Research data management in selected East African libraries: A survey

Abstract

This article investigates the knowledge of research data management and services among library professionals in selected East African libraries. A survey research design was employed, and data was collected using a structured questionnaire from 180 respondents representing four East African countries: Malawi, Mozambique, Zambia and Zimbabwe. The findings reveal that only 31.1% of the selected East African librarians agreed that their institutional libraries provided research data management services. The standard research data management services offered by their libraries included data publishing, sharing and reuse, while collaboration with academic programmes was identified as an essential approach for research data management skill development. The study highlights the need for librarians to acquire legal, policy and advisory skills and knowledge of institutional and extra-institutional resources and the research life cycle for effective research data management service delivery.

Keywords

Research data management skills research data management research data services East African libraries academic libraries African librarians

Introduction

The global research landscape has undergone significant transformations with the adoption of information and communications technologies (ICTs). This shift has profoundly impacted the library and information sector, leading to a transition from traditional library services to electronic and ICT-based offerings. Researchers and information users now encounter new phenomena, such as open access and open science, predatory publishing, stricter requirements from research funders and the handling of large data volumes (Atiso et al., 2019; Hrynaszkiewicz et al., 2020; Wilson et al., 2020). These developments have introduced new research terminologies, such as Research 2.0 and eScience. Within this evolving landscape, research data management (RDM) has emerged as a critical aspect of modern research (Koltay, 2020).

RDM encompasses a range of activities aimed at organising, storing, preserving and disseminating research data throughout its life cycle. Librarians, with their expertise in managing digital scholarly literature, possess relevant skills that can be applied to data curation, preservation and facilitating access. As research data gains increasing importance, universities and academic libraries are prioritising RDM initiatives to effectively support researchers (Chawinga and Zinn, 2020; Howie and Kara, 2022; Kalusopa et al., 2020; Semeler et al., 2019).

RDM ensures that data is appropriately organised, preserved and made accessible to meet the needs of data users and add value to society. Research data encompasses various types of information generated or acquired during the research process, including text, spreadsheets, questionnaires, photographs, films, test responses, slides, laboratory notes, statistics, observations, experimental results, measurements, samples, algorithms, scripts and workflows (Elsayed and Saleh, 2018; Syn and Kim, 2022).

With the introduction of RDM projects in universities, university administrations have recognised the need to prioritise data management to support researchers fully (Price, 2018). Similarly, the Society of College, National and University Libraries reported that academic libraries are shifting from traditional collections to services that align with the changing landscape of research, teaching and learning (Pinfield et al., 2017).

Librarians possess versatile skills, which they have accumulated and applied to managing digital scholarly literature. Therefore, it is argued that these skills are relevant and transferable to handling research data, including data curation, preservation and facilitating access (Anyaoku et al., 2018; Chawinga and Zinn, 2020; Cox et al., 2019; Federer et al., 2020; Howie and Kara, 2022). Cox et al. (2019) provide examples of relevant traditional library skills that can be applied in the RDM context, including advisory and support services, data advisory services, information literacy, data literacy, management of data repositories and metadata management.

The knowledge of these skills is essential for African librarians to provide effective RDM services to their respective communities. The literature has shown an increasing demand from scholars for supporting data to be included in their research (Chawinga and Zinn, 2020; Hrynaszkiewicz et al., 2020; Jones et al., 2019). Additionally, grant organisations now require that the data from their recipients be made available for funding purposes, and there have been campaigns led by data champions to lift embargoes on data access (Anyaoku et al., 2018; Wilson et al., 2020). Given these developments, librarians are encouraged to acquire RDM skills to meet the increasing user demands in their respective libraries.

In East Africa, universities are actively engaged in various research activities. More literature about RDM in East African libraries is needed, with further investigation into the role of librarians in RDM in the region. This study aims to reveal the level of RDM awareness and implementation in the region by examining the skills possessed by librarians. The underutilisation of RDM services could lead to a failure to harness the benefits of effective data management. RDM has become integral to librarianship and its practical application has created numerous opportunities. Therefore, this study is crucial in understanding the level of RDM knowledge among East African professionals and how this knowledge can be used to enhance service delivery.

