Library and Data Management Support for Interdisciplinary Research among Faculty Members in Nigerian Universities

Interdisciplinary research has become an essential approach for addressing multifaceted global challenges that extend beyond the scope of single disciplines. Central to this process is the management and use of data, which serves as the foundation for hypothesis formulation, validation, and knowledge production (Xu, 2022; Igbinovia, 2017; Tripathi et al., 2017). As the volume and diversity of research data continue to grow, the effective management of heterogeneous datasets has become a defining factor for the success of interdisciplinary research. Libraries, long regarded as custodians of knowledge, are increasingly recognized as key partners in facilitating research data management (RDM), offering technical, advisory, and policy-driven support in the digital age.Existing scholarship highlights both the opportunities and challenges of RDM in academic and research environments. Studies conducted across Africa, Asia, and developed regions underscore recurring themes such as inadequate infrastructure, insufficient policies, low researcher awareness, and skill gaps among librarians (Cox et al., 2017; Chigwada, 2021; Huang et al., 2021). In Nigeria, Abduldayan et al. (2021) found that while chemistry researchers valued RDM, they lacked formal data management plans, oftenresulting in data loss and mistrust of library systems. Similarly, Arthur and van der Walt (2021) reported that Ghanaian faculty members depended heavily on personal storage devices rather than institutional repositories, which hindered collaboration. Broader regional studies further show that RDM services are still nascent, with Subaveerapandiyan and Ugwulebo (2024) observing that only a minority of East and Southern African institutions offered structured RDM services, often limited to basic functions such as data publishing and sharing.Beyond Africa, comparative studies reveal similar limitations in Asia and the Middle East. Research in Jordanian, Pakistani, and Indian universities found weak or absent RDM policies, poor infrastructure, and limited staff training (Al-Jaradat, 2021; Piracha & Ameen, 2019; Singh et al., 2022). Even where institutional repositories exist, services remain fragmented and underutilized due to lack of awareness or policy enforcement (Ashiq et al., 2021; Huang et al., 2021). In contrast, studies from North America, Europe, and parts of Asia report more mature systems, though challenges persist in aligning RDM with interdisciplinary needs. Xu (2022) emphasized the global demand for discipline-specific RDM training, while Lee and Stvilia (2017) and Tripathi et al. (2017) identified sociotechnical and policy factors that continue to shape best practices. These findings suggest that although developed regions are more advanced, libraries worldwide continue to grapple with skills development, resource limitations, and researcher engagement.Despite these valuable contributions, a significant limitation of existing research is its lack of emphasis on the specific needs of interdisciplinary research. Most prior studies address RDM in general or within single disciplines, often overlooking the unique complexities of interdisciplinary collaboration such as data heterogeneity, communication barriers, and ethical considerations. Studies in African contexts, while highlighting infrastructural and policy-related challenges (Chiware & Becker, 2018; Adika & Kwanya, 2020), rarely examine how libraries can strategically respond to the demands of cross-disciplinary research teams. This leaves a critical gap in understanding how libraries, particularly in Nigerian universities, can provide integrated and sustainable RDM services tailored to interdisciplinary scholarship.This paper seeks to bridge that gap by investigating the challenges faced by interdisciplinary researchers in managing data and by exploring the role of libraries in supporting effective data practices within Nigerian universities. The novelty of the studylies in its focus on the intersection between RDM and interdisciplinary research in a context where systemic and institutional barriers remain largely unaddressed. Specifically, the study is guided by the following research questions: (i) What challenges do interdisciplinary researchers face in managing data? and (ii) How can libraries provide effective support for data management in interdisciplinary research? To address these questions, the paper is structured as follows: the next section presents a detailed review of literature on RDM and library support, followed by the methodology. The findings and discussion sections examine the Nigerian context, and the conclusion highlights the implications for policy, practice, and future research</p>

