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Background: This article presents a methodology to categorize scientific publications according to the targets of the 17 Sustainable Development Goals (SDGs) of the United Nations. For the above, a dataset with bibliographic and descriptive attributes of 2,379 articles from 2017 by co-authors affiliated to the Pontificia Universidad Católica de Chile, indexed in the Web of Science and Scopus databases, was used.

Methods: The methodology considered three relevant and consecutive milestones: establishment of the reading level that was applied for each publication record, which considers a proportional amount of information; assignment of one of the 18 categories identified for the analysis of the information, which include the 17 SDGs and the option “unclassified” and one of the 169 subcategories corresponding to the specific goals; and, finally, recording the status of the review process carried out, which allowed control of the progress and quality of the cross-review.

Results: The results show that 58.6% of the articles contribute to a primary target, of these 233 contribute to a secondary target; goals 3, 4, 9, and 11 are the most frequent in the process of assigning SDGs. There is an 81% increase in the use of alphanumeric targets when they are assigned as secondary targets. At the same time, cross-checking is shown to be beneficial when allowing the reclassification of 190 articles to some of the targets. Finally, it is established that levels 2 and 3 enabled better classification, given that the contents considered provide more information; however, it is significant that through level 1, 355 articles were categorized as “unclassified”.

Conclusions: It is concluded that the methodology allows for a conclusive, exhaustive, rigorous, extensive, and varied classification through the different milestones and actions carried out, providing strategic information for decision making and research management in the academy-society relationship.

In this study, the authors want to identify current possible causes for citing and referencing errors in scholarly literature to compare if something changed from the snapshot provided by Sweetland in his 1989 paper.

The authors analysed reference elements, i.e. bibliographic references, mentions, quotations and respective in-text reference pointers, from 729 articles published in 147 journals across the 27 subject areas.

The outcomes of the analysis pointed out that bibliographic errors have been perpetuated for decades and that their possible causes have increased, despite the encouraged use of technological facilities, i.e. the reference managers.

As far as the authors know, the study is the best recent available analysis of errors in referencing and citing practices in the literature since Sweetland (1989).

This study aims to explore the status of collaborative research productivity, major library and information sciences (LIS) research trends and the level of research among the LIS academicians as principal authors in Pakistan during 1975–2021 (47 years).

A quantitative research method was adopted to collect the required data using bibliometric patterns. The data of all faculty members working in LIS schools of Pakistan was collected from the official website of their employers/institutions. Different strategies were used to acquire respondents’ bibliographic/publication records such as faculty members’/employers’ official websites and faculty members’ Google Scholar profiles; advanced searching techniques were also used to retrieve their bibliographic records.

The results revealed that a total of 74 regular faculty members comprising 78.38% males and 21.62% females are working in 12 LIS Pakistani schools. A total of 1,787 papers were produced by LIS faculty, among which 702 were written by Pakistani LIS faculty as principal authors during the selected period. The results revealed that 60.72% of the principal authors’ work was produced in collaboration. The collaboration between faculty members and other faculty was 81%, while two authors' work productivity was on the top. No attention has been given to produce research in collaboration with international/foreign LIS experts, especially from developed countries.

The findings of this study are useful for faculties to have a richer understanding of the various elements of collaboration at national as well as international levels, and then discover the ways to begin and maintain effective partnerships to research emerging trends in LIS.

This study is a unique bibliometric study that systematically and quantitatively combined the research productivity of LIS academicians in Pakistan and provided a holistic sketch of the literature produced on various themes of LIS during 1975–2021.

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.

Records are current documents containing crucial personal, legal, financial and medical information, while archives house non-current documents with the same details. This study specifically aims to measure existing research in records and archives management with various scientific indicators.

Data extraction was conducted using the Web of Science, resulting in a data set of 2003 records for further analysis. Biblioshiny and VOSviewer have been used for mapping and visualization of the extracted data.

Managing and organizing this essential information is equally vital to maintaining records and archives. The findings encompass various aspects such as publications and citations, influential authors, source impact factors, relevant articles, affiliations, co-authorship trends across the top 10 countries and regions, references, publication year spectroscopy, keyword co-occurrence and historiography. The study concludes that medical records management prominently dominates the selected research area.

The study reflects the advancements in management systems and continues to emerge as research on the management of records and archives has gained significance.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

The purpose of this study is to depict the value added by digital transformation to intellectual capital (IC) by virtue of the studies reached by the literature review on different databases are examined.