Objectives of the study

This study aims to investigate the state of RDM in selected East African libraries. The objective is to survey and analyse the RDM services offered by these libraries; assess the frequency and types of services provided; identify areas for improvement and skill development needs; and explore the approaches libraries use to enhance their staff’s RDM expertise. The study includes the following research questions:

Do the libraries currently provide RDM services?

How frequently are RDM services offered in the surveyed libraries?

What specific RDM services are available in the libraries?

What are the skill development needs of library staff concerning RDM?

What are the essential skills and competencies required to provide effective RDM services?

What approaches do libraries adopt to develop their users’ RDM skills?

Literature review

Research data forms the basis of any scholarly investigation, and it is commonly recognised that research plays a crucial role in expanding scientific knowledge. Research is of the utmost importance, but research data appears to receive less attention and be accorded less value. According to Si et al. (2013), RDM is a crucial component of distributing research data sets and a major factor in academic libraries’ open data publication and curation services. RDM is the complete care and handling of research data, including tasks like making the data easier to access, preserving it and adding value to it over time. It is essential for improving the discoverability, accessibility and impact of research. It also adds to the collaborative, computational and data-intensive character of modern science investigations (Tenopir et al., 2020).

Research and academic institutions are investing in systems to manage the growing volume of research data in response to the changing scientific research landscape, which is characterised by greater collaboration, data intensity and worldwide outputs. This transformation is facilitated by cyber infrastructures and data-sharing rules from funding agencies that support open science principles. RDM services are multidimensional; they go beyond data curation and include open publication, open access advocacy and transparent research practices (Tammaro and Casarosa, 2014). The introduction of novel technologies has led to an explosion in digital data and study objects, presenting opportunities and difficulties for data management and collecting (Kruse and Thestrup, 2014).

There has been a global push for more data sharing, especially in biomedical research, emphasising open data as a less restrictive type of data sharing. Nonetheless, issues continue, especially in low- and middle-income countries in the Global South’s member regions of Africa, Latin America, and parts of Asia and the Middle East. Most of the Global South is still in the early stages of RDM implementation. Bhoi et al. (2023) surveyed leading colleges and universities in India and found that RDM services in the top Indian colleges and universities are still in their early stages, affirming the low level of RDM adaptation in the Global South. According to Mavodza (2022), despite the emergence of local RDM operations, little is known about their significance. As a result, leveraging current awareness to organise practical RDM activities can aid in the retrieval and availability of data that is relevant to the region. Chiware (2020) further discovered that open science in Africa is still in an early phase due to the funding and technical problems confronting research facilities. Hence, data management services are in their infancy, with reports of success in a few nations where open scientific and RDM policies have been formed, cyber and data infrastructures are being built, and limited data librarianship courses are offered.

Machimbidza et al. (2022) discovered that certain learning institutions in Zimbabwe were failing to meet the current TELOS (technological, economic, legal, organisational, scheduling) model because they lacked a robust technological system to support data creation, data collection and description, data storage, archiving and preservation, data access, data discovery and analysis, and data reuse and transformation. However, despite a lack of institutional capacity and policies regarding research data, libraries are deploying these new services, albeit unevenly in terms of both the number of services and the type of support provided (Martin-Melon et al., 2023).

