SCOPUS occupies a central role in the global ecosystem of academic publication. It is a key component of a proprietary information system which has been developed by Elsevier BV for the provision of bibliometric information on the performance of authors, journals, books, publishers, faculties and institutions to Universities, Corporations and Governments around the world. It functions in respectful competition with the Web of Science, which is owned by Clarivate Analytics. The Scopus Content Selection Advisory Board (CSAB) of independent members has a significant advisory role in quality assurance and policy development around the SCOPUS system, and in debating future technical developments. In this series of essays on the Art and Science of Academic Journal Editing and Publishing, I am seeking to create a durable record of the events and discussions of the SCOPUS CSAB from my own records, research, and perspectives as an active member of the Board since 2009, for future reference and for the further education of publishing professionals. In previous essays in this series, I have described the creation and early years of SCOPUS and the SCOPUS Title Evaluation Process (STEP) from 2003; the creation of the current SCOPUS Content Selection Advisory Board (CSAB) in 2009; and the evolution of policy for SCOPUS, STEP and the CSAB through 2010-2011; 2012-2016; 2017-2019; and 2020-2021. I have also separately described the technical evolution of SCOPUS itself, and of the Title Evaluation Platform. In this essay, I describe the policy work of the Board over the period 2022 to 2024. This saw the continued expansion and diversification of SCOPUS content and collaborations with national research collections using the new Research Data Platform. The global arrival of Generative AI in late 2022 prompted the introduction and development of SCOPUS AI. I also discuss the maturation of organisational and technical systems to counter the global explosion of sophisticated publication fraud; the further development of SCOPUS Radar; the retraction of articles; the challenges of identical and near-identical journal titles; and the challenges of evaluating faith-based journals.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026