This project will enable the reproducible analysis and sharing of large human brain imaging datasets. Imaging the brain using magnetic resonance imaging (MRI) is an essential tool for the study of the human brain, but the processing of large neuroimaging datasets is often a difficult and time-consuming process. This project will improve the ability of researchers to analyze these data more effectively and share the results. This work will build upon the OpenNeuro project, which provides researchers with the ability to easily upload and share neuroimaging data. The first aim of this project is to develop the ability to process these datasets using national supercomputing resources. Because these resources are both much more powerful and more cost-effective than commercial cloud computing resources, this extension will allow researchers to process larger datasets using more sophisticated analysis procedures. The second aim is to extend the reach of data storage and processing beyond standard neuroimaging datasets to include heterogeneous datasets with clinical and psychological data in addition to brain imaging data. A large study of human brain development will be used as a test case for this extension. The third aim of this project is to engage researchers and software developers in order to develop a broad community that will further extend the reach and capabilities of the proposed technical developments and promote the sustainability of the resources beyond the grant period.
The first aim will implement the ability to execute computational workflows using national supercomputing resources through a Science-As-A-Service model, via technologies such as the Agave API and the Singularity container system. This will provide the ability for researchers to execute complex containerized workflows using large datasets, providing a long-term sustainable computational platform for analysis of open data. The second aim will involve the extension of the current OpenNeuro platform to represent data from a large longitudinal neurodevelopmental study, in order to allow the joint analysis of imaging, clinical, psychological, and genetic data. The third aim will engage the relevant user and developer communities through workshops and code sprints.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