Libraries are central to this data management evolution because of their significant role in research and scholarly publication. Therefore, acknowledging their growing importance in RDM, librarians play a crucial part in implementing data management services. They engage in capacity building, community involvement and awareness building to improve research and data sharing (Serwadda et al., 2018). There is no shortage of opportunities for librarians to actively promote RDM and curation as part of the open scientific movement. Librarians have continually exhibited flexibility and readiness to embrace change. This approach has played a significant role in early successes, as witnessed in recent UK studies which document that librarians’ function in RDM emphasises the importance of prioritising data curation when building libraries and information centres (Davidson, 2016: Howie and Kara, 2022). Because they are skilled at adjusting to new technology, librarians are well positioned to be essential players in the evolving RDM scene. To help researchers throughout the data life cycle, it is seen to be crucial to provide librarians with fundamental RDM abilities, such as data planning, sharing, documenting and preservation (Ahmad et al., 2019; Chawinga and Zinn, 2020; Federer et al., 2020). Research has shown that librarians and libraries may offer various useful data services, from planning to research data services (Surkis and Read, 2015; Tenopir et al., 2020).

Nevertheless, there are still issues with RDM adoption and implementation, even as its significance is becoming more widely acknowledged. Although RDM is becoming increasingly important in academic libraries, there are differences in its application across developed and developing nations (Ashiq et al., 2022). Acknowledging RDM systems in higher learning institutions brings to light numerous issues in developed and developing nations. Studies have revealed obstacles that require greater attention and cooperation, such as institutional commitment, faculty participation, inadequate competence among library staff and lack of institutional support (Cox and Pinfield, 2014; Tenopir et al., 2020). Therefore, to stay relevant in the changing RDM environment, librarians are urged to acquire new skills and a deeper comprehension of the research life cycle (MacMillan, 2015). According to Ntja (2022), libraries offer data management planning assistance, data storage and management, and guidance and training in support of RDM, indicating a strong need for libraries to build capacity through the development of staff skills to deal with the challenge of librarians’ workloads and attitudes, and researchers’ reluctance to engage with RDM and institutional partnerships. Emphasizing the importance of widely accepted training criteria, including active participation during training, demand for RDM training, increased participant knowledge and grasp of RDM, confidence in implementing RDM practices, and soliciting and incorporating good post-training feedback is crucial for effective implementation and enhancement of RDM initiatives within library settings. A study by Rantasaari (2022) found that by achieving competency and awareness of RDM and its contents, as well as obtaining the necessary tools and skills to use sound RDM practices in their research library, library professionals had a significant impact on the success of academic and research professionals. This impact was evident in efficient research data management and in fostering a collaborative environment that facilitated the seamless integration of RDM principles into academic and research endeavours, ultimately contributing to the overall advancement and quality of scholarly output.

In a study conducted by Badenhorst and Raju (2023), it was identified that academic librarians require a set of essential skills to proficiently deliver Research Data Management (RDM) services to their research communities. These key abilities encompass expertise in information and data management practices, familiarity with data centers, repositories, and collections, proficiency in data curation, effective management of data collection, a comprehensive understanding of funder policies, and adeptness in research methods and procedures. The study also identified the prominent skill sets necessary for RDM services, which include ICT abilities, digitisation skills, and the ability to prepare data sets for deposit. The survey found that the most important personal traits (or ‘other competencies’) are flexibility, adaptability, digital savviness and a continuous willingness to learn. The study found that library and information science professionals interested in RDM are not expected to possess all these essential competencies. Consequently, collaboration among library and information science experts engaged in RDM becomes vital for delivering efficient RDM services to research communities, leveraging both existing abilities and opportunities for future learning. However, Behrens and Blask (2023) argue that focusing on the basic RDM competencies of data curation differs significantly from the RDM competencies of appropriately managing research processes. In this respect, it is noteworthy that training and continuing education for researchers on RDM themes has expanded significantly in recent years. On the other hand, training in curation-specific RDM competencies is still in its early stages and constitutes a significant gap in the development of data literacy.

Furthermore, because of the data ecosystem, faculty members must participate in the data management process. For reproducible and transparent science, good RDM is required. However, Leimer et al. (2023) found that researchers are frequently unfamiliar with handling research data, publication possibilities, legal considerations and accessible software tools. According to a study by Xu et al. (2022), social science graduate students who received online RDM teaching scored much higher in RDM knowledge than students in the control group.

