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This paper aims to assess whether the current eResearch Knowledge Centre’s (eRKC) research support practices align with researchers’ requirements for achieving their research objectives. The study’s objectives were to assess the current eRKC research support services and to determine which are adequate and which are not in supporting the Human Sciences Research Council (HSRC) researchers.

This study uses interviews as part of the qualitative approach. The researcher chose to use interviews, as some aspects warranted further explanation during the interview. The interviews were scheduled using Zoom’s scheduling assistant. The interviews were semi-structured, guided by a flexible interview procedure and supplemented by follow-up questions, probes and comments. The research life cycle questions guided the interviews. The data obtained were coded and transcribed using MS Excel. The interview data were analysed, using NVivo, according to the themes identified in the research questions and aligned with the theory behind the study. Pre-determined codes were created in line with the six stages of the research life cycle and applied to group the data and extract meaning from each category. Interviewee responses were assigned to groups in line with the stages of the research life cycle.

The current eRKC research support services are aligned with the needs of HSRC researchers and highlight services that could be expanded or promoted more effectively to HSRC researchers. It proposes a new service, data analysis, and suggests that the eRKC could play a more prominent role in research impact, research data management and fostering collaboration with HSRC research divisions.

This study is limited to assessing the eRKC’s support practices at the HSRC in Pretoria, South Africa. A more comprehensive study is needed for HSRC research services, capabilities and capacity.

Assessment of eRKC followed a comprehensive interviewee schedule that followed Raju and Schoombee’s research life cycle model.

Zoom’s scheduling assistant may have generated Zoom fatigue and reduced productivity. Technical issues, losing time, communication gaps and distant time zones may have affected face-to-face interaction.

eRKC research support practices are rare in South Africa and most parts of the world. This study bridges the gap between theory and practice in assessing eRKC research support practices.

One of the most critical changes to academic library services in the last decade has been the development and implementation of research data services (RDS). This paper seeks to provide a comprehensive understanding of conceptual models for the RDS space.

An extensive and comprehensive review of the literature on conceptual models for RDS is performed.

Various conceptual models for RDS provide a compelling tool for guiding and evaluating RDS development and implementation within academic libraries.

An insightful review and synthesis of context and issues in RDS models will help academic libraries to plan, develop and advance their RDS.

In today's global and competitive corporate environment characterised by rapidly changing information, knowledge and technology (IKT), researchers must be upskilled in all aspects of research data management (RDM). This study investigates a set of capabilities and competencies required by researchers at selected South African public universities, using the community capability model framework (CCMF) in conjunction with the digital curation centre (DCC) lifecycle model.

The post-positivist paradigm was used in the study, which used both qualitative and quantitative methodologies. Case studies, both qualitative and quantitative, were used as research methods. Because of the COVID-19 pandemic rules and regulations, semi-structured interviews with 23 study participants were conducted online via Microsoft Teams to collect qualitative data, and questionnaires were converted into Google Forms and emailed to 30 National Research Foundation (NRF)-rated researchers to collect quantitative data.

Participating institutions are still in the initial stages of providing RDM services. Most researchers are unaware of how long their institutions retain research data, and they store and backup their research data on personal computers, emails and external storage devices. Data management, research methodology, data curation, metadata skills and technical skills are critically important RDM competency requirements for both staff and researchers. Adequate infrastructure, as well as human resources and capital, are in short supply. There are no specific capacity-building programmes or strategies for developing RDM skills at the moment, and a lack of data curation skills is a major challenge in providing RDM.

The findings of the study can be applied widely in research, teaching and learning. Furthermore, the research could help shape RDM strategy and policy in South Africa and elsewhere.

The scope, subject matter and application of this study contribute to its originality and novelty.

As a part of doctoral study, this study aims to analyze research on library management models (LMMs) by conducting a systematic literature review (SLR).

