This research develops a framework and wireframes for an AI-driven personalization and recommendation system designed to enhance Library Management Systems (LMS). AI adapts library services dynamically to individual user characteristics and behaviors, such as reading preferences and interaction patterns, using predictive algorithms and behavioral analysis to deliver tailored recommendations. The study is primarily grounded in a User-Centered Design Thinking approach to ensure the system is intuitive, responsive, and meets diverse user needs. The proposed framework emphasizes seamless data integration and adaptive interface design. Prototypes created using Figma reflect intuitive, inclusive, and accessible features aligned with user needs. The prototype was evaluated in a controlled environment with high-frequency LMS users using the System Usability Scale (SUS) to assess usability and user satisfaction, achieving a score indicating excellent usability. Although the AI processing engine remains conceptual, this research provides a structured foundation for the future implementation of AI-driven recommendation systems in LMS, supporting enhanced user engagement and improved Selective Dissemination of Information through personalized and inclusive library experiences.
This study presents a simple AI-Powered Workflow designed to enhance the dissemination of information contained in newspaper archives, without the need to redevelop existing infrastructures or create new tools. By combining advanced multilingual Optical Character Recognition (OCR) systems, like Google Cloud Vision, Large Language Models (LLMs), and vector-based semantic retrieval, the workflow enables automatic text restructuring, summarization, thematic tagging, translation, and multilingual semantic search. Furthermore, it enhances academic communication by allowing researchers and scholars to quickly and accurately access sources of high cultural and historical value, significantly improving accessibility, usability, dissemination of knowledge and the promotion of scientific collaboration.
PeruCRIS, the national Current Research Information System (CRIS) of Peru, represents a significant step toward consolidating scientific information management and enhancing research visibility across the country. In South American countries that have implemented open access legislation and institutional repositories, the development of integrated research information systems remains limited. This study offers a first comprehensive overview of PeruCRIS implementation status, focusing on its technical architecture, institutional adoption, and interoperability mechanisms. The study reports that 120 institutions are currently sending data to the national CRIS, either through manual uploads or via interoperability mechanisms. A sample of 60 CRIS/RIM cases were examined from May 2019 to December 2025, exploring the interaction between national and institutional CRIS platforms, addressing the practical challenges in aligning them. Findings reveal disparities in adoption levels, reliance on proprietary technologies, and limited interoperability coverage. The study also highlights the critical role of research managers and information professionals in sustaining CRIS systems. Finally, it outlines lessons learned and provides recommendations for similar national initiatives in developing countries.
This study aims to identify the factors influencing undergraduate and postgraduate students' satisfaction with academic library information services in China, and to examine how anthropomorphic features in AI-enabled virtual service agents (VSAs), drawing on anthropomorphism theory and social information processing theory, enhance their user experience. Based on social information processing and anthropomorphism theories, this study adopts a mixed-methods approach combining virtual scenario experiments and questionnaire surveys. Virtual scenario experiments were conducted to manipulate visual and verbal anthropomorphism in AI-enabled library service agents, and a survey was administered to undergraduate and postgraduate students at Wuhan University using a snowball sampling method, yielding 307 valid responses. Structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were employed to examine how visual and verbal anthropomorphism influence users' psychological distance and, consequently, their satisfaction with digital library services. The results show that perceived familiarity, perceived relevance, and perceived interactivity positively affect psychological distance. Psychological distance positively affects enjoyment, trust, and perceived usefulness. Trust positively affects both affective and cognitive satisfaction; enjoyment positively affects affective satisfaction and perceived usefulness positively affects cognitive satisfaction. Furthermore, prior knowledge has a moderating influence. The fsQCA results highlight that perceived relevance, perceived interactivity, and perceived usefulness are the three fundamental antecedents of user satisfaction. This research demonstrates that anthropomorphic features in academic library digital interfaces can enhance user satisfaction by reducing psychological distance. It also highlights the distinct psychological and behavioral responses of undergraduate versus postgraduate students, providing actionable insights for designing more engaging and effective library services.
Several major academic publishers, like Taylor & Francis, have reverted to the publication of special issues as a way to diversify their publication portfolios while maximizing the use of guest editors to attract more authors to their journals. This strategy is often achieved through calls for papers (CFPs). In parallel, academic publishing is witnessing an increase in artificial intelligence (AI)-related and AI-assisted literature. In this study, our objective was to assess CFPs across the Taylor & Francis journal portfolio to understand the volume of CFPs related to special issues on AI. From 982 CFPs related to special issues, 242 (24.6%) included one or more AI-related terms in the title or body text and were identified as AI-related, with the highest prevalence in the fields of Computer Science (80.0%) and Information Science (62.5%). A text-mining analysis of 90 CFPs explicitly focused on AI revealed field-specific thematic orientations. For example, in the field of Engineering and Applied Sciences, the Taylor & Francis special issues focused on automation, intelligent systems, and logistics. There is little research dedicated exclusively to CFPs, which offer a unique insight into the publishing business model that focuses on special issues.
This article reports on usability testing for an updated view of the Primo VE interface, following an initial round of testing on the existing public interface. Round 2 followed the same testing protocols of task completion while under observation by the researchers and recorded in Zoom. The results showed improvements in task success rate and time on task; the frequency and severity of issues decreased. However, some issues persisted, and new, minor problems were identified. The findings reiterate the conclusion of round 1: that while tweaking the user interface of Primo VE can improve the patron experience, direct instruction from a knowledgeable librarian is still necessary for completion of more complex tasks.
