Application Area 7

Information and Data Science

Projects in this area focus on how to solve problems by studying the properties and behavior of information; organizing, sharing, and interpreting information; and processing information for optimum accessibility and usability. Projects may also include extracting knowledge and insights from data sets; developing data-driven solutions; and applying knowledge and actionable insights from data across a broad range of application domains. These include:

• Understanding and analytics of complex data, human, domain, network, organizational, social, behavioral, and system characteristics, complexities, and intelligences
• Creation and extraction, processing, representation and modeling, learning and discovery, fusion and integration, presentation and visualization of complex data, behavior, knowledge, and intelligence
• Data analytics, pattern recognition, knowledge discovery, machine learning, deep analytics and deep learning, and intelligent processing of various types of data (including transaction, text, image, video, graph, and network), behaviors, and systems
• Active, real-time, personalized, actionable, and automated analytics, learning, computation, optimization, presentation, and recommendation
• Big data architecture, infrastructure, computing, matching, indexing, query processing, mapping, search, retrieval, interoperability, exchange, and recommendation
• Distributed heterogeneous computing and algorithms, small data architecture
• In-memory, distributed, parallel, scalable, and high-performance computing, analytics, and optimization for big data
• Intelligent devices and services in scientific, business, governmental, cultural, behavioral, social and economic, health and medical, human, natural, and artificial (including online/web, cloud, IoT, mobile and social media) domains
• Ethics, quality, privacy, safety and security, trust, and risk of data science and analytics