Arnold: Topology and Big Data Making Shapes

IO Sense-Making
Stephen E. Arnold
Stephen E. Arnold

Topology and Big Data Making Shapes

The article titled Lawrence Livermore Explores the Shape of Data, Expanding Query-Free Analytics on GCN delves into the work of the Livermore National Laboratory in partnership with Ayasdi Inc. Using homegrown technology, the lab tackles big data to analyze various areas of research such as climate change, national security and biological defense. Recently their work has begun to incorporate topology, the study of shapes. The article explains the connection,

““The fundamental idea is that topological methods act as a geometric approach to pattern or shape recognition within data,” says a September 2013 article in the journal Science co-authored by Ayasdi CEO Gurjeet Singh. It allows “exploration of the data, without first having to formulate a query or hypothesis.” That is, researchers can find things they did not know they were looking for. For instance, in a database of billions upon billions of phone records scientists could make sense of who was talking to whom.”

Such complicated shapes are almost impossible for people living in 3D to even imagine. But the practical applications seem endless. Stanford University began the research that resulted in TDA in the 1970’s, and received $10 million from NSF and DARPA in 2003. Five years later Ayasdi was founded for commercial use of the TDA software, which is offered as a cloud-based service.

Chelsea Kerwin, February 05, 2014

Sponsored by ArnoldIT.com, developer of Augmentext

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