This study employed a descriptive research design, using a quantitative approach. This design is deemed suitable for capturing data from a sample of the target population at a specific point in time, thus providing a snapshot of faculty members' perspectives on data management and library support within interdisciplinary research contexts. Descriptive research is ideal for studies where understanding the characteristics, behaviors, and challenges of a defined population is required without manipulating variables or establishing causal relationships (Siedlecki, 2020). The target population for this study comprised faculty members at universities in Akwa Ibom State, Nigeria. Using Cochran’s formula for continuous data with a 95% confidence level and a 5% margin of error, the minimum sample size was calculated to be 200 faculty members. Cochran’s formula is particularly suitable for this study because it provides a scientifically grounded method for determining an adequate sample size when dealing with large or potentially infinite populations, ensuring that the sample is statistically representative while keeping sampling error within acceptable limits. This sample size was chosen to ensure adequate representation and reliability in capturing faculty perspectives. There are four universities in Akwa Ibom State: Top Faith University, Uyo; University of Uyo, Uyo; Akwa Ibom State University, Ikot Akpaden; and Federal University of Technology, Ikot Abasi. For this study, a convenient sampling approach was used to select two of these universities: Akwa Ibom State University, Ikot Akpaden, and the Federal University of Technology, Ikot Abasi. These institutions were selected due to their accessibility to the researchers, the willingness of their faculty to participate, and their engagement in interdisciplinary research activities relevant to this study. The choice also reflects practical considerations such as time and resource constraints, which are common in academic research.Faculty members in senior academic positions (senior lecturers, associate professors, and professors) were purposively targeted for this study. This decision is justified as these faculty members are likely to have extensive experience in interdisciplinaryresearch, data management, and a deeper understanding of library support services. Their seniority positions them to provide informed insights into both the challenges of data management in interdisciplinary research and the potential role of libraries inthis context. Data were collected using a structured questionnaire developed specifically for this study. Questionnaire items were derived from an extensive literature review and expert input in research data management and information science. A four-point Likert scale was used, with responses ranging from 1 (Strongly Disagree) to 4 (Strongly Agree). This scale was selected to prevent neutral responses, encouraging participants to take a clear stance on each statement. To ensure content validity, the initial draft of the questionnaire was reviewed by a panel of two experts in information science and research methodology. Each question was evaluated for relevance, clarity, and completeness. Following this, face validation was conducted, in which a small group of seasoned professors from various disciplines reviewed the questionnaire. They provided feedback on question readability, clarity of instructions, and overall flow, which helped refine the final instrument. The questionnaire was administered through an online survey hosted on Google Forms to facilitate ease of access and wide distribution. The survey link was shared on WhatsApp groups for faculty members at each university, with assistance from lecturers identified through ResearchGate. This distribution approach was effective in reaching respondents across different departments. All participants were provided with an information sheet detailing the study's purpose, procedures, potential risks and benefits, and their right to withdraw at any point. Informed consent was sought from each participant, and privacy and confidentiality were safeguarded by assigning unique identifiers instead of names, securely storing data, and limiting access to authorized personnelonly. Participants were assured that their responses would be used solely for research purposes and that no individual would be identifiable in any reports or publications.Data collection occurred between June and September 2023. At the end of this period, a total of 82 completed and usable questionnaires were returned, representing a response rate sufficient for analysis. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize participant responses. For interpreting responses to research questions, the four-point Likert scale responses were analyzed with a threshold mean score of 2.50, derived as the midpoint of the scale. Responses with a mean score below 2.50 indicated disagreement with the statement, while scores at or above 2.50 indicated agreement.</p>

