The main aim of the study is to investigate content creation and academic writing with Generative Artificial Intelligence (GenAI). Also, the study is focused to explore the benefits and challenges that might occur while using AI to write academic content that must align with existing legal and ethical principles and guidelines provided by global organisations. The paper is conceptual and analytical that investigated ethical principles, offered guidelines and real-world problems that occur while using AI to create content. It involved detailed literature review of existing research work and available guidelines associated with ethical and responsible use of AI, performed to know about possible concerns related to the use of GenAI in writing and best ways to incorporate it in the work. The study revealed key concerns including inaccuracy, misleading information, unintentional biases, privacy, transparency, IPR compliance, fairness and others. It was noted that if the information has poor quality, false citations, hallucinated and biased data, all these carry a reader to lack of trust and authenticity issues. Apart from all the challenges and problems, the need to have human oversight was emphasized to maintain the accuracy and relevance of the content.
In today's world, adopting advanced research utility tools (ARUTs) for information access are essential for every research scholar to maximize digital innovation in their research work and academic field or other research domains. Now a day's researchers are recognized the power of these research utility tools in maximizing their capabilities and effectively addressing complex issues. This study explores various research utility tools, focusing on their practical applications and research scholars' perceptions of these tools, ultimately leading to the development of even more effective research tools for their benefit. This study investigated among research scholars from seven well-known Central Universities of North India who have vast experience in research utility tools. The researchers shared a structured questionnaire administrated via an online survey link on WhatsApp and email to collect data from 210 research scholars from January 15, 2026 to January 30, 2026. The descriptive statistical analysis showed a strong correlation between performance expectancy and behavioral intention (r = 0.71, p < .01), as similar facilitating conditions (r = 0.67, p < .01), effort expectancy (r = 0.64, p < .01), and social influence (r = 0.52, p < .01). These results clearly demonstrate that perceived usefulness, ease of use, social influence, and institutional support play a significant role in adoption of research utility tools in universities. The results of multiple regression analysis confirmed that performance expectancy (beta = 0.45, p < .001) is the strongest predictor of behavioral intention to use research utility tools. Accordingly, effort expectancy (beta = 0.29, p < .001), facilitating conditions (beta = 0.26, p < .001), social influence (beta = 0.21, p < .001) and this model explains (68%) of the variance in behavioral intentions (R & sup2; = 0.68), indicating the model's high explanatory power (F = 108.72, p < .001).
Environmental research plays a central role in addressing global challenges such as climate change, pollution and ecosystem degradation. However, the visibility and interoperability of scientific publications from the Global South, particularly Morocco, remain limited due to absence of dedicated dispositive and open repositories, along with the insufficient adoption of international standards. This study applies Semantic Web and Linked Data technologies to improve the discoverability and reuse of Moroccan environmental publications. A methodological framework was developed combining a literature review, a comparative study of semantic web tools (Prot & eacute;g & eacute;, VocBench, RDFlib, RMLMapper, Open Refine, Apache Jena Fuseki, GraphDB and Virtuoso), and an experimental implementation on a corpus of 27 open access articles. The proof of concept generated an RDF knowledge graph comprising 1120 triples. This structure supported advanced SPARQL queries and demonstrated improvements in resource discoverability, semantic interconnection and metadata enrichment. The corpus analysis showed complete metadata coverage, with all records including DOIs, publication years and institutional affiliations. It revealed a sparse but structured graph (density= 0.007), where research outputs were largely oriented toward climate change (85%) and water-related topics (52%). The results highlight the feasibility of lightweight, open-source solutions as the proof of concept was achieved with modest resources and standard open-source tools, yet still delivered metadata enrichment and advanced querying. The findings also emphasize the strategic importance of developing national ontologies, dedicated triple stores, and infrastructures aligned with FAIR principles. This approach provides a transferable model for Southern countries aiming to improve the international visibility of their scientific production.
Academic libraries are at the centre of the academic excellent of higher institutions providing relevant information services and resources required for teaching, learning and research functions. This paper discusses the critical role of academic libraries in supporting the United Nations sustainable development goals (SDGs) in Nigerian. The results demonstrate that academic libraries are key drivers of sustainable development due to their ability to provide fair access to information that facilitates education, reduction of poverty, health, and gender equality. The research notes that academic librarians have a positive overall awareness and knowledge regarding the SDGs, especially the ability to align academic library services with the goals such as quality education (SDG 4), poverty eradication (SDG 1), good health and well-being (SDG 3), and gender equality (SDG 5). Nevertheless, the results also indicate low profile of the contribution of academic libraries in certain aspects like collaboration, social media lobbying, and direct interactions with the social issues. The key challenges that have been identified are lack of funding, inadequate ICT infrastructure, institutional policies connecting libraries to the SDGs, weak university engagements, and low collaborations with national and international stakeholders. The study suggests that more funding by the government and institutions, policy changes and building capacity will help to improve the strategic functions of academic libraries that will enable the academic libraries in Nigeria to be better players in facilitating inclusive and sustainable development.
This research examines structural relationship between information filtering, information overload and user satisfaction in the context of digital library environments. Even though information filtering typically assumed to decrease cognitive burden, very little empirical evidence explained how information filtering mechanisms affects evaluative cognition and satisfaction in information intensive academic systems. The survey data was analysed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach, with 390 active digital library users' respondents. The results show that information filtering has a positive and significant effect on perceived information overload (beta = 0.236, p < 0.001), suggesting that access to information resources that are rich with information relevance can increase evaluative cognitive demands in digital information interaction. Significantly also, Perceived information overload was related to user satisfaction (beta = 0.158, p = 0.003), indicating that as perceived information overload increases, user satisfaction with digital library use might also increase. It is a constructive evaluative state resulting from environments in which people retrieve information that are relevance-intensive and not just a negative cognitive state, which is what people have been thinking of perceived information overload up until now. Besides, mediation analysis which shows that perceived information overload completely mediated the relationship between information filtering and user satisfaction, and the direct relationship between information filtering and user satisfaction was not statistically valid (beta=0.091, p>0.05). The findings have implications for digital library scholarship, showing how evaluative cognitive engagement can be an important explanatory mechanism of the linkage between information filtering processes and user satisfaction in today's digital knowledge environments.
