types (Borgman, 2015;Whitmire, Boock and Sutton, 2015;Borghi and Van Gulick, 2018), both within and between research domains (Mayernik, 2016).…”

Section: Research Data Management and Data Mobilitymentioning

confidence: 99%

Data Sharing in the High-throughput University - Mobility and Precarity

Reichmann¹

2021

Preprint

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The nascent field of data science and the expansion of the higher education sector share surprising affinities. The emergence of the “entrepreneurial university” has brought increasing differentiation of the work roles of academics in addition to increased mobility and, for some, precarity. At the same time, researchers are dealing with unprecedented amounts of data. The present article describes how policies and infrastructures implemented to support researchers with data curation tasks might be repurposed by research administrators to tackle problems of academic mobility rooted in increasing precarity of non-tenured research staff. Findings suggest that the organizational benefit of research data management (RDM) is not increased efficiency or reusability of research, but rather increased control over data left behind by non-tenured staff. Recent interest in data mobility needs to be understood by reference to increased researcher mobility. While the view of data as context-independent evidence has been challenged by reference to the investments necessary to mobilize data as evidence in the first place, the material presented here suggests that RDM is repurposed by universities as a strategy to manage, not data, but rather increasing rates of staff turnover. The mobility of data producers and the immobility of data are frequently in tension. Handing over data is problematic irrespective of domain, data type, and funding source. The term “high-throughput university” is introduced in opposition to “high-throughput” data production techniques to suggest that findability and reusability of data need to be recontextualized with reference to increased academic mobility.

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Research Data Management in Research Institutions in Zimbabwe

Cited by 42 publications

References 5 publications

Open Science in Kenya: Where Are We?

Open Science in Kenya: Where Are We?

Research Librarians' Experiences of Research Data Management Activities at an Academic Library in a Developing Country

Data Sharing in the High-throughput University - Mobility and Precarity

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