Big Data and Cognitive Computing: Five New Journal Sections Established

The journal Big Data and Cognitive Computing (BDCC) is a scholarly online journal which provides a platform for big data theories with emerging technologies on smart clouds and exploring supercomputers with new cognitive applications. We are delighted to announce the launch of five new Sections in this journal, each dedicated to advancing specific frontiers within our interdisciplinary field. These Sections reflect the rapid evolution and deepening specialization of research in data-driven and cognitive technologies, and are designed to provide focused platforms for scholars, practitioners, and innovators to share cutting-edge work.

The new Sections are as follows:

• Big Data;
• Cognitive Systems;
• Artificial Intelligence and Multi-Agent Systems;
• Data Mining and Machine Learning;
• Large Language Models and Embodied Intelligence.

Each Section has been designed with a clear purpose, to support high-quality research and promote discussion across connected fields. Below, we provide a brief overview of their thematic focus.

Big Data: The Big Data Section is dedicated to the foundational architectures, systems, and methodologies that enable the acquisition, storage, management, and processing of massive-scale datasets. This Section aims at publishing research that addresses the significant challenges of volume, velocity, variety, and veracity in the big data lifecycle.

Cognitive Systems: The Cognitive Systems Section focuses on the design and development of computational systems that emulate high-level human cognitive functions. The aim is to advance machines beyond mere data processing towards capabilities such as reasoning, problem-solving, perception, and semantic understanding. This Section explores the intersection of computer science, psychology, and cognitive science to create systems that can interact with their environment and users in an intelligent, adaptive, and context-aware manner. It serves as a platform for research that bridges cognitive informatics with practical computational models.

Artificial Intelligence and Multi-Agent Systems: The Artificial Intelligence and Multi-Agent Systems Section is dedicated to the core algorithms, theories, and formalisms that constitute the field of AI. This Section aims at publishing fundamental research on creating agents, including the Agentic frameworks, that can perceive their environment and take actions to achieve specific goals. It covers a broad spectrum from symbolic AI and knowledge-based systems to modern probabilistic and bio-inspired algorithms. The focus is on the theoretical underpinnings, algorithmic innovations, and the application of these core AI techniques to solve complex, structured problems across various domains.

Data Mining and Machine Learning: This Section focuses on the algorithms and techniques for discovering patterns, extracting knowledge, and building predictive models from data. The aim is to showcase research that advances the state-of-the-art in learning from data, from both a theoretical and an applied perspective. The Section emphasizes the entire process, from data pre-processing and feature engineering to the application of sophisticated learning algorithms to uncover hidden insights and facilitate data-driven decision-making.

Large Language Models and Embodied Intelligence: This Section is dedicated to the frontier of AI research: the creation of large-scale, foundational models and their integration into physical or simulated worlds. The Section has two interconnected pillars. First, it focuses on the development, scaling, and societal impact of large models (e.g., for language, vision, and multimodal data). Second, it explores embodied intelligence—how these and other AI models can be deployed in robots, avatars, and digital twins to enable intelligent interaction with a dynamic human-centered environment.

These Sections are designed to help organize the growing range of work in our field and to encourage collaboration across disciplines. We welcome submissions that align with these themes and look forward to sharing research that advances the potential of data and intelligent technologies.