Libraries and librarians will benefit by acquiring a collection of open access information resources. The OA movement in Bangladesh is being developed to reduce the huge pressure on the library budget for subscriptions to journals. In most developed countries, university libraries view open-access materials as an important part of their collection development strategy. In this study, we examine the current state of OA resources in public university libraries in Bangladesh, collection development policies, the library authority's perspectives, the challenges libraries face in including OA resources in their collection development, and how to overcome those obstacles. Methodology: A survey and a stratified random sample technique were used in this study. A total of 276 students and 268 faculty members were surveyed. The first six public universities (in order of date of establishment) were selected. We sent out questionnaires directly to students, library personnel, librarians, and other library officials. Using library websites, journals, official records, and Google Scholar was another step. Findings: This study indicates that although open access materials may be quite useful in the growth of collections, most academic library authorities seem unconcerned about this. The utilization of open access materials in the overall collection is visible, but it is insignificant.
People do not search information as such but seek to get a job done or to manage a situation by the help of search results. Therefore, the ultimate goal of information search is to advance task performance. It should be evaluated accordingly, i.e. by its contribution to task outcome. This implies an extended notion of search process, which also covers the use of information in search results for task outcome. For measuring the effect of search to task outcome we propose both indirect and direct indicators which measure search success.
Over the last few decades, scholarly communication is changing with the use of social media serving as an effective medium. Several new factors have emerged in the context of social media activity to accelerate the shift. The current research relied on the ResearchGate platform, an Academic Social Networking Site (ASNS), meant for scientists and scholars enabling them to share, communicate, collaborate, connect and get updated with the feeds and scholarly information. The study focused on the top 15 cited Indian researchers and their research performance on ResearchGate. The research data was collected manually and analysed using several altmetric parameters available on ResearchGate to evaluate the performance of the targeted researchers. For statistical correlation analysis, the researcher relied on JASP statistical analysis software (v. 0.16.0.0). The study findings reveal that Sujit K Bhattacharya has the maximum citations (17210) among Indian researchers on ResearchGate, accompanied by the maximum number of publications (505), the highest value of h-index (70) and Research Interests (8991). The majority of the contributions from the targeted researchers are research articles (71.95%) and 49.10% are available in full text. Researcher S G Deshmukh has asked the maximum number of questions (22), and also provide a significant number of answers (314). The publications of researcher K. M. Singh (Res. 15) received a maximum number of Read (529397), and recommendations (3179). The RG Score of S G Deshmukh is the highest (57.00) among all of the targeted researchers. Pearson’s Correlations Test among five interconnected variables calculated that among 7 different types of correlation formation, “Citations - Res. Int.” (0.920), “Publications - Res. Int.” (0.865), “RG Score - Res. Int.” (0.773), and “Publications - RG Score” (0.765) pairs possess highly positive correlation linkage. The core context of this study is helpful for the representation of India in terms of top-cited researchers and their research performance on ResearchGate. The study also promotes young researchers to disseminate their research over such ASNS platforms to increase visibility and research impact.
This study suggests a pragmatic approach to the authority control process in library cataloguing systems in order to develop a better database that facilitates speedy information retrieval from library OPACs. The authority control method also creates a unified bibliographic database with separate access points for both library users and library professionals. To review the authority control procedure for the sake of this study, we used free and open-source library management software, namely Koha. Different methods are followed by the Koha administration and its cataloguing module. The bibliographic and authority frameworks are very helpful and conducive to all the libraries and information centers. The originality of this study has been successfully demonstrated by library cataloguers’ observations on frequent strategies for carrying out the authority control processes.
Dr. S. R. Ranganathan, an Indian librarian and educator who is known as the 'Father of Library Science in India', is also widely known throughout the rest of the world due to his worldwide contribution to library science. Earlier it was difficult to find citations to prominent old research works. New computer technology helps find these types of articles more easily and it also finds sleeping beauties in several disciplines. Here the term 'Sleeping beauty' is used to define a research article life (year) that has been relatively uncited for several years and then suddenly attracts a lot of attention. The present paper describes four sleeping beauties that are found from Ranganathan’s contributions (books only) in library science, such as; Colon Classification (1933), Prolegomena to Library Classification (1937), Philosophy of Library Classification (1951) and Reference Service (1961). Above mentioned four sleeping beauties are detected using three main criteria; depth of sleep, length of sleep, and awakening intensity given by Van Raan (2015) to detect the sleeping beauties.