A study conducted by Leonard et al. (2023) revealed that the transition to new services has led to a limited integration of librarians into the research process in academic and research libraries. Consequently, new positions in librarianship, including roles such as digital curator, research data librarian, scholarly communications librarian, and research librarian, have been introduced in academic and research libraries across Africa. Masenya (2021) goes on to say that academic libraries are struggling to manage their research data due to a lack of established policies and standards, inadequate standardised storage infrastructure, time constraints on organising data, limited funding, insufficient resources, a lack of skills and training in managing research data, and a lack of incentives for researchers to share their data.

Farinelli and Zigoni (2022), in their analysis of the adoption of current research information systems for RDM, found that current research information systems play a key role in facilitating the management and reporting of an institution’s research activities and outputs. Not only do they offer extensive functionality for researchers and research administrators to manage all aspects of their research information effectively, but they are also integrating more and more with specialised RDM tools, institutional repositories and other external systems.

The literature shows that a multifaceted strategy is needed to address these issues, including faculty involvement, awareness-raising marketing, the creation of data management infrastructure and research data service policies. This is because effective RDM practices are impeded at several higher education institutions by the lack of strong policies, infrastructure and management support (Chigwada et al., 2017; Chiware and Becker, 2018). Furthermore, studies show that to overcome the current obstacles, more RDM policies, better infrastructure and more managerial assistance are required (Buhomoli and Muneja, 2021; Hamad et al., 2021), as well as the formulation of a data management plan (Fadlelmola et al., 2021). A study by Donner (2023) reveals that the implementation of an RDM system is strongly impacted by the organisational structure, infrastructure and labour culture as strategic considerations.

The literature on RDM is scarce in the East African setting, necessitating a complete study to understand the implementation, problems and methods connected with RDM in East African libraries. Such an examination is critical for creating a vibrant regional research ecosystem and addressing East African libraries’ unique issues in efficiently handling research data.

Methodology

This study utilised a quantitative research method, employing a survey-based approach to gather data from academic libraries across four African countries. A closed-ended questionnaire was meticulously developed to capture the diverse dimensions of RDM practices, services and skill development needs. The questionnaire was distributed using Google Forms through various platforms, including Web 2.0 channels and direct emails collected from institutional directories and library websites.

Questionnaire development and validation

The questionnaire was structured to facilitate quantitative analysis, emphasising clarity, conciseness and relevance. Accomplished RDM experts and academicians critically assessed the questionnaire for clarity, relevance and comprehensiveness, contributing valuable feedback. A small group of potential participants carried out a pilot study. Feedback gathered was instrumental in refining the questionnaire for accuracy and meaningful responses.

Selection of participants

The study focused on academic librarians and information scientists from four East African countries – Malawi, Mozambique, Zambia and Zimbabwe – that were chosen to represent diverse RDM practices. One hundred and eighty respondents were selected using simple random sampling, balancing statistical significance with the feasibility of data collection. Thirty-seven (20.6%) of the participants were from Malawi; 8 (4.4%) were from Mozambique; 76 (42.2%) were from Zambia; and 59 (32.8%) were from Zimbabwe.

Data collection

The structured questionnaire comprised three sections covering demographic information, the availability of RDM services, and librarians’ RDM skill development needs. The data was collected over three months (July to September 2022) to encourage engagement and ensure diverse responses.

Data analysis

Utilising the Statistical Package for the Social Sciences (SPSS), quantitative methods such as frequency analysis, percentage calculation, and mean and standard deviation were applied to extract meaningful insights from the data collected.

Ethical considerations

This research obtained prior ethical clearance from relevant institutions, adhering to established protocols for studies involving human subjects. Formal permissions were acquired from the respective academic institutions before data collection, ensuring compliance with their guidelines. The participants were fully informed about the study’s purpose and procedures, providing explicit consent voluntarily. To safeguard confidentiality, no personally identifiable information was associated with the collected responses during analysis, preserving participant anonymity. Stringent data-handling protocols were implemented, restricting access to authorised personnel to maintain data confidentiality. Throughout the study, strict adherence to the ethical guidelines and regulations set by institutional review boards was maintained, ensuring the protection of the participants’ rights and welfare.