This article examines how countries move beyond the traditional model of publishing open government data by integrating AI-driven surveys, blockchain-based verification and participatory feedback forums to co-create higher-quality, more trustworthy datasets. In this regard, the study analyzes user feedback mechanisms across various national open data platforms and particularly investigates three specialized e-participation initiatives: the U.S. Challenge.gov crowdsourcing ecosystem, Sweden's NOSAD open data and open-source collaboration network, and Vienna's blockchain-driven data verification system. The cross-national content analysis identifies a diverse set of mechanisms, including interactive forms, social media integration, dataset request systems, metadata automation and community discussion boards that e-government platforms increasingly deploy to enhance data quality, usability and civic participation. Findings show that context-aware feedback, AI-tailored user interactions and decentralized metadata verification significantly strengthen transparency, trust and citizen engagement. The case studies further illustrate how incentives, collaborative resource exchange and distributed ledger technologies shape new models of participatory data governance. The article concludes by proposing a conceptual framework for evolving OGD portals into citizen-centric, innovation-driven ecosystems and offers policy recommendations to support more responsive, secure and collaborative open data infrastructures.
The integration and usage of Artificial Intelligence (AI) tools in academic research writing has ushered in a paradigm shift, fundamentally transforming traditional research methods. AI tools have reshaped scholarly writing by enhancing accuracy, efficiency, and productivity. This study investigated the level of awareness, adoption, challenges, perceived benefits, and effectiveness of AI tools among research scholars from India and the United Arab Emirates (UAE), via a structured questionnaire administered to 174 research scholars across various academic disciplines in leading universities. The study identified various generative AI platforms used by scholars and explored key metrics, such as brainstorming, generation of ideas, grammar and style checking, literature discovery, paraphrasing, citation management, and plagiarism detection. The findings revealed a strong positive response related to awareness and adoption rates as well as significant differences based on geographic location, gender, academic discipline, and years of research experience. Despite acknowledging the perceived benefits and effectiveness of AI tools, concerns and challenges related to ethical usage, accuracy and bias, academic integrity, overdependence, and technical difficulties exist. The study provides various recommendations for AI use in academic writing, including the need for AI literacy training, institutional support, and policies related to ethical standards, and offers important implications for academic institutions, AI tools developers, research supervisors, and policy makers, fostering the effective integration of AI in academic research practices, following an ethical framework.
Publication scams have plagued academia for decades, with fraudulent journals impersonating legitimate ones to deceive authors. Compounding the issue are journal policy changes driven by editorial misjudgment or the acquisition of journals by profit-oriented publishers, leading to their removal from the Scopus database. This article focuses on the troubling trend of academic publications with an apparent mismatch between article content and specialized journal titles. Despite these discrepancies, the alarming number of publications in both discontinued and hijacked journals continues to rise. It is logical to explore whether authors who ignore titles and scopes may not be mere victims of these scams but also, potentially, in some cases, willing participants seeking to exploit the system.
Artificial intelligence (AI) is increasingly embedded in library systems, creating a pressing need for AI-literate Library and Information Science (LIS) professionals. This study explores the state of AI literacy through a cross-sectional survey of 317 LIS professionals across six countries in South Asia and the Middle East. The analysis examines three domains of competence: cognitive understanding, behavioral application and normative awareness. Results reveal relatively strong conceptual knowledge, moderate ethical awareness and comparatively limited practical integration of AI into professional practice. While gender and national differences were not statistically significant, notable variations emerged by age, educational background and library type, highlighting how demographic and institutional factors shape readiness for AI adoption. To interpret the findings and propose pathways for development, the study employs the Human-centered AI Literacy (HcAiL) Framework, which encompasses four interrelated dimensions: Foundational (cognitive), Operational (behavioral), Critical (normative) and Transformational (transformative) aspects of AI literacy. The research advances the discourse on digital transformation in librarianship and offers practical insights for curriculum reform, professional development and institutional policy, particularly in regions underrepresented in global debates on AI adoption.
The proliferation of journals across disciplines presents a significant challenge for researchers in selecting appropriate venues for manuscript submission. In response, various scholarly publishers have developed web-based journal recommendation tools to assist authors in identifying suitable target journals. This study evaluates ten such tools using a comprehensive, three-tiered framework comprising 133 user interface features across the query interface, recommendation page, and venue details page. Multiple Correspondence Analysis was employed to cluster tools based on shared features. The findings reveal that tools such as Journal Guide, Elsevier Journal Finder, and Edanz Journal Selector offer a relatively broader range of features, while JANE exhibits distinct characteristics. These tools provide overlapping as well as unique functionalities, offering researchers diverse options for journal selection. A comparative table is presented to aid research support librarians in guiding authors based on specific needs. The study has practical implications for developers, publishers, and research support librarians, who play a vital role in guiding researchers through the publication process. By understanding the capabilities of these tools, librarians can effectively incorporate them into library instruction, consultations, and research support services. This research contributes to the scholarly communication literature and underscores the value of collaboration between libraries, developers, and publishers.