In our previous article (Digital Access Brokers: clustering and comparison (Part I - locator services), we covered a total of twelve browser extensions under one broad group viz. Group A- Locations, Citations & References. This paper covers another twenty-two more browser extensions under four major groups viz. Group B- Summarizers, Recommenders & Commenters; Group C- Multi Functional; Group D - Resource Integration; and Group E- Citation Map Builder. All of these tools assist researchers in a variety of ways in obtaining content, both open-access and licenced content owned by various publishers or databases.
This paper seeks to analyze information search process in complex tasks1. Complex tasks are larger tasks, which lead people to engage in search tasks for finding information to advance those tasks. Search process consists of activities from query formulation to working with sources selected for task outcome. This paper approaches task performance from the cognitive point of view conceptualizing it as changes in knowledge structures. These structures consist of concepts and their relations representing some phenomenon. Changes in knowledge structures are associated to query formulation and search tactics, selecting contributing sources and working with sources for creating task outcome. As a result, hypotheses concerning associations between changes in knowledge structures and search behaviors are suggested. The paper also presents some ideas for success indicators at various stages of search processes.
Universal Decimal Classification (UDC) is a popular controlled vocabulary that is used to represent subjects of documents. Text categorization determines a text's category, as evident from the notation-text label format of the Universal Decimal Classification. With the help of machine learning techniques and the Universal Decimal Classification (UDC), the present work aims to develop an end-user (library professional) based recommender system for automatically classifying documents using the UDC scheme. The proposed work is conceived for determining and constructing a complex class number using the syntax of Universal Decimal Classification (UDC). A corpus of documents classified with the UDC scheme is used as a training dataset. The classification of the documents is done with human mediation having proficiency in classificatory approaches. The BERT model and the KNIME software are used for the study. This study uses the classified dataset to fine-tune the pre-trained BERT model to construct the semi-automatic classification model. The results show that the model is constructed with high accuracy and Area Under Curve (AUC) value, although the prediction represented a low accuracy rate. This study reflected that if the model is explicitly trained by annotating each concept and if the full licensed version of UDC class numbers becomes available, there is a greater potency of developing an automated, freely faceted classification scheme for practical use.
In the digital era, libraries have been acquiring and subscribing to various types of digital resources. Each e-resource possesses distinct formats and search requirements, offers multiple access and authentication methods, and involves complex licensing agreements. Therefore, effectively managing these diverse e-resources necessitates a system that simplifies the processes of acquisition, access, and organization. An Electronic Resource Management System (ERMS) presents a potential solution for centralizing these operations. Numerous open source and commercial ERMS solutions are available and utilized in libraries worldwide. Nevertheless, numerous studies have revealed that libraries face financial constraints as well as limitations in terms of ICT infrastructure. An ideal solution should be both cost-effective and require minimal ICT infrastructure. Koha is one such software that has gained popularity in library automation, making it a viable option for managing e-resources. This study explores the implementation of Koha, version 22.11, for managing a library's e-resources. The study aims to investigate the existing features and functionalities of Koha in the context of libraries.
This study utilizes GPT (Generative Pre-Trained Transformer) language model-based AI writing tools to create a set of 80 academic writing samples based on the eight themes of the experiential sessions of the LTC 2023. These samples, each between 2000 and 2500 words long, are then analyzed using both conventional plagiarism detection tools and selected AI detection tools. The study finds that traditional syntactic similarity-based anti-plagiarism tools struggle to detect AI-generated text due to the differences in syntax and structure between machine-generated and human-written text. However, the researchers discovered that AI detector tools can be used to catch AI-generated content based on specific characteristics that are typical of machine-generated text. The paper concludes by posing the question of whether we are entering an era in which AI detectors will be used to prevent AI-generated content from entering the scholarly communication process. This research sheds light on the challenges associated with AI-generated content in the academic research literature and offers a potential solution for detecting and preventing plagiarism in this context.
Physical stacks in academic libraries, despite the advent of digital repositories, remain important to users, especially in countries like India where physical resources hold considerable value. This study seeks to develop a system that enables users to locate books physically by integrating stackmaps functionalities with Koha OPAC. In addition, the study showcases how an open-source text analytics server can be incorporated inside an OPAC in Koha to generate various word-level visualizations by analyzing a text corpus, including the identification of geospatial features such as place names. This research aims to contribute to the advancement of information retrieval and visualization techniques in OPACs in academic libraries, and to improve the user experience in locating physical resources. (The video abstract of this paper may be found at: https://youtu.be/q940TUkcTTE ).
