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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.

The debate about academic librarians’ roles in research data management (RDM) services is currently relevant, especially in the context of making research data findable, accessible, interoperable and reproducible. This study aims to explore the RDM services offered by Malaysian academic libraries and the implementation progress based on the librarians’ practices and roles.

This descriptive study involves three sequential forms of data collection: a website analysis of 20 academic libraries relating to RDM services, training and policy; an online survey of the academic libraries’ RDM implementation progress; and semi-structured interviews with three academic librarians to gauge their practices and roles in RDM services.

Malaysian academic libraries provide RDM services based on their related or basic skills which are bibliographic management tools, institutional repository and openness of research data rather than impacted services to support RDM, such as data analysis, data citation, data mining or data visualisation services. Although the librarians were aware of RDM and their roles in research data services, the progress of practicing and implementation of the RDM services still has not been fully delivered to support the main RDM elements.

This study illustrates the RDM roadmap on the current landscape of areas and types of services that the libraries are doing well. The list of services can be used and implemented as the best practices or strategies to be applied within Malaysian academic libraries.

This study highlights the gaps of RDM services in Malaysian academic libraries. To the best of the authors’ knowledge, as this is the first study in Malaysia that articulates the case of RDM services in academic libraries, it has paved the way for further research.

The purpose of this paper was to systematically collect and review all studies which have been conducted on research data services in libraries across the globe.

Six world-renowned scholarly databases were searched and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used for the identification and selection of eligible studies. The studies were then assessed using a well-renowned framework for the quality assessment of research studies.

The results revealed that the libraries were engaged in providing different types of research data services such as identification, acquisition, management and preservation of research data. They also arranged training programs, supported the publishing and sharing of data and dealt with the licensing and copyright issues related to data.

The results of this study would be helpful for researchers and organizations, especially those engaged in educational activities, in understanding the current scenario of research data services in the world libraries. Furthermore, the findings offer valuable insights to library professionals regarding the types of research support services available globally. This would enable them to play an integral role in planning, designing and implementing such services in their libraries.

To the best of the authors’ knowledge, this study is the first of its kind that systematically collects and reviews the literature on research data services in libraries worldwide.

The purpose of this study was to establish the current skills base of librarians working in research data management services in academic and research libraries in South Africa. The purpose was also to determine the relevance of courses and programmes that are currently being offered by library and information studies programmes in response to the needs of research data management services and make recommendations on curriculum improvement.

About 13 institutions which were considered early adopters of research data management services were identified as participants in an online survey. In addition, a review of Web pages of existing library and information studies schools was carried to establish courses that would support research data management services. Data collected through the two approaches were analysed and presented quantitatively and qualitatively.

The findings reveal an environment in a developmental stage, with limited skilled personnel to run research data management services. The findings also show an absence of specific data librarianship courses within existing library and information studies programmes and a very limited scope for the full range of data management courses within professional development programmes.

The paper provides information on approaches to further develop existing curriculum and contribute to the data management needs and support governments, funders and publishers' requirements for the discoverability and re-use of research data across research domains.

The purpose of this paper is to describe the evolution to date and future directions in research data policy, infrastructure, skills development and advisory services in an Australian university, with a focus on the role of librarians.

The authors have been involved in the development of research data services at Griffith, and the case study presents observations and reflections arising from their first-hand experiences.

Griffith University’s organisational structure and “whole-of-enterprise” approach has facilitated service development to support research data. Fostering strong national partnerships has also accelerated development of institutional capability. Policies and strategies are supported by pragmatic best practice guidelines aimed directly at researchers. Iterative software development and a commitment to well-supported enterprise infrastructure enable the provision of a range of data management solutions. Training programs, repository support and data planning services are still relatively immature. Griffith recognises that information services staff (including librarians) will need more opportunities to develop knowledge and skills to support these services as they evolve.

This case study provides examples of library-led and library-supported activities that could be used for comparative purposes by other libraries. At the same time, it provides a critical perspective by contrasting areas of good practice within the University with those of less satisfactory progress. While other institutions may have different constraints or opportunities, some of the major concepts within this paper may prove useful to advance the development of research data capability and capacity across the library profession.

A major development in academic libraries in the last decade has been recognition of the need to support research data management (RDM). The purpose of this paper is to capture how library research data services (RDS) have developed and to assess the impact of this on the nature of academic libraries.

Questionnaire responses from libraries in Australia, Canada, Germany, Ireland, the Netherlands, New Zealand, the UK and USA from 2018 are compared to a previous data set from 2014.

The evidence supports a picture of the spread of RDS, especially advisory ones. However, future ambitions do not seem to have seen much evolution. There is limited evidence of organisational change and skills shortages remain. Most service development can be explained as the extension of traditional library services to research data. Yet there remains the potential for transformational impacts, when combined with the demands implied by other new services such as around text and data mining, bibliometrics and artificial intelligence. A revised maturity model is presented that summarises typical stages of development of services, structures and skills.