The data collected through the questionnaire were analyzed using descriptive statistics, including frequencies, percentages, means, and standard deviations. For interpretation, a decision rule was applied based on the midpoint threshold of the fourpoint Likert scale used in the study. Specifically, a mean score of 2.50 or higher indicated agreement (acceptance) with the statement, while a mean score below 2.50 indicated disagreement (rejection). Out of 82 senior lecturers to whom questionnaires were administered, 77 copies were successfully completed and returned, making a 93.9 return rate.Table 1: Challenges interdisciplinary-researchers face in managing dataS/n Variables Total Mean Std Dev Decision1.Data diversity and heterogeneity 77 3.23 0.56 Accepted 2.Collaboration and communication challenges 77 3.45 0.48 Accepted 3.Variations in jargons 77 3.12 0.58 Accepted 4.Different methodologies 77 3.51 0.45 Accepted 5.Ethical considerations 77 2.75 0.62 Accepted Data in Table 1 indicates the challenges interdisciplinary researchers face in data management. Among the indicators, “different methodologies” recorded the highest mean score (3.51), followed closely by “collaboration and communication challenges” (3.45),suggesting that methodological incompatibility and team coordination issues are the most pressing barriers. “Data diversity and heterogeneity” (3.23) and “variations in jargons” (3.12) also scored highly, reflecting the conceptual challenges of reconciling disciplinary differences in data structure, format, and terminology. Ethical considerations, although still above the acceptance threshold (2.75), had the lowest mean score, indicating that while important, they may be less immediately problematic compared to methodological and communication challenges. Overall, the findings reveal that the challenges can be broadly grouped into conceptual challenges (data diversity, jargon variations, and ethical considerations) and technical/operational challenges (different methodologies, collaboration, and communication), with technical issues slightly more prominent in terms of impact.Table 2: How libraries provide effective support for data management in interdisciplinary researchS/n Variables Total Mean Std Dev Decision6.Data literacy training 77 3.19 0.57 Accepted 7.Data repository 77 development 3.02 0.60 Accepted 8.Data management planning 77 support 3.41 0.50 Accepted 9.Guidance on best practices 77 and standard 2.57 0.69 Accepted Data in Table 2 indicates how libraries can provide effective support for data management in interdisciplinary research. The highest-rated form of support was “data management planning” (mean = 3.41), highlighting the importance of structured frameworks for handling research data. This was followed by “data literacy training” (3.19) and “data repository development” (3.02), both of which address the skills and infrastructure needed to facilitate effective data use and sharing. “Guidance on best practices and standards” had the lowest mean score (2.57), though still above the acceptance threshold, suggesting that while such guidance is valued, it may not be as readily recognized or utilized as tangible training or planning services. Grouping the findings shows that libraries provide both conceptual support (best practice guidance, data literacy) and technical/infrastructural support (repository development, planning assistance), with a slightly higher emphasis from respondents on technical and planning-relatedroles.Discussion I. Challenges do interdisciplinary researchers face in managing dataThe findings of this study reveal several critical challenges that interdisciplinary researchers encounter in managing research data effectively. These challenges encompass variations in research methodologies, collaboration and communication barriers, data heterogeneity, jargon differences, and ethical considerations. The current study’s findings that different methodologies complicate data management are substantiated by Abduldayan et al. (2021), who demonstrated that even within the field of chemistry, variations in data handling among researchers in Nigerian universities led to inconsistencies in data preservation and loss of valuable data due to inadequate planning and storage. Similarly, Xu (2022) emphasized the necessity for discipline-specific RDM training, particularly because diverse fields have varying standards and practices, which make general solutions for data management insufficient. This underscores the unique difficulties interdisciplinary researchers face when bridging these methodological gaps, suggesting the need for customized data management solutions tailored to specific disciplinary needs.Furthermore, collaboration and communication challenges, highlighted as another key obstacle in this study, resonate with the findings of Arthur and van der Walt (2021) and Subaveerapandiyan and Ugwulebo (2024). Arthur and van der Walt's study in Ghana demonstrated that researchers often relied on personal storage devices rather than institutional repositories, which created barriers to effective data sharing and collaborative work. Subaveerapandiyan and Ugwulebo (2024) also noted that insufficient RDM services in East African universities restricted collaboration efforts. These studies suggest that for interdisciplinary teams, the lack of cohesive RDM policies and platforms intensifies collaboration issues, reinforcing the present study’s claim that improved RDM infrastructure and inter-institutional policy support are essential to foster collaboration across disciplinary divides.