"CIRDC Research Data Mining Challenge: Exploring IEEE Xplore Scholarly Metadata"

"This competition invites participants to explore and analyze large-scale scholarly metadata using the CIRDC (Comprehensive IEEE Research Data Collections) dataset, available via IEEE DataPort. CIRDC provides structured metadata for IEEE Xplore publications, including information such as article titles, DOIs, authors, publication venues, publication dates, article numbers, and content types, offering a comprehensive view of the evolution of engineering and technology research.The goal of this challenge is to encourage the development of scalable data mining, machine learning, and analytical methods for understanding patterns in scientific publishing at scale. Participants may investigate research trends over time, model author collaboration networks, identify emerging or declining topics, or design recommendation and retrieval systems for scholarly content. The dataset also enables exploration of bibliometric indicators, citation-independent impact proxies, venue-level analysis, and metadata-driven knowledge discovery.By participating, researchers and practitioners can contribute novel methodologies for large-scale analysis of scholarly data and demonstrate how metadata can be leveraged to enhance academic discovery, improve information retrieval systems, and support science-of-science research. The competition also aims to promote reproducibility, transparency, and open research practices within the broader data science and academic communities."