The proposed Enterprise Storage Solution (ESS), comprising of a Hewlett Packard Enterprise Virtual Array with EFS Clustered Gateway and EML Tape Library, will allow the Iowa Neuroimaging Center (INC) to provide high quality, high performance data management and storage for a large number of projects. It is difficult to assess the storage requirements for the data collection and analysis necessary to perform the science of neuroimaging. When the institutional guidelines and conformance requirements of that scientific data are considered, the task becomes even more daunting. The ESS will enable the INC to globally manage data, ensure scientific research continuance, satisfy regulatory and compliance standards, and improve resource utilization. The ESS will minimize total cost of ownership and reduce management complexity by addressing all aspects of INC storage needs in single unified system. The Iowa Neuroimaging Center (INC) realizes that providing low cost and reliable storage services are imperative to ensure continued success in the pioneering research that is performed at The University of Iowa. To maximize the scientific impact of each collected data set the INC adheres to stringent data-sharing standards and provides a long-term data retention model for the aggregation and preservation of knowledge resources. The ability to rely on the proposed ESS and the associated competitive storage costs will allow submission of strong proposals for gaining continued financial support through intramural and extramural funding. The neuroimaging community at The University of Iowa has a long history of producing exceptional science. The INC recognizes that collaborations between a diverse group of investigators, reflecting a variety of academic backgrounds and skills, will be more competitive and better equipped to succeed. The ESS is necessary for supporting multi-site studies that generate very large amounts of data due to their collaborative nature. The ability to share and combine data from multiple research institutions is critical to uncovering the separable endophenotypes that contribute to the heterogeneity of many disorders studied by INC investigators. Relevance The funded projects that will benefit from the IRB imaging data repository explore the neural basis of schizophrenia, affective disorder, addiction, and other disorders that have a high incidence, and that pose a huge public health cost burden. The proposed repository is extremely cost effective in that it will make existing data analyses much more efficient, and will also permit the development of new, novel analysis strategies that could significantly advance the development of new diagnostic and treatment approaches. ? ? ?
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