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Distributed Big Data & Analytics University of Cincinnati –Bioinformatics

•Project/Research Title: NIH BD2K-LINCS Perturbation Data Coordination and Integration Center

•Industry Sector: Health care / Environmental Health/ Biomedical Research

•Science Sub-domain: Bioinformatics and Data Science

•Short Description of Project & Relation to Big Data: The Library of Integrated Network Based Cellular Signatures (LINCS) project is expected to produce masses of data collected from human cells and tissues perturbed with drugs and other molecules. The center’s role is to develop new methods to integrate big data, come up with intelligent ways to mine and analyze it, intuitive tools to interact with it and to educate the research community on how to best leverage this trove of information for biomedical research.

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

•Big Data Attributes: In biomedical research, these data sources include the diverse, complex, disorganized, massive, and multimodal data being generated by researchers, hospitals, and mobile devices around the world.

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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 _____