Results and discussion

Figure 1 illustrates the frequency and percentage distribution of gender among the respondents. Of the 180 participants, 63.3% were male and 36.7% were female.

Figure 1.

Frequency and percentage distribution of gender.

In Figure 2, the data presents the availability of RDM services at East African universities. Of the respondents, 56 individuals (31.1%) reported that RDM services were available, while 124 individuals (68.9%) indicated that such services were not available. This data suggests that a significant number of the surveyed institutes and universities currently need to provide RDM services, highlighting an area for improvement in supporting RDM needs.

Figure 2.

Availability of RDM services at the institutes and universities.

As shown in Figure 3, the frequency of use of RDM services reveals a predominant lack of implementation, with 68.9% reporting no usage. A small proportion (5.5%) used RDM services a couple of times a year, while 8.9% employed them monthly. Weekly usage was reported by 11.7% of the participants, and 5% said they used such services on a daily basis. This data showcases that there is a significant majority of institutions and universities without RDM services, indicating low integration. However, a minority of the participants demonstrated regular use, with some employing RDM services weekly or daily. This disparity underscores the respondents’ diverse adoption levels and usage patterns, indicating room for increased RDM implementation across the surveyed population.

Figure 3.

Frequency of use of RDM services.

Table 1 presents the data analysis of the libraries’ RDM services. The table reflects the availability and frequency of various RDM services offered by the libraries based on a sample of 180 participants. The most commonly provided RDM service is ‘data publishing, sharing and reuse’, which includes assistance with intellectual property matters and metadata, accounting for 27.2% of the responses. The second most prevalent service is ‘carrying out long-term preservation of research data’ through data or institutional repositories, accounting for 26.7%. Additionally, the librarians emphasised ‘supporting reproducibility, transparency in workflows and research integrity’, which accounted for 25.6% of the responses. The libraries also offer ‘data management training or data literacy instruction’ for research students and early career researchers, with 20% of the respondents benefitting from this service.

Table 1.

RDM services offered by the libraries (N = 180).

RDM services available	f	%
Data publishing, sharing and reuse (assistance with intellectual property matters and metadata)	49	27.2
Carrying out long-term preservation of research data (through data repositories or institutional repositories)	48	26.7
Supporting reproducibility, transparency in workflows and research integrity	46	25.6
Data management training or data literacy instruction (e.g. for research students, early career researchers)	36	20
Analysis and visualisation of data sets using Python scripts, SPSS, R and Microsoft Excel software	31	17.2
Study and analysis of data (instructional support)	31	17.2
Advisory services on data analysis, mining and visualisation	24	13.3
Promoting awareness of reusable data sources, such as data archives	18	10
Maintaining a web resource/guide of local advice and valuable resources for RDM	8	4.4

Note: The participants were allowed to choose more than one answer.

Furthermore, libraries in East Africa provide ‘analysis and visualisation of data sets’ using various software tools, including Python scripts, SPSS, R and Microsoft Excel, which accounted for 17.2% of the responses. Another service in this domain is ‘study and analysis of data (instructional support)’, with the same percentage. In addition, 13.3% of the participants had libraries that offered ‘advisory services on data analysis, mining and visualisation’. The libraries also play a role in ‘promoting awareness of reusable data sources, such as data archives’, benefiting 10% of the respondents. Lastly, a few libraries maintain ‘a web resource/guide of local advice and valuable resources for RDM’, catering to 4.4% of the participants.

Table 1 reveals that the libraries offer a diverse range of RDM services. While data publishing, preservation and support for reproducibility are prominent areas of focus, data analysis, training and advisory services are also essential components of their RDM offerings. The libraries’ commitment to promoting data literacy and accessibility is evident through providing valuable resources and advice on RDM.

