Data Science is an interdisciplinary field that is concerned with systems, storage, software, algorithms, and applications for extracting knowledge or insights from data. Data-driven research is also commonplace in many fields of sciences and engineering, where direct observations (astronomy), instrumentation (sensors, DNA sequencers, electron microscopes), or simulations, (molecular dynamics trajectories), generate datasets that must be analyzed with domain-specific knowledge. Recently, our ability to collect and store massive datasets that are typically characterized by high volume, velocity, or variety, and inadequacy of current techniques to handle such large data sizes, led to the coining of the term “Big Data.”
IDEAS Research Areas
Underpins the transformation of data to knowledge to actionable insights. Research in unstructured and dynamic data, deep learning, data mining, and interactive machine learning advances foundations and big data applications in many domains.
High Performance Computing
Critical technology for big data analysis. High performance systems, middleware, algorithms, applications, software, and frameworks support data-driven computing at all levels.
Algorithms and Optimization
Algorithms, optimization, and statistics are laying the foundations for large-scale data analysis. Streaming and sublinear algorithms, sampling and sketching techniques, high-dimensional analysis are enabling big data analytics.
Health and Life Sciences
Big data sets abound in genomics, systems biology, and proteomics. Advances in electronic medical records, computational phenotyping, personalized genomics, and precision medicine are driving predictive, preventive, and personalized healthcare.
Materials and Manufacturing
Large-scale data sets providing a microscopic view of materials, and scalable modeling and simulation technologies, are paving the way for accelerated development of new materials.
Advances in sensors and the Internet of Things enable energy infrastructure monitoring. Data analytics brings unparalleled efficiencies to energy production, transmission, distribution, and utilization.
Achieving efficient use of resources and services, safety, affordability, and a higher quality of life using data-based research. Internet of Things research uses big data and analytics from massive streams of real-time data and applies it to smart city initiatives.