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Lawrence Livermore Explores the Shape of Data, Expanding Query-Free Analytics

Lawrence Livermore National Laboratory is using topological data analysis research to explore new ways of obtaining useful information from extremely large, complex data sets. The lab is working with Stanford University spinoff Ayasdi, which is funded by the U.S. Defense Advanced Research Projects Agency and the National Science Foundation. Ayasdi’s Insight Discovery software handles big data problems by extracting information from very large data sets. The lab, which uses high-performance computing for modeling and simulation in energy, climate change, biological defense, and national security, has developed its own tools in the past but is now looking to commercial technologies, as big data gains momentum in the technology world. In particular, the lab believes its work could benefit from topological data analysis, which studies the shapes and meanings of vast, high-dimensional data sets. Topological methods focus geometrically on pattern and shape recognition within data, which enables scientists to make discoveries without specifically seeking them. The Insight Discovery software analyzes data to produce dimensional shapes and uses algorithms to extract relationships, without querying databases. The U.S. Department of Agriculture is using the software to study E. coli bacteria. One particular topological data analysis focus for the Lawrence Livermore lab will be bioinformatics.


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