Table 2 summarises the RDM skill development needs for the libraries, and includes the mean (M) and standard deviation (SD) values for each skill. ‘Legal, policy and advisory skills’ had the highest mean (M = 4.33, SD = 0.9), indicating their significant importance, closely followed by ‘knowledge of institutional and external resources’ (M = 4.23, SD = 0.9). ‘Knowledge of RDM principles, technologies and metadata’ ranked third (M = 4.18, SD = 0.92). ‘Knowledge of the research life cycle’ received a mean rating of 4.01 (SD = 1.09). ‘Data curation and metadata skills’ and ‘technical and ICT skills’ had mean ratings of 3.95 (SD = 1.04) and 3.93 (SD = 1.07), respectively. ‘Knowledge of researchers’ needs and available resources’ received a mean rating of 3.79 (SD = 1.05), while ‘data description and documentation’ scored 3.75 (SD = 1.14). Libraries should prioritise legal and policy skills, knowledge of resources and RDM principles. Additionally, they should consider targeted training for areas with lower mean ratings and diverse opinions, such as technical skills and understanding researchers’ needs.

Table 2.

Libraries’ RDM skill development needs.

RDM skill development needs	M	SD
Legal, policy and advisory skills (e.g. intellectual property, ethics, licensing)	4.33	0.9
Knowledge of institutional and external resources	4.23	0.9
Knowledge of RDM principles, technologies and metadata	4.18	0.92
Knowledge of the research life cycle	4.01	1.09
Data curation and metadata skills	3.95	1.04
Technical and ICT skills (e.g. data storage, infrastructure, architecture)	3.93	1.07
Knowledge of researchers’ needs and available resources	3.79	1.05
Data description and documentation	3.75	1.14

Note: A 5-point Likert scale was used (1 = strongly disagree to 5 = strongly agree).

Table 3 summarises the essential skills required for providing RDM services, including each skill’s mean and standard deviation values. ‘Data ethics’ received the highest mean rating (M = 4.48, SD = 0.76), followed closely by ‘data visualisation’ (M = 4.43, SD = 0.87) and ‘metadata standards’ (M = 4.36, SD = 0.9). This demonstrates the crucial importance of these skills in RDM. ‘Data management planning’ received a mean score of 4.27 (SD = 0.9), while ‘understanding different types of data structures and file formats’ had a mean of 4.22 (SD = 0.88). ‘Big-data analytics’ (M = 3.79, SD = 1.06), ‘identifying data repositories for various subject areas’ (M = 3.76, SD = 1.12), ‘deep-learning techniques’ (M = 3.66, SD = 1.02) and ‘proficiency in qualitative analysis and statistical analysis’ (M = 3.65, SD = 1.14) received lower mean ratings. These findings suggest that there are areas for improvement and development in RDM services. Organisations should strengthen the top-rated skills while considering targeted training to enhance competencies with lower ratings and varied opinions. Understanding the mean and standard deviation values helps prioritise skill development efforts and tailor training programmes to meet specific RDM service requirements.

Table 3.

Essential skills required for providing RDM services.

Skills	M	SD
Data ethics	4.48	0.76
Data visualisation	4.43	0.87
Metadata standards	4.36	0.9
Data management planning	4.27	0.9
Understanding different types of data structures and file formats	4.22	0.88
Big-data analytics	3.79	1.06
Identifying data repositories for various subject areas	3.76	1.12
Deep-learning techniques	3.66	1.02
Proficiency in qualitative analysis and statistical analysis	3.65	1.14

Note: A 5-point Likert scale was used (1 = strongly disagree to 5 = strongly agree).