A Preferred Reporting Items for Systematic Review and Mata-Analysis approach was used to search four databases. The search criteria included studies published in English until 2022, resulting 9,125 records. Out of these records, a total of 36 studies were selected for final analysis

The results show a positive attitude among researchers toward the development of LMM for libraries globally. The results depict that more than one-third (39%) of the target population was comprised of academic staff and students. The majority (91.76%) of studies were conducted using survey. Quantitative methods were predominant (89%) for LMMs. There were a significant number of studies conducted in 2016. The country-wise distribution shows the USA and China each contribute (20%) of the studies.

The findings of this research could assist policymakers and authorities in reconciling the LMMs applied in libraries for providing efficient access to information resources and services to end users.

To the best of the authors’ knowledge, this study is unique as no comprehensive study has been conducted on LMMs using the SLR method.

The purpose of the present study was to identify the conditions that affect the absorptive capacity (AC) of knowledge, discover its consequences and design an AC paradigm pattern in public academic libraries. To do so, AC was investigated at the levels of individual and organizational learning.

In this paper, to answer the three major questions of this qualitative-survey study, the views of 24 experts were examined using an in-depth semi-structured interview and grounded theory strategy. The data were collected using a nonrandom combined targeted sampling procedure (targeted and snowball) and analyzed based on Strauss and Corbin’s (1998) approach and utilizing MAX Qualitative Data Analysis (MAXQDA) software.

Throughout the grounded analytic stages, 121 open codes were identified. These were distributed around the AC axial category in academic libraries in terms of individual and organizational learning. The 33 axial concepts were then categorized into 16 selective general categories. The paradigm pattern was initially designed to explore the relationships between causal, intervening, strategies, context and consequences conditions. The transition from academic libraries to learning organizations, their increased functional value and the development of their innovation were identified as the consequences of AC development.

This qualitative research is the first in the field of Library and Information Science (LIS) to support AC both theoretically and empirically in terms of learning in academic libraries. This study thus not only addresses a key research gap in LIS but also provides significant insights and direction to interested librarians and researchers.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

This study aims to examine the state of embedded librarianship in African academic libraries by exploring the extent of librarian embedment in research processes in selected academic libraries in Africa.

A survey was conducted to collect data using an online questionnaire. The study population was comprised of librarians who directly support researchers throughout the research process in the scholarly communication and information services sections. Purposive sampling was used to select librarians, and 63 responses were received from the target of 100. The collected data were analysed using the statistical package for the social sciences (SPSS) software, and content analysis was used to analyse open-ended questions.

The study results showed that the extent and nature of librarians' embeddedness in the research process vary across different university contexts in Africa. Challenges and areas of research skill gaps among librarians were identified, and propositions to address the research skill gaps were provided.

The study findings can be used as a framework for libraries to embed librarians in the research process. The study made recommendations with practical implications for library practitioners in academia, and institutions offering library and information science education, and the library management responsible for the research process.

A study brings a novel perspective by examining the state of embedded librarianship in the African context. Its contribution generates knowledge and insights that inform the development of effective embedded librarianship practices in African academic libraries to enhance research support services and advancement of scholarly research in the region.

The academic library’s physical capacity and its service obligations to local users structured the traditional print collection. Largely freed of these constraints, the digital collection manager enjoys unprecedented freedoms but now contends with a collection susceptible to resource sprawl and scope ambiguity. This exploratory study aims to consider the possibility that intra-field social processes help to structure and routinize digital collection practice.

Lacking the constraints to which print collections are subject, electronic resource and digital library collections are more likely to reflect idiosyncratic institutional interests and therefore, to demonstrate significant variation. Evidence of homogeneity may suggest the influence of heretofore underexplored social structures. To determine the extent of such homogeneity, the author performed exploratory/descriptive content analyses on ten electronic resource collection development policies and six digital library collection development policies.

The data reveal among both the electronic resource and digital library collection policies significant uniformity. Content analyses demonstrate consistent themes (e.g. media, audience, selection priorities, etc.) and rhetoric. These findings lend support to the study’s central hypothesis regarding latent social structures. Analyses also reveal a set of unanticipated constraints unique to digital collection management.

Despite the breadth and maturity of literature addressing the Digital Turn in academic librarianship, relatively little attention has been paid to the social dimensions of collection management. This work represents an important corrective and suggests new theoretical approaches to the study of digital collection practice.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.