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This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

The increasing number of papers on zakah shows that it has become an important research topic. However, few studies attempt to analyze the evolution of zakah studies which might be helpful as guidance for policymakers in creating zakah management systems and policies, for zakah management organizations administering zakah funds, for future research on related subjects and for academic actors to construct a zakah study curriculum. This study aims to conduct a bibliometric analysis of the evolution of zakah theme publications from 1964 to 2021.

This study uses bibliometric analysis to analyze the evolution of zakah research. This study compared all Scopus-indexed journal papers to Zakah publications regarding research flow, themes, abstracts and titles. The relationships between researchers, the titles of the papers and keywords associated with “zakah” are analyzed in these publications published between 1964 and 2021. A total of 632 scientific contributions were discovered using RStudio and VOSviewer to analyze the bibliometric metadata.

Based on the results, the theme of zakah has evolved from 1964 to 2021. The author emphasizes the zakah publication theme. Each affiliation and country have its conditions, management method, data sources and characteristics. The theme “zakah institutions and zakah collecting” grew in popularity between 2010 and 2021 and is projected to grow in the following years. Malaysia, Indonesia and Pakistan can be used as zakah development research models. In spans of zakah publications, the author with the most global citations is Wahab N.A., and the author with the most productive is Saad Raj.

Zakah publications are analyzed using the Scopus database. This study applied only Scopus index data, excluding non-Scopus, and most studies conducted in non-English languages. This conclusion indicates the issue’s importance among academic researchers and practitioners, notably on the subject of zakah. Thus, a comprehensive picture of zakah theme publications assists researchers and zakah fund institutions in making assessments, focusing on the unstudied fraction of the zakah theme.

This research is planned to serve as a reference for future research, particularly examining the theme’s novelty. It is intended to have implications for policymakers, particularly zakah institutions, regarding funding the several zakah research issues and concentrations.

This research can guide future researchers and is expected to include parameters such as author, year and data source while analyzing zakah publications to generate new findings.

This is probably one of few comprehensive studies that examined the evolution of the zakah theme using the Scopus-indexed database. The relevance of this paper is to provide suggestions and projections for future zakah research. Scholars should examine zakah publications by author, year and data source to gain fresh insights. Search for data sources with high-impact factors and objective metrics, then clear out irrelevant documents to improve the analysis’ quality and findings.

This study aims to measure the global research landscape of the National Institute of Pharmaceutical Education and Research (NIPER) of India on a set of quantitative and qualitative metrics in terms of research output toward exploring research trends and give an overview of collaborative practices by researchers of NIPERs.

The present study has selected the Scopus database as a tool to retrieve potential publications of studied NIPERs during the last 12 years (2010–2021). NIPER-Mohali, NIPER-Hyderabad, NIPER-Ahmedabad, NIPER-Guwahati and NIPER-Kolkata have been selected for the study. The study has adopted a comprehensive search strategy to extract 3,926 publications data. VOS viewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The global scientific research output of NIPERs accrued 3,926 publications with an average of 327 publications per year. The retrieved publications fetched a total of 67,772 citations with an average citation impact of 17.26. There observed a steady growth of publications from 168 to 509 registered with an average growth rate of 18.44%. The mean relative growth rate and doubling time of research output are 0.26 and 2.94. The authorship patterns explore collaborative trends as most of the publications were published by multiple authors (99.39%). NIPERs have expanded their outreach to collaborate with the USA, Malaysia, Saudi Arabia, Australia and the UK to collaborate on research and regulatory reforms exhibits in the USA as a major contributor.

The present study is the first effort to evaluate the global research productivity of NIPERs and assess the current research trends on a set of quantitative and qualitative metrics to provide some insights into the complex dynamics of research productivity. The study’s outcome may help to identify the current research progress of NIPERs at the global level.

This article describes the interviews the authors conducted in late 2021 with 19 researchers at the Department of Classical Philology and Italian Studies at the University of Bologna. The main purpose was to shed light on the definition of the word “data” in the humanities domain, as far as FAIR data management practices are concerned, and on what researchers think of the term.

The authors invited one researcher for each of the official disciplinary areas represented within the department and all 19 accepted to participate in the study. Participants were then divided into five main research areas: philology and literary criticism, language and linguistics, history of art, computer science and archival studies. The interviews were transcribed and analysed using a grounded theory approach.

A list of 13 research data types has been compiled thanks to the information collected from participants. The term “data” does not emerge as especially problematic, although a good deal of confusion remains. Looking at current research management practices, methodologies and teamwork appear more central than previously reported.

Our findings confirm that “data” within the FAIR framework should include all types of inputs and outputs humanities research work with, including publications. Also, the participants of this study appear ready for a discussion around making their research data FAIR: they do not find the terminology particularly problematic, while they rely on precise and recognised methodologies, as well as on sharing and collaboration with colleagues.

The purpose of this study is to offer a checklist that can be used for both creating and evaluating digital collections, which are also sometimes referred to as data sets as part of the collections as data movement, suitable for computational use.

