Visual Analysis for CPS Data

Submission Deadline: 31 March 2020

IEEE Access invites manuscript submissions in the area of Visual Analysis for CPS Data.

Ubiquitous sensing technologies, social media and large-scale computing infrastructures have produced a variety of CPS (cyber-physical-social) data, e.g., Twitter/WeChat posts, human mobility, car trajectories, phone calls, WeChat connections, and geographical data. Analyzing CPS data can provide solutions for green, high-efficient and intelligent production and lifestyles. However, CPS data is usually massive, heterogeneous and distributed, and consequently cannot be analyzed effectively by analysts with traditional data processing techniques. The goal of Visual Analysis for CPS Data is to develop methods and tools that can help analysts understand and utilize CPS data to gain insight and make decisions in an interactive and iterative way. To facilitate management of CPS-relevant future applications, visual encodings, visual interfaces and visual interactions are essential components that integrate (or combine) human intelligence with machine intelligence.

The Special Section in IEEE Access on “Visual Analysis for CPS Data” of IEEE Access aims to address issues related to the representation, visual design, visual mapping, interaction, analysis and applications of multi-variate and time-varying data collected in a CPS system (e.g., smart city, MOOCs, smart factory, ITS). We solicit articles describing frameworks, theories, approaches, and techniques from visualization, visual data mining and visual analysis for designing, building and managing CPS systems.

The topics of interest include, but are not limited to:

• Visual representation, visual design, visual interaction, visual reasoning, visual decision-making for CPS data
• Visualization theories and visual analysis models for CPS systems and applications
• Novel visual data mining, visual machine learning pipelines for CPS data, and applications, surveys, and evaluation approaches of visual-assisted CPS systems
• Visualization and visual analysis theories for CPS data analysis
• Visual representations and interaction techniques for CPS data analysis
• Novel visual data mining and visual machine learning pipelines for CPS data analysis
• Visual-assisted CPS data management and knowledge representation
• Visual-supported modeling, planning and decision-making for CPS systems and applications
• Collections, benchmarking and evaluations for visual analysis of CPS data
• Surveys of visual-assisted CPS systems and application

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Shuiguang Deng, Zhejiang University, China

Guest Editors:

1. Wei Chen, Zhejiang University, China
2. Ye Zhao, the Kent State University, USA
3. Xinheng (Henry) Wang, University of West London, UK
4. Panpan Xu, Bosch Research North America, USA

Relevant IEEE Access Special Sections:

1. Applications of Big Data in Social Sciences
2. Advanced Software and Data Engineering for Secure Societies
3. AI-Driven Big Data Processing: Theory, Methodology, and Applications

IEEE Access Editor-in-Chief:  Derek Abbott, Professor, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: dengsg@zju.edu.cn.