Scientific Data Division
The Scientific Data Division (SciData) transforms data-driven discovery and understanding through the development and application of novel data science methods, technologies, and infrastructures with scientific partners.
The Machine Learning & Analytics Group conceives, designs, and implements new methods in high-performance machine learning, data and image analytics, computational geometry and topology, and visualization technologies. Our work involves a mix of theoretical research and applied research. The group works in close collaboration with scientific partners to identify and address challenging, large-scale, data-rich problems emerging from simulations, experiments, and observations. Read More »
The Usable Data Systems (UDS) group* performs research and development on software and methodology for improving the usability, quality, and security of scientific computing. The group is a mix of software engineers and computer scientists. We work with earth scientists, material scientists, chemists, process engineers, and physicists, as well as the NERSC and ESNet facilities. Read More »
The Scientific Data Management (SDM) group enables and accelerates scientific discoveries through effective data management and analysis tools and libraries. The SDM group’s research and development efforts focus on (1) scalable storage and I/O strategies, (2) autonomous data management infrastructure, (3) data life-cycle management, and (4) workflow optimization and automation. Read More »
The Integrated Data Systems (IDS) group is focused on data integration and frameworks for computational and data analysis systems. We are involved in several important areas of data science including usable scientific workflow tools and data pipelines; intuitive interfaces and web science gateways to explore, analyze, process data and run computations on HPC and distributed systems; and data integration, standardization and curation, with an emphasis on Findable, Accessible, Interoperable, and Reusable (FAIR) data. Read More »
By constantly improving the practices and knowledge around sustainable software, the Sustainable Software Engineering Group aims to create a broad and supportive community of researchers and engineers performing state-of-the-art software development for all aspects of publicly funded science. Read More »
The Computational Biology Group is a collaboration between Berkeley Lab's Computational Research Division and the Biosciences Area. Our goals are to develop tools and frameworks to meet the analysis challenges posed by present and future biological research that addresses our nation's energy and health needs. Read More »