Newly developed mathematical techniques reveal important tools for data mining analysis.
Data Analytics and Management
Data Analytics and Management is the branch of computer science that is concerned with extracting usable information from data. At LLNL, we’re working with data in many forms: text, images, videos, semantic graphs, and more. This data may be “at rest” in files or databases, or “in motion” as it streams in from sensors or other live sources. Our informatics research aims to gain insight from data that is very large, geographically distributed, complex, fast moving, or some combination of these characteristics. Applications for this work span a wide range of LLNL missions, including energy security and efficiency, biosecurity, computer security, and climate change. View content related to Data Analytics and Management.
Two currents in computation, machine learning and data analytics, popularly called “big data,” are poised to transform simulation-based science.
StarSapphire is a collection of scientific data mining projects focusing on the analysis of data from scientific simulations, observations, and experiments.
LLNL’s Celeste Matarazzo talks about the need for diversity in cyber defense.
The Earth System Grid Federation is a web-based tool set that powers most global climate change research.
New platforms are improving big data computing on Livermore’s high performance computers.
LLNL and University of Utah researchers have developed an advanced, intuitive method for analyzing and visualizing complex data sets.
More than 60 LLNL staff members are contributing to the intellectual vitality and smooth operations of the 2015 International Conference for High Performance Computing, Networking, Storage, and Analysis.
This year, Computation’s Institute for Scientific Computing Research welcomed 164 summer scholars from 97 universities in 9 countries—the largest group yet.