TR&D Project 3: Standardized Execution Environments Abstract Our proposed BTRC resource, the Center for Reproducible Neuroimaging Computation (CRNC), seeks to implement a shift in the way neuroimaging research is performed and reported. Through the development and implementation of technology that supports a comprehensive set of data management, analysis and utilization frameworks in support of both basic research and clinical activities, our overarching goal is to improve the reproducibility of neuroimaging science and extend the value of our national investment in neuroimaging research. Reproducibility is critical because the current literature is fraught with published results that are due to mistakes (occasionally misconduct); or turn out to be false positive (contributed to by the lack of statistical power). More importantly, given the current publication system, it is exceedingly difficult to discern between false positive and true positive finding as data is hard to aggregate, and exact methods are hard to replicate. In this Technology Research and Development Project, TR&D 3: Execution Environments, we will establish the technology for development of execution options that facilitates operation in multiple computational environments and reduces barriers to scale and reliability. Centralized clearinghouses address only one necessary aspect of a sustainable software ecosystem: availability. Unfortunately, even given a detailed specification of provenance information, mere availability of software and data does not provide accessibility. Accessibility requires that software and tools are deployed in computing environments available to end users without technical system and software installation knowledge. This deployment needs to be well specified (e.g., exactly which tools are installed), automated (so it can be reconstructed later on), and controlled (e.g., the environment is tested). To accomplish this, we will develop NeuroImaging Computation Environments MANager (NICEMAN) which will provide: 1) computational platform with automatic version-based provisioning; 2) tools for turnkey execution of computational workflows; and 3) web service for instantiation of arbitrary computation environments locally or in the cloud through interactive web interface. We will work in partnership with the other TR&D projects, the Training and Dissemination Core and the Collaborator and Service Project users to deploy, test and validate the reproducible analysis system and to foster use of the reproducible framework in the neuroimaging research community.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Biotechnology Resource Grants (P41)
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Special Emphasis Panel (ZEB1)
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University of Massachusetts Medical School Worcester
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