NeuroStorm: Accelerating Brain Science Discovery in the Cloud
Gregory Kiar, Robert J. Anderson, Alex Baden, Alexandra Badea, Eric W., Bridgeford, Andrew Champion, Vikram Chandrashekhar, Forrest Collman, Brandon, Duderstadt, Alan C. Evans, Florian Engert, Benjamin Falk, Tristan Glatard,, William R. Gray Roncal, David N. Kennedy
TL;DR
NeuroStorm is a cloud-based platform that aims to enhance brain science discovery by addressing data findability, accessibility, interoperability, and reproducibility through hackathon-driven development.
Contribution
This work demonstrates how focused hackathons can accelerate progress in neuroinformatics by improving data management and software interoperability in line with FAIR principles.
Findings
Improved data findability and access methods
Enhanced software interoperability for neuroscience tools
Reproducibility frameworks developed during hackathon
Abstract
Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capacities is hampered by technical challenges. The key barriers to accelerating scientific discovery correspond to the FAIR data principles: findability, global access to data, software interoperability, and reproducibility/re-usability. We conducted a hackathon dedicated to making strides in those steps. This manuscript is a technical report summarizing these achievements, and we hope serves as an example of the effectiveness of focused, deliberate hackathons towards the advancement of our quickly-evolving field.
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Taxonomy
TopicsBiomedical and Engineering Education · Cell Image Analysis Techniques · Scientific Computing and Data Management