Table 4 presents the data analysis of the approaches used by libraries to develop users’ RDM skills. The data is based on the responses from the 180 participants, and it is important to note that the participants were allowed to select more than one approach. The most prevalent approach reported by the participants was ‘collaboration with an academic programme to develop professionals with skills related to research data services’, which received a significant response rate of 93.9%, indicating the high relevance and effectiveness of partnering with academic programmes to enhance RDM skills. The second most popular approach was ‘support for staff to attend conferences or workshops on RDM’, with a substantial percentage of 91.7%. This highlights the value of empowering library staff with up-to-date knowledge and expertise through external events focused on RDM.

Table 4.

Approaches used by libraries to develop users’ RDM skills (N = 180).

Approaches	f	%
Collaboration with an academic programme to develop professionals with skills related to research data services	169	93.9
Support for staff to attend conferences or workshops on RDM	165	91.7
In-house staff workshops or presentations	157	87.2
Support for staff to take courses related to research data services	133	73.9

Note: The participants were allowed to choose more than one answer.

The libraries also rely heavily on ‘in-house staff workshops or presentations’ as an approach to skills development, as indicated by 87.2% of the respondents. This method allows libraries to tailor training sessions to meet their needs and cater to their staff’s requirements. Finally, ‘support for staff to take courses related to research data services’ was selected by 73.9% of the participants, demonstrating an interest in providing comprehensive training opportunities for staff members.

The results in Table 4 suggest that libraries recognise the significance of continuous learning and development in RDM. By embracing multiple approaches simultaneously, libraries can effectively foster a skilled workforce that is capable of providing valuable research data services to their users. The flexibility in allowing the participants to choose multiple approaches reflects the diverse and dynamic nature of RDM skill development in libraries, ensuring a well-rounded and competent support system for researchers and other library users.

Discussion

Figure 1 shows the gender distribution among the 180 participants, revealing that 63.3% were male and 36.7% were female. By providing a broad perspective of the respondents, this core demographic insight sets the stage for the following analysis. Figure 2 provides a complete depiction of the RDM services environment. Notably, 31.1% of the respondents said that RDM services were available, while 68.9% said they were not. This indicates a major need for improvement in supporting RDM, consistent with previous studies by Corrall et al. (2013) and Tenopir et al. (2020) highlighting the lack of RDM services in libraries. Furthermore, Chawinga and Zinn (2020) agree with these findings, citing the introduction of RDM as a concept in East African libraries.

Figure 3 delves deeper into the frequency of RDM services, finding that 68.9% of the respondents said RDM services had never been performed in their libraries. This scarcity of regular RDM services highlights the critical need for infrastructure improvements and public awareness efforts to provide researchers with adequate data management solutions. According to Lu et al. (2018) and Wang et al. (2016), there is a gap between the perception and practice of RDM among librarians. Table 1 shows that certain RDM services provided by the libraries stand out, with the most common being ‘data publishing, sharing, and reuse’ (27.2%) and ‘carrying out long-term preservation of research data’ (26.7%). Libraries’ commitment to complete RDM support is demonstrated by their varied services, including data analysis and visualisation, training and advisory responsibilities. These findings are consistent with those of Chawinga and Zinn (2020), Hrynaszkiewicz et al. (2020) and Jones et al. (2019), all of which emphasise librarians’ ability to provide RDM services.

Table 2 explains the RDM skill development needs, emphasising the importance of ‘legal, policy and advisory skills’, with the highest mean value of 4.33. The findings emphasise the need to prioritise skill development efforts in the legal and policy domains, which is consistent with the studies of Anyaoku et al. (2018), Federer et al. (2020) and Tang and Hu (2019). Table 3 shows that ‘data ethics’ (M = 4.48), ‘data visualisation’ (M = 4.43) and ‘metadata standards’ (M = 4.36) obtained the highest mean ratings for individual RDM abilities. These findings highlight areas of strength and reveal sectors that demand focus and development, such as big-data analytics and qualitative analysis. The findings support Cox et al.’s (2019) and Chawinga and Zinn’s (2020) research in emphasising the critical abilities that librarians require to provide effective RDM services.

