Scope and Topics

I. Data Science

    Foundational Theories of Data Science
    Data Classification and Taxonomy
    Data Metrics and Metrology
    Data Analytics
    Complex Network Analysis and Mining
    Security, Privacy and Trust in Data

II. Data Processing Technology

    Data Representation and Processing
    Machine Learning and Deep Learning
    Graph Neural Networks
    Semi-supervised and Unsupervised Learning
    Statistical, Mathematical and Probabilistic Modeling and Theories
    Information visualization
    Data Visualization

III. Data Systems

    Storage and File Systems
    High Performance Access Toolkits
    Compiler and Runtime Support
    Real-time Data Intensive Systems
    Multi/Many-Core Platforms
    Big Data and Cloud Computing

IV. Data Applications

    Business and Finance Applications
    Industrial Data Applications
    Bioinformatics Applications
    Healthcare and Medical Services
    Applications in Soil and Water
    HPC Systems for Data Applications
    Future Data Applications