Journal of Intellectual Capital, which has the highest number of records from the resources included in the “Web of Science” content and covering the title of “intellectual capital” has been selected in this study. Research using bibliometric analysis has been conducted and it has been determined that the terms “digital transformation” and “intellectual capital” should be searched for simultaneously in each and every article published in the journal between the years 1975 and 2022.

A bibliometric analysis and citation mapping process are carried out considering all dimensions to reach the results and interpretation of findings. VOSviewer is used to visualize the bibliometric networks of results and findings in the form of scientific mapping, as well as to visualize the co-authorship analysis of keywords, co-authorship analysis and citation networks.

Bibliometric analysis is a method that can be used to evaluate the performance of a single journal. However, it is important to note that bibliometric analysis has some limitations when it comes to assessing the validity of a single journal. This circumstance is elaborately described as a limitation of this study. Bibliometric analysis is a method that can be used to evaluate the performance of a single journal. However, it is important to note that bibliometric analysis has some limitations when it comes to assessing the validity of a single journal. One limitation is that bibliometric analysis is based on quantitative metrics, such as citation counts, which do not take into account the quality of the research. Therefore, bibliometric analysis alone may not provide a complete picture of the validity of a single journal. In addition, bibliometric analysis is based on the number of times a paper is cited, which can be influenced by factors such as the prestige of the journal, the field of research and the time since the publication. In conclusion, bibliometric analysis can be used to evaluate the performance of a single journal, but it is important to consider its limitations.

This study identified contributions, gaps and limits based on the results of a bibliometric analysis. Italy is the most influential country and the issue is structured around four clusters: IC; digital transformation; human capital; and knowledge management. As previously unexplored issues are addressed in an innovative manner, it is acceptable to underline the paper’s originality.

This study aims to examine the status, explores the hurdles and identifies the prospects for developing a union catalogue of university libraries in Lahore, Pakistan.

Following a quantitative research approach, a questionnaire was developed from literature and authors’ experience. After ensuring its validity and reliability, data were collected from librarians after the census. A total of 105 librarians were approached, of whom 73 (71%) responded to the survey.

University libraries in Lahore are well organized, have adequate collections and information technology-literate staff, are well automated, have good internet connections, are equipped with integrated software, follow cataloguing rules and MARC standards; however, the absence of standardized software, lack of funds, absence of uniform policy, professional workload and absence of standardized vocabulary are significant challenges. Private-sector librarians reported facing more challenges. Librarians consider all prospects vital for developing a union catalogue. These prospects include the availability of relevant information, incentives to librarians, coordination with librarians, a realization that sharing is caring, the Higher Education Commission of Pakistan taking initiative and librarians’ training.

University librarians in Lahore are ready to cooperate with the development of a union catalogue; however, they seek support from higher authorities, professional library associations and the Higher Education Commission of Pakistan.

To the best of the authors’ knowledge, this research is the first of its kind that examines the status, explores the hurdles and identifies the prospects for developing a union catalogue of university libraries in Lahore. It would lead to the development of a union catalogue of university libraries in Pakistan.

Sustainability has been the subject of several scientific investigations. Many researchers in the construction industry have also examined a range of sustainability-related studies. However, few studies have thoroughly reviewed implementing sustainability concepts in high-rise residential buildings (HRRBs).

By adopting scientometrics and systematic review (SR), this study seeks to map out recent sustainability trends and concepts in the design, development and operation of HRRBs worldwide and in Hong Kong. With a focus on bibliographic records from the Web of Science (WoS) database, 1,395 journal articles from 2013 to 2022 were analysed. Furthermore, thirteen studies were systematically reviewed.

The SR indicated that sustainable practices in developing Hong Kong's HRRBs emphasised zero-carbon buildings, reduced energy usage and energy-efficient retrofitting. Likewise, terms such as BIM, urban density, life cycle assessment and system dynamics are strongly connected with clusters that include “residential buildings”, “high-rise buildings” and “high-rise residential buildings”. The study identified significant themes in establishing HRRBs by combining sustainable practices, emphasising urban governance and policy management, building performance and thermal comfort, energy and design optimisation, occupant behaviour and sensitivity analysis. Core sustainability ideas have improved resource management, air quality management and knowledge of user behaviour in HRRBs.

The study allows researchers and practitioners to explore future research directions in the built environment per the application of sustainable concepts in the development of HRRBs from design, construction and post-construction phases.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.