As the fields of artificial intelligence and scientometrics converge, new methodologies and insights are emerging that can revolutionize how we analyze and evaluate scientific output.

We are pleased to announce a special topic dedicated to the theme "AI for Science of Science." We invite researchers, practitioners, and thought leaders to submit original research articles, case studies, and reviews that explore the following topics:

● Innovative AI techniques for measuring science impact

● Applications of AI in knowledge discovery, bibliomtric analysis, technology forecasting

● AI for enhancing research evaluation processes

● Ethical considerations and challenges in AI applications in scientometrics

● Datasets for evaluating the performance of AI tools in the context of Science of Science

Submission Instructions

Submissions should be made through our online platform https://mc03.manuscriptcentral.com/jdis by June 30, 2025. When submitting, please select the type “AI4SoS.” Once you submit, we will immediately start the peer review process, and if it passes review, we will immediately publish it online, without the need to wait for any issue publication deadlines. For more information, please contact us at jdis@mail.las.ac.cn.

Join us in exploring the transformative potential of AI in the field of scientometrics!

What are the top questions towards better science and innovation and the required data to answer these questions?

1. Which are the questions that need to be answered, to promote the development of science and technology? 

More specifically the journal welcomes:

* Perspectives on why these questions need to be answered

* Primary research on addressing these questions

* Reviews of a specific problem, the current status, and gaps in our knowledge

2. Which data are required to answer the above questions?

* Exploring the relationship between questions and data

* Providing and describing one or several datasets

* Comparing the quality of different data sources

* Presenting methods or tools that help to improve data quality

Guest Editors

* Yi Bu, Peking University

* Dongbo Shi, Shanghai Jiaotong University

* Zhesi Shen, National Science Library, CAS

* Ye Sun, University College London

* Yang Wang, Xi'an Jiaotong University

Research integrity and responsible research practices are increasingly being discussed by the academic community and the public. In recent years, a number of significant cases of academic misconduct have been reported worldwide. With the improvement in the availability of scientific papers and their related data, our understanding of academic misconduct is also improving. Nevertheless, we still notice a gap among policymakers, researchers, and societal participants on their understanding of academic misconduct and related policies and measures. To provide insights into research integrity and academic misconduct from multiple perspectives, this research topic aims to answer the question – what can policymakers, scientometricians, publishers, institutions and researchers do to counter academic misconduct?
In addition to organizing special paper solicitations, JDIS also facilitates broader exchanges among stakeholders on research integrity issues through symposiums.
Promoting Research Integrity-4th Data-Driven Knowledge Discovery Symposium successfully held.

Statistics have been widely used in bibliometric analyses. Yet, it is well-known that not all uses follow best practices, possibly resulting in invalid conclusions or irreproducibility. This Research Topic aims to provide insights into the proper use of statistics in bibliometrics.