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.

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.

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.

Green open access (OA) is a form of OA that allows authors to post an accepted or submitted version of their paper, either onto a personal or institutional repository, a preprint server, or onto an academic social networking site, such as ResearchGate, provided that established publishing embargoes are not violated. In the case of an OA paper, once the final version of that paper is published, this removes the need to have a green OA version because the paper is already OA. In such a case, green OA merely serves as an additional copy (and earlier version) of the published version, and in instances (such as preprints) where a digital object identifier (DOI) is assigned, in essence, that paper has two bibliometric copies, albeit of different versions. In this paper, a new version of green OA of an accepted paper, and to which a DOI is not assigned, coined as lettuce-green OA (LeGOA), and a novel form of a preprint, is proposed. LeGOA allows for the temporary exposure (typically weeks or months) of information to interested readers while the accepted paper is processed by the journal, but is removed when the final version is published, “senescing,” similar to the leaves of a lettuce. Four real-case studies, as test objects, using the author’s actual papers, were tested in the first few months of 2023, while an additional LeGOA entry was created at ResearchGate in October of 2024. Even though authors who create a LeGOA file for their accepted papers gain additional weeks or months of open exposure to the public, when the LeGOA file is deleted, “reads” are irretrievably lost. Using LeGOA, authors have an expanded form of showcasing their research findings prior to the publication of their accepted paper, expanding the knowledge stream earlier. LeGOA represents a shift in the culture of self-created, web-based librarianship.

The rapid advancement of generative artificial intelligence (AI) has transformed research and scholarly communication ecosystems. More and more instructors and researchers have started using generative AI chatbots to help with their academic teaching and research. Prompt engineering is the process of creating and refining inputs for generative AI chatbots to generate desired responses. Known for teaching users to refine academic database keyword searching and promoting critical thinking, academic librarians are well-positioned to use prompt engineering techniques to support academic research, teaching, and learning. This paper provides reviews about the implications and applications of prompt engineering for academic librarians and how they can use prompt engineering to support their work.

The Covid-19 pandemic profoundly affected the online presence of every institution as in-person interactions abruptly came to a halt. Libraries had to make both significant adjustments and minor tweaks to their websites to accommodate new remote work and scholarship modalities. In some cases, entire web pages, which would typically require weeks of planning, research, and testing before being launched, were hastily published. In this article, the author explores how web committees can make on-the-fly changes that continue to yield positive results beyond the unique circumstances of a once-in-a-lifetime pandemic. They argue that by encouraging the use of design thinking principles, administrators and web committees can effectively showcase remote library services to students, faculty, and staff.

This article explains how one academic library met greater demand than ever before by streamlining the room reservation process for both patrons and staff and implementing an events calendar and other tools to make library happenings more visible. Like many academic libraries, the College of Charleston’s main library, Addlestone Library, contains a mix of spaces used by students, faculty, and staff from across campus, and library faculty and staff. The library had used LibCal, the popular library room booking software from Springshare, to efficiently manage study rooms and other patron-forward library spaces since 2013. Spaces reserved primarily by library staffers were booked using legacy Outlook calendars, a system that had become increasingly difficult to manage. By thoughtfully reorganizing the library’s LibCal Spaces module, the library incorporated all reservable library spaces into a single platform and streamlined the room booking process for all users. The project reduced staff time spent managing room bookings and setups, made it easier for staff to find information about what is going on in the library, and facilitated the relaunch of an events calendar on the library website.

"Open Heritage Data: An Introduction to Research, Publishing and Programming with Open Data in the Heritage Sector." Journal of Web Librarianship, 17(3), pp. 73–74

"Student-created media: Designing research, learning, and skill-building experiences." Journal of Web Librarianship, ahead-of-print(ahead-of-print), pp. 1–2