Since ancient times, books have been utilized as a therapeutic aid. However, its function and mode of operation have surely changed over time. It is the field of study that examines how writing might be used and how it might affect people's lives. Under the direction of a trained assistant, it is an act of interactive interplay between the reader's personality and the literature. People have various mental health issues, challenges, and difficulties in recent years. Bibliotherapy is a concept where, with the help of books, people manage their lives and their challenges. This study aims to see the efficacy of bibliotherapy in patients with obsessive-compulsive disorder (OCD) and depression. Based on this experiment, researchers propose a conceptual framework for libraries. A book by Catherine M. Pittman titled "Rewire Your OCD Brain: Neuroscience-Based Skills to Break Free from Obsessive Thoughts and Fears" served as the primary data gathering tool for this research, which was carried out using an experimental methodology. The study's findings demonstrate a substantial difference between the experimental and wait-list groups in the treatment of mild to moderate OCD and depression symptoms with the application of bibliotherapy. Based on the findings, a conceptual framework with some recommendations has been suggested.
The present study discusses data migration and various issues involved in data cleansing and standardization. Libraries are moving to the popular open-source ILMS Koha. The paper describes the design of a data migration framework from proprietary Integrated Library Management Software (ILMS) to Koha. The issues related to data quality in source ILMS and processes involve understanding and correcting raw data. The paper highlights the methods, tips and tricks, configurations, and data migration in open ILMS Koha. Studies proved Open Source Solutions (OSS) such as Koha for library automation is the better choice as it supports customization at a minimal cost. The paper examines the errors, mistakes and lack of uniformity of data in source databases and methods for quality enhancement of raw data. The current article is of practical significance for those who wish to migrate from existing ILMS to open-source solutions like Koha. The paper covers the migration of bibliographic data, member data and transaction data.
Perceptions about Indian media vary and are dependent on where you are located as within the country or part of the Indian diaspora or established media outlets' view quite often described as western media. To Indians, the shrillness of TV news debates and the so-called diverse panellists' perspectives reflects one aspect of how liberal Indian media can be, as well as the tempered variations of the same in the daily newspapers of your choice. Intellectuals are worried and critical about the skewed nature of such debates and their proximity to the ruling polity dispensation. Some express their views or concerns through write-ups in media outlets outside the country. The growth of news media outlets sectoral, as in newspapers, radio, television etc. or converged as in the present digital ecosystem, is imbued within the media's relationship to the formation and sustenance of democratic structures and upheld freedom as an abiding principle. Indian media in the past has always been regarded as relatively accessible when compared to many other developing contexts and is now being debated as the shift from an editorial policy-driven entity to a platform-based content in a free for all user-generated content has occurred not only in India but in other countries as well. The transition from explicit frameworks as laws and ethics to regulating social media platforms is dynamic as well problematic when weighed against conventional notions for freedom of media etc. What, then, are some of the issues and or challenges in the Indian digital ecosystem that will be the focus of this invited article.
There are several ways to employ machine learning for automating subject indexing. One popular strategy is to utilize a supervised learning algorithm to train a model on a set of documents that have been manually indexed by subject matter using a standard vocabulary. The resulting model can then predict the subject of new and previously unseen documents by identifying patterns learned from the training data. To do this, the first step is to gather a large dataset of documents and manually assign each document a set of subject keywords/descriptors from a controlled vocabulary (e.g., from Agrovoc). Next, the dataset (obtained from Agris) can be divided into – i) a training dataset, and ii) a test dataset. The training dataset is used to train the model, while the test dataset is used to evaluate the model's performance. Machine learning can be a powerful tool for automating the process of subject indexing. This research is an attempt to apply Annif (http://annif. org/), an open-source AI/ML framework, to autogenerate subject keywords/descriptors for documentary resources in the domain of agriculture. The training dataset is obtained from Agris, which applies the Agrovoc thesaurus as a vocabulary tool (https://www.fao.org/agris/download).
