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Study Features Global Impact of Journal of Big Data in First Decade

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A new study published in the (JBD) highlights the journal’s emergence as one of the world’s leading publications in data science and artificial intelligence research during its first decade – an ascent rooted in a transformative National Science Foundation investment at the College of Engineering and Computer Science at �鶹��Ʒ��Ƶ.

Between 2014 and 2017, FAU’s Data Mining and Machine Learning Laboratory secured a $600,000 NSF grant to work on big data. The project was led by Taghi M. Khoshgoftaar, Ph.D., Motorola Professor in FAU’s Department of Electrical Engineering and Computer Science and director of the Data Mining and Machine Learning Laboratory. A direct outcome of this work was the initiative to launch the JBD, co-edited by Khoshgoftaar and Borko Furht, Ph.D., professor in FAU’s Department of Electrical Engineering and Computer Science and director of the NSF Research Center for Advanced Knowledge Enablement (CAKE).

Since its founding in 2014, JBD has become one of the most influential publications in computer science. By 2024, the journal achieved a 98th-percentile Scopus CiteScore of 22.3 and amassed nearly 65,000 citations. It has published more than 1,000 articles spanning disciplines from computer science and engineering to medicine and social sciences.

The NSF-funded effort also catalyzed a prolific body of research from the Data Mining and Machine Learning Laboratory, producing more than 300 peer-reviewed papers, graduating 24 Ph.D. students, and generating more than 72,750 Google Scholar citations since 2014, and has authored four of JBD’s five most-cited articles. These include landmark surveys on image data augmentation, transfer learning, deep learning with class imbalance and big data analytics – each cited thousands of times and widely used across academia and industry.

“This study validates what we have long believed. The Journal of Big Data has become a central hub for high-impact research in data science and machine learning worldwide,” said Khoshgoftaar. “We are incredibly excited to see how the journal has shaped the field over the past decade and continues to drive innovation across disciplines.”

A bibliometric analysis examined more than 1,000 JBD publications indexed in Scopus and Web of Science from 2014 to 2024. Using advanced science-mapping techniques, researchers identified three dominant thematic pillars: big data infrastructure (including Hadoop and Apache Spark), machine and deep learning (such as neural networks), and applied domains like cybersecurity, health care analytics and sentiment analysis.

The study also highlights the journal’s global reach, with significant contributions from the United States, China, India and across Europe, as well as strong international collaboration networks. Its h-index of 91 reflects both sustained scholarly output and growing influence, particularly since 2019.

Importantly, the findings show that JBD serves not only as a repository of foundational research but also as a platform for emerging topics – from causal inference to advanced neural network applications – demonstrating its adaptability in a rapidly evolving field.

“The results of this study clearly demonstrate the journal’s relevance in shaping the future of big data and artificial intelligence,” said Furht. “It highlights how interdisciplinary collaboration and methodological innovation are driving solutions to real-world challenges, from cybersecurity to health care.”

Beyond its academic impact, the NSF grant and resulting research output have played a critical role in elevating FAU’s national research profile. The university is now recognized as an R1 institution, the highest classification for research activity, and ranks first in Florida for high-quality computer science research.

The study also provides practical insights for researchers, institutions and policymakers, identifying high-impact research clusters and collaboration opportunities across regions. It emphasizes the importance of scalable algorithms, applied machine learning, and interdisciplinary approaches in addressing complex global challenges.

“This work exemplifies the exceptional research being conducted within our College of Engineering and Computer Science,” said Stella Batalama, Ph.D., dean of the college. “The groundbreaking contributions from our faculty in machine learning and big data have not only advanced the scientific community but have also been instrumental in propelling �鶹��Ʒ��Ƶ to R1 status. As the Journal of Big Data enters its second decade, this study affirms its position as a cornerstone of the global data science ecosystem – driving innovation, fostering collaboration and shaping the future of artificial intelligence and analytics.”

Co-authors of the study are Mohammad Sadegh Khorshidi, Ph.D., a postdoctoral researcher; José M. Merigó, Ph.D., professor; and Ghassan Beydoun, Ph.D., professor, all with the University of Technology Sydney, Australia.

-FAU-

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