Finally, Table 4 describes the ways in which libraries help users enhance their RDM skills. ‘Collaboration with an academic programme’ (93.9%) and ‘support for staff to attend conferences or workshops on RDM’ (91.7%) stand out as common strategies. Staff courses and in-house workshops are also popular, demonstrating a diversified commitment to continual learning. These findings are consistent with those of Jones et al. (2013), who indicate that educational institutions are now establishing infrastructures to support researchers’ data management and storage repository services. Lewis (2010) states that RDM should be integrated into curricula to increase librarians’ acquisition of skills and enable effective RDM service delivery. One of the barriers to RDM skill development is the lack of a policy to guide RDM. According to Howie and Kara (2022), the number of data-sharing policies in New Zealand had decreased in 2018 compared to 2012.

This study highlights the crucial need to improve RDM services at these institutes and universities. The availability, frequency and skill development discrepancies highlight the significance of tailored interventions to close these gaps. Libraries’ dedication to various RDM services and skill development initiatives indicates a promising future. Addressing these findings could increase research productivity, data integrity and data-sharing compliance while aligning with broader efforts to advance RDM practices in academic contexts.

Recommendations

The findings from this study underscore the critical need for strategic interventions to strengthen RDM services within East African libraries. First, institutions should prioritise developing comprehensive plans to introduce and support RDM services. This should involve strategically allocating resources and funds to establish the necessary infrastructure, tools and training programmes to support RDM services consistently. Moreover, a focus on capacity building through regular workshops and training sessions, specifically targeting priority areas such as legal, policy and advisory skills, is paramount. Collaborative efforts between libraries and academic programmes should be fostered to integrate RDM concepts into curricula, ensuring a well-rounded education for students and researchers. Additionally, formulating and implementing clear policies and guidelines tailored to RDM practices within institutions is crucial, providing a structured framework for effective service delivery. Continuous assessment and feedback mechanisms should be established to gauge service effectiveness and identify areas for further enhancement.

A concerted effort to diversify RDM services within libraries is essential, concentrating on areas with a low frequency of implementation. Libraries should foster interdisciplinary collaborations across departments to develop holistic RDM approaches. It is imperative to create awareness campaigns to emphasise the significance of RDM practices and their inherent benefits among researchers, students and faculty members. Investing in technological tools and the infrastructure necessary for advanced RDM services will significantly facilitate efficient data management, storage and analysis. Encouraging libraries to benchmark with global institutions will foster the adoption of innovative practices, contributing to the continual improvement of RDM services.

Conclusion

RDM is an indispensable aspect of modern academic libraries worldwide and crucial for fostering effective scholarly endeavours and ensuring data integrity and accessibility. The findings from this study of selected East African libraries shed light on a global concern: the inadequacies in RDM services and skill development. The identified gaps in service provision, frequency and skill development resonate beyond East Africa, reflecting a broader global need for strategic interventions. Institutions worldwide must recognise the urgency of enhancing RDM services within libraries.

The strategic recommendations encompass the development of comprehensive plans, capacity building through training, collaborative efforts with academic programmes, policy formulation and continuous assessment. These recommendations hold relevance on a global scale and are applicable to libraries across diverse socio-economic and cultural landscapes. Moreover, the suggestions for diversifying RDM services, interdisciplinary collaborations, awareness campaigns, technological integration and benchmarking resonate universally. Libraries worldwide must embrace these suggestions to evolve and adapt to the changing landscape of data-driven research.

This study underscores that while the specific nuances of RDM service provision may vary across regions, the core challenges and strategies for improvement remain consistent globally. Addressing these challenges and implementing the suggested measures is imperative for libraries worldwide to effectively manage research data, ensure data integrity, facilitate collaborative research and contribute meaningfully to the scholarly ecosystem. These strategies will strengthen the global academic community by fostering robust, transparent and accessible research practices.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iDs

A Subaveerapandiyan

Jeremiah E Ugwulebo

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