Academic writing has played an essential role in communicating the cognitive aspects of the human mind. Natural Language Processing (NLP) tools enable us to examine linguistic knowledge. However, writing patterns and applicable linguistic characteristics differ geographically. The study's primary purpose is to understand the global writing pattern and linguistic diversities of research articles in the LIS domain. The corpus was identified from four SCOPUS-enrolled open-access libraries and information science journals. The journals published in India and outside India were selected for the study in 2020. The syntactic complexity in 147 text documents was measured using the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TASSAC). The corpus was further examined using the Structural Equation Model (SEM) to determine the causal relationship among independent variables such as syntax features and readability scores. The results depict the differences in the patterning of syntactic features at both the global and national levels. Furthermore, the study allows us to see how linguistic diversity is underplayed in research writings and helps to understand writing patterns through cross-country comparisons. Furthermore, the paper employs model-based reasoning to identify global and national latent variables.
Wikidata is emerging rapidly as an omnipresent information space. The main objective of Wikidata is to create a structure to represent all human knowledge in many different languages. It is a free, Linked Open Dataset (LOD) that can interact with humans and machines and act as a bridge between them. Wikidata serves as a central repository for structured data of all other Wiki-based applications (like Wikipedia, Wikibooks, and Wikinews), integrating them into a coherent unit. It is a multilingual, collaboratively editable central repository of structured and linked open data. Interestingly, Wikidata is based on a facet-based linked open data approach like, the theory of facet analysis proposed by Ranganathan. The literary works available in Wikidata are linked with the author of the work, the language of the work, and other important attributes like genre, publication year, and so on. The author of the work has properties like, date of birth, occupation, native language, writing language, and so on. These faceted linked data elements of literary works can be joined together based on the rule base of the Colon Classification (6th edition). The synthesis of the Colon class number is therefore amenable to automation in the Wikidata environment by using a set of suitable JavaScripts (these JavaScripts are called gadgets in the Wikidata environment). One such gadget is CCLitBox, developed by Stefano Bargioni (a librarian) and Carlo Bianchini (a teacher in LIS). This research study explores the applications of CCLitBox in generating CC 6th edition-based class numbers for Indian literary works.
This paper attempts to study ‘Emotional Intelligence’ (EI) to understand the library professionals in the post-covid scenario which has seen technology adoption in library and information services. This study investigates EI among librarians in India by employing the ability model, and administering SSEIT as a research tool. The present study revealed that, in general, the respondents perceive themselves as more or less capable of dealing with situations with EI. However, analysis indicates that respondents differed in perceiving the difficulty and their ability level to tackle a workplace situation with emotional abilities. Data analysis also revealed that respondents with different education level differed significantly in their overall EI scores.
Predatory or deceptive publishing is still a persistent issue in scholarly communication. A large number of predatory journals are being published, and it is essential to keep them in check as the potential harm they could do to the scientific discourse is enormous. With the Open Science Framework (OSF) project titled "Decoding Predatory Publishing Practices for Academia (DePA)," the authors try to equip users to identify potential predatory journals and endorse ethical and quality publishing. The project will consist of training materials and a rubric developed to examine the quality of an open-access scientific journal by combining the publisher and individual journal aspects. The project includes a rubric consisting of different aspects regarding publication in scientific journals, quantifying the quality of the publishing practices adopted by these journals. Predatory or deceptive publishing is still a persistent issue in scholarly communication. For instance, deceptive publishers could hold the unpublished manuscript indefinitely, and little can be done if the author has signed a copyright transfer agreement. We can reduce the impact of predatory publishers by aiding the scholar community with simple and easy-to-understand devices that help them analyse the journals and publishers themselves. This could be part of the orientation at a researcher’s, library’s, or mentor’s level.
The purpose of this paper is to highlight the importance of topic modelling in conducting literature reviews using the opensource LDAShiny package in the R environment, with green libraries literature as a case study. To conduct the analysis, a title and abstract dataset were prepared using the Scopus database and imported into the LDAShiny package for further analysis. It was found that the green libraries' literature ranged from 1989-2023, with a sharp increase in research topics since 2003. The study also identified key themes and documents associated with green libraries research, revealing that energy efficiency, waste reduction and recycling, and the use of sustainable materials have been extensively discussed in the literature. However, further research is needed on the implementation of these practices in libraries, as well as the impact of the COVID-19 pandemic on green libraries. The findings will be beneficial to researchers interested in using topic modelling for literature reviews.
