NeuroStorm: Accelerating Brain Science Discovery in the Cloud
Other Quantitative Biology
2018-03-22 v2
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.
Keywords
Cite
@article{arxiv.1803.03367,
title = {NeuroStorm: Accelerating Brain Science Discovery in the Cloud},
author = {Gregory Kiar and Robert J. Anderson and Alex Baden and Alexandra Badea and Eric W. Bridgeford and Andrew Champion and Vikram Chandrashekhar and Forrest Collman and Brandon Duderstadt and Alan C. Evans and Florian Engert and Benjamin Falk and Tristan Glatard and William R. Gray Roncal and David N. Kennedy and Jeremy Maitin-Shepard and Ryan A. Marren and Onyeka Nnaemeka and Eric Perlman and Sharmishtaas Seshamani and Eric T. Trautman and Daniel J. Tward and Pedro Antonio Valdés-Sosa and Qing Wang and Michael I. Miller and Randal Burns and Joshua T. Vogelstein},
journal= {arXiv preprint arXiv:1803.03367},
year = {2018}
}
Comments
10 pages, 4 figures, hackathon report