</p> <p>Data diversity and heterogeneity are additional complications identified in this study. Interdisciplinary research often combines datasets with varying structures, formats, and standards, making integration challenging. Huang et al. (2021) observed similarissues in Chinese universities, where RDM was still evolving, leading researchers to emphasize repositories rather than data support services. The lack of support for data standardization and interoperability limits researchers’ ability to effectively manage heterogeneous data, an issue mirrored in this study’s findings. Moreover, Singh et al. (2022) and Ashiq et al. (2021) highlighted that, in contexts with limited resources, even essential RDM functions like data organization and preservation become difficult to implement. The resulting inconsistency in data management practices emphasizes the need for more robust support to help interdisciplinary teams manage complex and diverse datasets.The challenge of jargon variations and discipline-specific terminologies also emerged as a barrier, complicating interdisciplinary communication and data sharing. The findings by Chigwada (2021) on librarians’ challenges in delivering RDM services in Zimbabwe reveal similar language and conceptual divides, where inadequate training and support led to miscommunication between librarians and researchers. Similarly, the work of Cox et al. (2017) highlights that even in developed regions, libraries often struggle to bridge gaps in data curation skills across disciplines, making data management guidance difficult to implement effectively. These findings reinforce the notion that for interdisciplinary teams, differences in terminology can impede understanding, underlining the need for shared vocabularies and standardized data descriptions. In addition, ethical considerations were identified as a significant challenge in this study, aligning with findings from Majid et al. (2018), who noted that faculty members at Nanyang Technological University were often concerned with legal and ethical implications of data sharing. This cautious approach to data handling reflects the broader trend of ethical dilemmas in interdisciplinary research, particularly when data originates from human subjects or sensitive sources. Similarly, Lee and Stvilia (2017) identified a need for institutional support in handling ethical issues related to data access, usage rights, and ownership. These ethical complexities highlight the importance ofcomprehensive RDM policies that guide interdisciplinary researchers in navigating data privacy and ownership while promoting ethical data sharing practices.II. How libraries provide effective support for data management in interdisciplinary researchThe findings from this study indicate the potential of libraries to support data management in interdisciplinary research effectively. Libraries offer critical assistance in data management planning, data literacy training, data repository development, andguidance on best practices and standards. These roles not only help researchers but also reinforce libraries as vital partners in managing data across disciplines. The following discussion validates these findings through supporting literature and highlights areas where challenges remain.The study’s indication that libraries play a valuable role in data management planning aligns with Frederick and Ru (2019), who investigated RDM support in Ghanaian universities. Their findings demonstrate that libraries are beginning to establish RDM frameworks, develop policies, and build infrastructure to support data management. These efforts are bolstered by training programs and advocacy initiatives aimed at increasing researcher engagement. This aligns with the current study’s conclusion that effective support from libraries in data management planning can enhance interdisciplinary research by addressing specific data handling needs and providing consistent frameworks.Data literacy training, highlighted in the present study as a crucial support service offered by libraries, also finds support in Palsdottir (2021) and Xu (2022). Palsdottir (2021) showed that researchers and doctoral students often possess limited RDM knowledge, with inconsistent practices due to gaps in RDM understanding. The study called for university-led initiatives to improve training and tool access, underscoring libraries’ importance in this area. Xu’s (2022) global review of RDM best practices reinforced the need for discipline-specific training, suggesting that libraries collaborate with faculty to offer customized data management curricula. Together, these studies confirm that libraries are well-positioned to provide essential training in data literacy, particularly if they offer targeted, discipline-specific programs.The development of data repositories is another area where libraries provide effective support, as indicated by the findings. Singh et al. (2022) examined Indian academic libraries and found a need for institutional support, policies, and technology resources to enhance RDM practices. The lack of resources in many libraries hampers the creation of robust data repositories, which are essential for data sharing and preservation across disciplines. Although some libraries face constraints in repository development, as also noted by Hamad et al. (2019) in Jordanian