The checklist was built by synthesising and analysing the results of relevant research literature, articles and studies and the issues and needs obtained in an observational study. The checklist was tested and applied both as a tool for assessing a selection of digital collections made available by galleries, libraries, archives and museums (GLAM) institutions as proof of concept and as a supporting tool for creating collections as data.

Over the past few years, there has been a growing interest in making available digital collections published by GLAM organisations for computational use. Based on previous work, the authors defined a methodology to build a checklist for the publication of Collections as data. The authors’ evaluation showed several examples of applications that can be useful to encourage other institutions to publish their digital collections for computational use.

While some work on making available digital collections suitable for computational use exists, giving particular attention to data quality, planning and experimentation, to the best of the authors’ knowledge, none of the work to date provides an easy-to-follow and robust checklist to publish collection data sets in GLAM institutions. This checklist intends to encourage small- and medium-sized institutions to adopt the collection as data principles in daily workflows following best practices and guidelines.

Background: How many higher education researchers are there in the world? How many academic articles are published by researchers each year? This paper aims to answer these two questions by tracking the number of higher education teachers and the number of publications over the past four decades.

Methods: We collected data on the number of higher education institutions and researchers from the United Nations, the World Bank, and the US, China, and UK governments (three countries with the largest number of academic publications in recent years). We used Scopus to obtain the number of publications per year. The growth of higher education researchers and academic publications were characterized using 4-parameter logistic models.

Results: The number of higher education teachers-cum-researchers increased from 4 million in 1980 to 13.1 million in 2018 worldwide. Concurrently, the number of academic publications increased from 0.65 million in 1980 to 3.16 million in 2018 based on data from Scopus. At the country level, the number of academic publications from the USA increased from 0.15 million in 1980 to 0.70 million in 2018, while that from China increased by almost 1,000 times from 629 in 1980 to 0.60 million in 2018.

Conclusions: The number of higher education researchers would reach 13.6 million and they would publish 3.21 million academic articles in 2020, imposing enormous pressure to publishers, peer-reviewers, and people who want to understand emerging scientific development. Additionally, not all academic publications are easily assessable because most articles are behind pay-walls. In addition, unethical research practices including falsification, fabrication, plagiarism, slicing publication, publication in a predatory journal or conference, etc. may hinder scientific and human development.

The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to identify data mining related subject terms and topics in representative LIS scholarly publications.

A large set of bibliographic records over 38,000 was collected from a scholarly database representing the fields of LIS and the data mining, respectively. A multitude of text mining techniques were applied to investigate prevailing subject terms and research topics, such as influential term analysis and Dirichlet multinomial regression topic modeling.

The findings of this study revealed the relationship between the LIS and data mining research domains. Various data mining method terms were observed in recent LIS publications, such as machine learning, artificial intelligence and neural networks. The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.

This investigation is one of a few studies that empirically investigated the relationships between the LIS and data mining research domains. Multiple text mining techniques were employed to delineate to which extent the two research domains would be associated with each other based on both at the term-level and topic-level analysis. Methodologically, the study identified influential terms in each domain using multiple feature selection indices. In addition, Dirichlet multinomial regression was applied to explore LIS topics in relation to data mining.

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.

This paper aims to highlight the importance of open data and the role that knowledge management and open innovation can play in its identification and use. Open data has great potential to create social and economic value, but its main problem is that it is often not easily reusable. The aim of this paper is to propose a unique identifier for open data-sets that would facilitate search and access to them and help to reduce heterogeneity in the publication of data in open data portals.

Considering a model of the impact process of open data reuse and based on the digital object identifier system, this paper develops a proposal of a unique identifier for open data-sets called Open Data-set Identifier (OpenDatId).

This paper presents some examples of the application and advantages of OpenDatId. For example, users can easily consult the available content catalogues, search the data in an automated way and examine the content for reuse. It is also possible to find out where this data comes from, solving the problems caused by the increasingly frequent federation of data in open data portals and enabling the creation of additional services based on open data.

From an integrated perspective of knowledge management and open innovation, this paper presents a new unique identifier for open data-sets (OpenDatId) and a new concept for data-set, the FAIR Open Data-sets.

Despite the potential benefits of open government data (OGD) and its recent adoption by many governments, little is known about monitoring its use by the public. This paper aims to address the knowledge gap by empirically examining OGD usage in Tanzania.

A field survey design was used to gather quantitative data from 288 people in seven regions of Tanzania to facilitate an analysis of the determinants of users’ behavioural intention and use behaviour of OGD. Guided by the Unified Theory of Acceptance and Use of Technology model, the study analysed the tendencies of these determinants on the use of the OGD portal.

The results show that performance expectancy, effort expectancy, social influence and facilitating conditions affect users’ acceptance and use of the OGD portal. The results suggest that OGD initiatives should focus more on their potential applications than publication. It is important to monitor and evaluate OGD use and the conditions that allow it to continue. By linking OGD with other government initiatives, governments can build strategies, capacity and social awareness. During the development of OGD platforms for extensive reuse, new data technologies like the semantic web should be considered.

Hitherto, research has underlined the significance of OGD initiatives at large and that studies in developing countries are scarce, especially that probe the uptake of the current efforts. The present study seeks to plug this research gap by examining the use of OGD in Tanzania’s context.