The research models show how RDS are developing. It also reflects on the extent to which RDM represents a transformation of the role of academic libraries.

Practitioners working in the RDM arena can benchmark their current practices and future plans against wider patterns.

The study offers a clear picture of the evolution of research data services internationally and proposes a maturity model to capture typical stages of development. It contributes to the wider discussion of how the nature of academic libraries are changing.

Research data management (RDM) has been called a “ground-breaking” area for research libraries and it is among the top future trends for academic libraries. Hence, this study aims to systematically review RDM practices and services primarily focusing on the challenges, services and skills along with motivational factors associated with it.

A systematic literature review method was used focusing on literature produced between 2016–2020 to understand the latest trends. An extensive research strategy was framed and 15,206 results appeared. Finally, 19 studies have fulfilled the criteria to be included in the study following preferred reporting items for systematic reviews and meta-analysis.

RDM is gradually gaining importance among researchers and academic libraries; however, it is still poorly practiced by researchers and academic libraries. Albeit, it is better observed in developed countries over developing countries, however, there are lots of challenges associated with RDM practices by researchers and services by libraries. These challenges demand certain sets of skills to be developed for better practices and services. An active collaboration is required among stakeholders and university services departments to figure out the challenges and issues.

The implications of policy and practical point-of-view present how research data can be better managed in the future by researchers and library professionals. The expected/desired role of key stockholders in this regard is also highlighted.

RDM is an important and emerging area. Researchers and Library and Information Science professionals are not comprehensively managing research data as it involves complex cooperation among various stakeholders. A combination of measures is required to better manage research data that would ultimately move forward for open access publishing.

The purpose of this paper is to describe how the authors gained a better understanding of the variety of library users' data needs, and how gradually some new data services were established based on current capabilities.

This paper uses a case study of the new data services at the John Cotton Dana Library, at Rutgers, The State University of New Jersey, Newark campus, to demonstrate the possible ways to extend data reference services and provide data computing services. A content analysis of services records shows how each user group falls into the multiple data services levels and subcategories.

Library users can be classified into many different categories, and each of these may have different needs. Research centers might have big projects involving data gathering and applications where a librarian can mainly provide consultation; while an individual faculty member or student might need the librarians as research partners, with help for their specific problems. Computing data services can involve group training and statistical analysis assistance, where researchers need emergent help. Data librarians can take various opportunities for data management education, thereby gradually raising awareness and cultivating better research habits among researchers.

Library data computing services can make unique contributions to faculty and students' research and study. Institution, library and users' interaction determines the levels and extent of data services and is generalized from the description and analysis of typical data service examples. Classic concept of data services levels is applied to a concrete case of data services program, and sub‐categories of each data services level and user types are developed based on the authors' services record.

This study aims to investigate the perceptions of academic librarians regarding research data services (RDS) in academic library environments. This study also examines a range of challenges in RDS from the perspectives of academic librarians.

A nationwide online survey was administered to academic librarians engaged in data services at research universities around the USA. The collected survey responses were analyzed quantitatively using descriptive statistics, hierarchical clustering and multidimensional scaling.

Academic librarians perceived that consultation services would be more valuable to users than technical services in offering RDS. Accordingly, skills associated with consultation services such as instructional skills and data management planning were perceived by participants to be more important. The results revealed that academic libraries would need to seek collaboration opportunities with other units on campus to develop and offer RDS, especially technical services.

This study contributes to the existing body of research on the topic of data services in research universities. The study investigated various types of specific professional competencies and used clustering analysis to identify closely associated groups of service types. In addition, this study comprehensively examined both relevant resources for and barriers to RDS.

This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to semantically enrich data services, so that they can dynamically provide both semantic descriptions and data representations.

The enrichment approach is designed to intercept the requests from data services. Therefore, a domain ontology is constructed and evolved in accordance with the syntactic representations provided by such services in order to define the data concepts. In addition, a property matching mechanism is proposed to exploit the potential data intersection observed in data service representations and external data sources so as to enhance the domain ontology with new equivalences triples. Finally, the enrichment approach is capable of deriving on demand a semantic description and data representations that link to the domain ontology concepts.

Experiments were performed using real-world datasets, such as DBpedia, GeoNames as well as open government data. The obtained results show the applicability of the proposed architecture and that it can boost the development of semantic data services. Moreover, the matching approach achieved better performance when compared with other existing approaches found in the literature.

This work only considers services designed as data providers, i.e., services that provide an interface for accessing data sources. In addition, our approach assumes that both data services and external sources – used to enhance the domain ontology – have some potential of data intersection. Such assumption only requires that services and external sources share particular property values.

Unlike most of the approaches found in the literature, the architecture proposed in this paper is meant to semantically enrich data services in such way that human intervention is minimal. Furthermore, an automata-based index is also presented as a novel method that significantly improves the performance of the property matching mechanism.