libraries, this study’s findings reveal the essential role of repositories in supporting interdisciplinary research. Libraries with sufficient resources for repository management can enhance access toshared data, promoting collaboration and innovation across research fields.Guidance on best practices and standards for data management further validates the importance of libraries in interdisciplinary research. Igbinovia (2017) observed that librarians are equipped to engage in cross-disciplinary RDM by supporting Sustainable Development Goals (SDGs) through knowledge-sharing and training. This finding aligns with the present study’s focus on librarians as knowledgeable resources who can standardize data management practices across fields, thereby addressing the unique challenges interdisciplinary researchers encounter with data diversity and management standards. Libraries, by providing consistent guidance on best practices, play a pivotal role in helping researchers across disciplines adhere to RDM standards, increasing data accessibility and reliability</p>

This study demonstrates the role that libraries play in supporting data management for interdisciplinary research, while also highlighting existing challenges and opportunities for enhancement. Libraries contribute significantly to data management planningby establishing frameworks and policies that provide a structured approach for researchers, reinforcing the importance of library-led data management initiatives. Through data literacy training, libraries address critical knowledge gaps, equipping researchers with essential skills to handle, store, and share data responsibly. This study underscores that targeted, discipline-specific training is especially valuable for interdisciplinary teams, as varying RDM practices often complicate data handling and sharing across fields.The development of data repositories by libraries facilitates data sharing and preservation, which are essential for interdisciplinary collaboration. However, resource constraints and limited infrastructure in some regions present barriers to fully leveraging repositories’ potential. Libraries with adequate technological resources provide robust support for data access and sharing, but disparities in access to these resources highlight the need for more consistent institutional and national support to strengthen repository capabilities across academic institutions. The study further concludes that libraries serve as critical advisors in guiding best practices and standards, helping researchers navigate the complexities of RDM with greater consistency and reliability. This role is vital in interdisciplinary contexts, where variations in methodologies and terminologies can lead to miscommunication and inefficiencies in data management. Although libraries are well-positioned to offer this guidance, challenges such as limited staff expertise, inadequate coordination with researchers, and underdeveloped infrastructure remain persistent obstacles.Based on the conclusions of this study, the following recommendations are derived. First, universities and research institutions should prioritize the development of specialized data management training programs tailored to address disciplinespecific needs, equipping researchers with practical skills in data handling, storage, and ethical considerations. Collaboration between research departments, libraries, and faculty members should be strengthened to design training relevant across disciplines, fostering a shared understanding of best practices in data management. These programs should be updated regularly to keep pace with evolving data management technologies and standards. Lastly, institutional stakeholders, including university administrations and national education bodies, should increase funding and resources for libraries to expand their RDM services. Support should target the creation or enhancement of data repositories, delivery of data literacy training, and provision of ongoing guidance on best practices in data management. With adequate resources, libraries can establish centralized RDM support hubs that offer infrastructure essential for interdisciplinary data sharing and collaboration.However, the study has some limitations. First, the study focused on a sample of faculty members from only two universities in Akwa Ibom State, Nigeria, due to accessibility and logistical considerations. This limited scope may restrict the generalizability of findings across other regions or institutions with different data management practices or RDM support structures. While the sample provided valuable insights, including additional institutions or a larger, more diverse sample could offer a broader perspective on interdisciplinary data management challenges and library support. On the other hand, the researcher faced time and resource constraints, which influenced the selection of study sites and participants. These limitations impacted the breadth of the research, as expanding the study to more universities or including additional data collection methods, such as interviews or focus groups, could have provided a richer understanding of the issues</p>