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The Lariat Networking Project Building connections in the rural West Gwen Jacobs Montana State University APAN Cairns, AU Julya 6,2004
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IDeANet: leveling the playing field for “have-not” states NIH/NCRR supported program to upgrade networking capabilities in 23 “have-not” states in the US Part of the NIH IDeA Program –Includes BRIN, COBRE, INBRE –Similar to NSF EPSCoR program Build networks: personal and physical Lariat is the first piece: 6 institutions in rural states –University of Alaska, Fairbanks –University of Idaho –University of Hawaii –Montana State University –University of Nevada -Reno –University of Wyoming
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Participants Montana State U. and University of Washington –Gwen Jacobs, Montana State University –Ron Johnson, Vice-Provost, Computing and Communications and Vice-President, UW –Jacqueline Brown and Louis Fox, University of Washington Pacific Northwest Gigapop, CENIC, Front Range Gigapop BRIN (INBRE)/COBRE faculty in all six states BRIN Universities/Tribal colleges/ four year schools
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Goals of the Lariat Network Build two networks: –Upgrade internet connectivity in 6 rural states –Enhance and enable scientists and educators within the BRIN/INBRE network Provide training and expertise Provide access to research resources Strengthen partnerships with other institutions Support the goals of IDeA, BRIN, INBRE and WWAMI
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L A R I A T ’ S C H A L L A N G I N G G E O G R A P H Y & E C O N O M Y
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U. Idaho U. Wyoming PNWGP U. Nevada Reno Montana State U CENIC FRGP U. Hawaii U. Alaska Lariat will improve connectivity to research and education networks
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Improved connectivity will enable participation in national initiatives
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E-science for the individual scientist Remote access to research resources –Microscopes, telescopes, synchrotons –Data repositories, databases, storage Group collaboration tools –Real time videoconferencing –Real time collaborative experiments Biomedical research –Genomics, proteomics, physiomics –Neuroscience, bioengineering, bioinformatics –Information science/resources –Public health/environmental epidemiology
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Modeling structure function relationships in the nervous system
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Development of modeling tools We have developed a software package (XModeL) for representing and evaluating complex hybrid models. Key features: Describe and store models, data, and experiment protocols in portable XML GUI design, editing, and visualization tools Import/export data in many formats Numerical simulation using Matlab, Python, and Neuron. Easy modular expansion of numerical tools. Analysis, optimization, and parameter search tools. Distributed computation Data from Graham Cummins
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Access to remote resources
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Predicting spatial distribution of synaptic inputs: simulations done remotely at NASA Ames
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E-science collaborations
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BIRN: An example of biomedical e-science
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Research in extreme environments:
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Regional public health issues
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Unique to Montana
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Information dissemination: lariat-west.org
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