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Distributed Big Data & Analytics University of Cincinnati – High Energy Physics

•Project/Research Title: Large Hadron Collider (LHCb) experiment at CERN studying heavy flavor physics

•Industry Sector: Nuclear Physics, Energy

•Science Sub-domain: Physics

•Short Description of Project & Relation to Big Data: The physics focus is studying oscillations of matter into anti-matter and studying the differences in decays rates of matter and corresponding anti-matter to “mirror-image” final states. These address the nature of fundamental interactions between the basic constituents of matter. We move large data files from host laboratories to computers at UC for final analysis. For example, a single file with an LHCb NTUPLE from a small fraction of the data is 3GB. The size of the data set to be transferred for this analysis will be on the order of 1TB.

•Best Contact: Jane Combs, combsje@uc.edu

•Big Data Attributes: LHCb NTUPLE data sets

•Aggregate Data Size: Now __3TB___, 2016 __6TB___, 2017 __6___, 2020 _____

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Distributed Big Data & Analytics Project Template

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Distributed Big Data & Analytics Project Template

•Project/Research Title: Machine Tool Ball Screw Health Monitoring

•Industry Sector: Manufacturing / Industrial Machinery

•Science Sub-domain: Data Analysis / Prognostics & Health Management

•Short Description of Project & Relation to Big Data: The goal of this project is to conduct multiple run-to-failure tests using commercially available machine tool ball screws and motors to collect data and design a data driven model for health monitoring and prediction of such ball screws. Data from these tests is transferred and stored on a central server. A mobile app will be developed for monitoring these tests.

•Best Contact: Professor Jay Lee

•Big Data Attributes: Sensor, Near Real-time

•Aggregate Data Size: Now __5TB___, 2016 __15TB___, 2017 __30TB___, 2020 _____